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This book brings together papers presented at the 2017 International Conference on Communications, Signal Processing, and Systems (ICCSP 2017), which was held on July 14–17, 2017 in Harbin, China. Presenting the latest developments and discussing the interactions and links between these multidisciplinary fields, the book spans topics ranging from communications, signal processing and systems. It is aimed at undergraduate and graduate electrical engineering, computer science and mathematics students, researchers and engineers from academia and industry as well as government employees.



Wireless Networks


Demand-Aware Opportunistic Spectrum Access: A Game-Theoretic Learning Approach

We study the problem of opportunistic spectrum access with users’ demands in distributed systems. The users’ demands play an important role in estimating the final access results. For example, the same throughput may lead to completely different experience for the users with different demands. To emphasize the influence of the demand, we use the ratio of demand and throughput to consider them together. We focus on the sum ratios of each user to make the resource allocation efficient from the system view. We model the channel selection problem with demand-throughput ratio as a cooperative game, propose an ordered best response algorithm to achieve NE point and prove the existence of NE point. The stochastic learning algorithms has been used in simulations. The results show that the ordered best response algorithm and stochastic learning approach both converged and achieved good performance in fairness and utility which are better than random access situation. what’s more, the ordered best response algorithm has a significant improvement in convergence time.

Yuli Zhang, Xucheng Zhu

Spectral and Energy Efficiency Optimization Through Coordinated Transmission for Downlink Cloud Radio Access Networks

Cloud-based Radio Access Network (C-RAN) is capable of implementing flexible antenna installation and centralized processing to facilitate dense deployment of cells in the era of mobile traffic explosion. This paper investigates into the spectral and energy efficiency trade-off of C-RAN, and proposes optimized downlink coordinated transmission to enhance spectral efficiency (SE) and energy efficiency (EE). SE optimization is formulated as a sum rate maximization problem and solved by Lagrange multiplier method. EE optimization is formulated as a multi-objective function, and is then transformed into single objective function, which is solved by numerical search method. Simulations are conducted under different pre-coding configurations, and results demonstrate the effectiveness of proposed methods.

Ying Sun, Yang Wang, Gang Wu

Load-Aware Dynamic Access for Ultra-Dense Small Cell Networks: A Hypergraph Game Theoretic Solution

In this paper we research the load-aware channel allocation in ultra-dense small cell networks based on the hypergraph interference model. Cumulative interference is a hard nut to crack in ultra-dense networks because of the intensive distribution of low-powered and small-coverage small cells. The traditional binary graph interference model, which mainly focused on the pair-wise strong interference relation, can not capture the cumulative interference. Therefore, we use the hypergraph model to accurately describe the complex interference relation among small cells. The applications of hypergraph in wireless networks is in its infant stage. Considering the practical traffic demands of small cells, they can access multiple channels. To cope with this problem, we formulate the multi-channel access problem as a local altruistic hypergraph game and prove that it is an exact potential game, which admits at least one pure strategy Nash Equilibrium. To overcome the complexity of the centralized method and the constraint on the direct information exchange among small cells in hyperedges, a cloud-based centralized-distributed model is utilized. With the information shared in the cloud, a centralized-distributed learning algorithm can quickly search the Nash Equilibrium. The simulation results show that the proposed algorithm is superior to the existing binary graph-based schemes and significantly improves the communication efficiency.

Xucheng Zhu, Yuhua Xu, Yuli Zhang, Youming Sun, Zhiyong Du

Uplink Joint Resource Reallocation in a Multi-homing Heterogeneous System Based on Cognitive Radio

In this paper, a joint resource reallocation algorithm based on cognitive radio (CR) is investigated for power-constrained user equipment, in a multi-homing heterogeneous system with limited original subcarriers. Currently, all relevant works consider systems where networks run in separate frequency bands. Unlike them, we assume that they are capable of sharing spectrum resources by adopting CR to improve the resource utilization efficiency. Unlike conventional resource allocation, we jointly reallocate both the original resources and the detected new resources of a running system based on spectrum sensing results. This paper first proposes a CR-based uplink joint resource reallocation method on condition that networks can share spectrum resources. Then we formulate the proposed method, adopt the continuity relaxation method to convert the formulated problem into a convex optimization problem, and solve it. Finally, simulation results demonstrate the significantly improved performance of our proposed method, i.e., throughput and energy efficiency over the benchmark.

Xinyu Wang, Min Jia, Qing Guo, Yu Han, Wanmai Yuan

Spectrum Access Strategy with Two-Way Cooperation Based on Joint Allocation of Time and Bandwidth

In this paper, a two-way cooperative spectrum access strategy is proposed to optimize the performance of secondary user (SU), which is based on joint allocation of time and bandwidth. In the strategy, the unit transmission time is divided into three time slots. Primary users (PU) communicate with each other in the first two time slots with the help of secondary user. Thus the secondary user can access the spectrum to transmit its own signal in the third time slot. Besides, through joint optimization of time and bandwidth, the transmission rate of secondary user can reach the maximum when the target rate of primary user is guaranteed.

Ting Wang, Weidang Lu, Zhixia Wang, Hong Peng, Zhanghui Lu

Intermediate Performance of Rateless Codes over Dying Erasure Channel

In this paper, we propose a new rateless coding scheme for dying erasure channels with random channel lengths and time-varying packet error rates. Firstly, we propose a heuristic approach for suboptimal degree distributions based on AND-OR tree technique to achieve higher intermediate performance. Secondly, the optimal code length for the maximum average date delivery ratio is derived and analyzed. Simulation results demonstrate that our coding scheme outperforms existing conventional rateless codes with significantly better performance, which can be employed as a solution to the efficient large bulk transmission on dynamical and unreliable channels.

Shushi Gu, Jian Jiao, Qinyu Zhang

Efficient Design of Polar Coded STTD Systems over Rician MIMO Channels

In this paper, a polar coded space-time transmit diversity (STTD) scheme is proposed in order to improve the performance of MIMO system. In Rician fading MIMO channels, the corresponding polar coded STTD system can be equivalent to a single transmission channel for each polar code bit. Density evolutions for the polar coded STTD systems are proposed based on the analyses of the single transmission channel. The proposed density evolutions provide preferable guidance to construct polar codes for the polar coded STTD systems. Simulation results show that the BER performance of polar coded STTD system is significantly improved as the number of antennas increases. The proposed $$2\times 2$$ polar coded STTD system can provide better FER performance than LDPC-based system under low and mid code rates.

Bowen Feng, Jian Jiao, Shushi Gu, Shaohua Wu, Qinyu Zhang

Novel Cognitive Radio Network Setup Mechanism Using Underlay as Control Channel to Enhance Efficiency

Interest in Dynamic Spectrum Access (DSA) remains powerful as the communications community efforts to solve the spectrum congestion problem. However, the basic problem of control channel is one that impediment the deployment of such dynamic networks. Now many studies of control channel have shown that using spectrum holes to transmit control information is a common rule. While such rule is lacking in aspects below. Firstly, Second Users (SU) can not have a common spectrum hole as control channel which leads to low link of Second Users. Secondly, the arrival of Primary User (PU) is unknown which causes interruption on the use of control channel. In this paper, we identify and discuss the way to begin the initial communication and setup a Cognitive Radio network with no need of using spectrum holes to convey control information in multi-hop scenarios. Simulations and derivations can show the change of the performance on the front aspects.

Hui Han, Xiang Chen, Yun Lin

Multi-tier ON/OFF Scheduling Algorithm for Small Cell Networks with Renewable Energy

In the future cellular network, densifying the multi-tier heterogeneous cellular network (HetNet) via viral deployment of small cell base stations (SBSs) can increase energy consumption. In order to solve the energy problem in the future, SBSs that rely solely on energy harvesting can be adopted. In this paper, we focus on problem about multi-tier ON/OFF scheduling of SBSs and the goal is to minimize the overall cost of the network, including energy consumption costs and transmission delay costs of a HetNet. Finally, simulation results show, proposed algorithm can improve the overall performance of the network.

Yungui Mao, Zhi Chen, Dapeng Li, Lin Gao, Feng Tian

A Bidirectional Cooperation Spectrum Access Method Based on Time and Bandwidth Allocation

In order to eliminate the interference between primary user (PU) and secondary user (SU) and improve the transmission performance of SU, this paper proposes a two-way cooperation spectrum access method based on time and bandwidth allocation. Specifically, SU uses part of the time and bandwidth to help forward PU’s signal and uses the remaining time and bandwidth to send its own signal, which maximizes SU’s transmission rate while guaranteeing the PU to achieve its target rate. Since PU and SU works on different authorized bandwidth, respectively, they will not interfere with each other. Both the analyses and numerical simulation results illustrate the performance of the proposed spectrum access method, not only the interference between PU and SU can be eliminated, but also SU gains maximum transmission rate. Besides, primary system obtains a better performance.

Zhixia Wang, Weidang Lu, Ting Wang, Jie Zheng, Min Jia, Hong Peng

A New Static Routing Algorithm of GEO/LEO Hybrid Satellite Networks

With the rapid development of satellite mobile communication, building a satellite/terrestrial integrated network is the inevitable trend of satellite communication. Based on the network of backbone and access, a global coverage of GEO/LEO hybrid satellite constellations are designed. As the backbone network, GEO constellation realize relay and management. As the access network, LEO constellation realize the communication with the terrestrial users. A new static routing strategy based on virtual topology is proposed, which provides significant advantages of low complexity, high efficiency and low routing overhead. The satellite networks can provide the features of flexible structure, easy management, efficient transferring, and potential in scalability.

Tianjiao Gao, Qing Guo, Haitao Wang, Zhihui Liu, Min Jia

A Minimum Connected Dominating Set Based Multicast Routing Algorithm in Hybrid LEO/MEO/GEO Constellation Network

Multicast capability could provide excellent distribution services for globally scattered users in a multi-layer satellite network with global coverage. In this paper, we proposed a distributed routing algorithm for a hybrid LEO/MEO/GEO satellite constellation network based on a time-evolving Minimum Connected Dominating Set (MCDS) algorithm, which is constructed in a serial of slotted topology snapshots. The simulation results show that, the proposed routing algorithm could find an end-to-end route with less costs both in single and multiple time slots than the minimal spanning trees (SMT) algorithm, by making a trade-off between end-to-end hops and total path cost.

Ying Jing, Zhihua Yang, Xiaoli Liao, Xiaohan Qi

Performance Analysis of MIMO-HARQ Schemes in LTP for Space Information Networks

Recently, with the development of Ka/Q/V mmWave band high throughput satellites (HTS) and space information networks (SIN), distributed/virtual multiple-input multiple-output (MIMO) over satellite have attracted considerable research interest. In this paper, we propose a novel performance analysis framework for MIMO with orthogonal space-time block coding (OSTBC) under Licklider transmission protocol (LTP) in upcoming SINs, that the closed-form expressions of the mean number of transmission rounds for reliable data delivery in automatic repeat request (ARQ) and hybrid-ARQ (HARQ) schemes is derived by using Laplace transform. Furthermore, we derive throughput expressions for lossless- and truncated-HARQ schemes, and investigate the data delivery delay in LTP over Rayleigh and Rician fading channels. We also verify the accuracy of our derived closed-form expressions of mean number of transmission rounds through the Monte Carlo simulations.

Youjun Hu, Jian Jiao, Rui Zhang, Shaohua Wu, Shushi Gu, Qinyu Zhang

Multi-terminal Networking Algorithm Without Common Control Channel for CRAHNs

Considering the explosive growth of the wireless device and the serious circumstance for static spectrum allocation, the scarcity of radio frequency has become an increasingly apparent problem. Cognitive radio ad hoc networks (CRAHNs) is an emerging technology opportunistically accessing the licensed spectrum of the primary user (PU) by the secondary user (SU), which can improve the usability of existing allocated frequency spectrum. If SUs want to correspond with any other users, they should establish a communication topology network to exchange messages simultaneously and efficiently. Many methods to establish communication links between two users have been proposed. However, a multi-terminal networking technology is under-explored. In this paper, to establish the self-organizing network without CCC, the multi-terminal dynamic topology discovery algorithm is proposed, which builds a novel dynamic hierarchical tree-based architecture for the cognitive radio ad hoc networks (CRAHNs). Meanwhile, a protocol that ensures no interference to PU is designed, which rebuilds link between SUs effectively. Extensive simulations and analyze are conducted to evaluate the performance of the algorithm in terms of the success rate and networking time.

Yukun Wang, Wenbin Guo, Xiao Zhang

Collaborative Caching Optimization on Chunk Based Content in Fog Radio Access Network

Rapid development of smart devices and mobile applications brings about tremendous amount of traffic in mobile wireless access network. For content oriented applications, plenty of network traffic is usually derived from some popular contents that have been requested for multiple times. The traffic load caused by these contents can be alleviated by deploying cache at the edge of the radio access network. How to optimize caching resources and improve hit rate in F-RAN has become a hot research issue. In this paper, a framework called CCF-FRAN is proposed by integrating F-RAN and heterogeneous radio access network. The caching problem is formulated as a cache optimization placement problem to maximize the average hit rate of UEs based on content chunks. A collaborative chunk-based caching optimization algorithm called OA-BCC is presented and solved based on a binary search algorithm with low complexity. The simulation results validate the effectiveness of OA-BCC in term of average hit rate compared with Probability Caching, HPF and Random caching.

Haiya Lu, Zheng Guo, Dan Xu, Hao Jin, Chenglin Zhao

Parameter Fitting of C.Loo Model for Air-Ground Mobile Channels

With the rapid development of various spacecraft, aircraft and ground control communication requirements for the increasingly high-to-air transmission link research have received more and more attention of the agencies. Under the high-speed mobile environment of the aircraft, the paper has carried out air-ground transmission link. Considering the pure multipath signal, which is not affected by the role of the shadow, and the direct signal, which is affected by the shadow effect, we have designed C.Loo channel model. Based on minimum mean square error criterion, we get the influence of parameters on the data fitting degree of channel model and the most appropriate parameters for the data measured in this paper.

Zhenyong Wang, Jie Li, Dezhi Li, Gongliang Liu, Haibo Lv, Qirui Zhang

Research on Cognitive Satellite in Complex Environment Based on Dynamic Electromagnetic Spectrum Management

Compared with the space systems abroad, it is hard for domestic spacecraft to meet the increasingly high demand in future information war, especially in providing a complex environment awareness, avoiding the enemy jamming and deception and improving the anti-interference ability of the system as a whole. Based on the analysis of the existing problems on the basis of spatial information system construction, this paper integrates cognitive technology into the traditional space system, puts forward new concept cognitive satellite which has the function of dynamic perception, presents the cyclic process of the cognitive satellite. On the basis of the above, this paper proposes the architecture principles of the cognitive satellite and prospects the application study of the cognitive satellite. Developing the cognitive satellite can enhance our country’s advantages of system development and engineering application in the future, and the theory research can be in the position of the fundamental equilibrium compared with the developed countries in the new stage of space system development.

Jianjun Zhang, Ming Xue

Cooperative Spectrum Sharing for Multi-antenna Cognitive Networks with Joint Time and Power Allocation

In this paper, we proposed a cooperative spectrum sharing scheme for multi-antenna cognitive networks with joint time and power allocation which consists of a primary transmission (PT) node, a primary receive (PR) node, a multi-antenna secondary transmission (ST) node and a secondary receive (SR) node. Two-phase transmission protocol with variable time is used in our proposed scheme. The first phase is used for PT to transmit its signals to ST and the second phase is used for ST to relay and transmit its own signals at same time. We design beamforming factors with zero-force beamforming (ZFBF) and study the joint optimal time and power allocation to maximize the secondary transmission rate under the condition that primary system can achieve the target rate. The simulation results show the scheme is feasible and has a better performance compared with a fixed time allocation.

Hong Peng, Yanbing Wang, Weidang Lu, Xin Liu

An Updating Discrete Graph-Based Capacity Analytical Framework for Satellite Disruption-Tolerant Networks

In the satellite Disruption-Tolerant Networks (DTN), capacity of multi-path delivery is quite susceptible to a quasi-deterministic topology with limited resource in nodes. Currently, the space-time graph and event-driven graph, proposed for capturing the dynamics of DTN-inbuilt satellite networks, will incur excess demands of computation and storage with dispensable quantization errors. In this paper, we construct an updating discrete graph (UDG) based algorithmic model to make quantitative analysis on the capacity of a DTN-inbuilt Multiple Satellites and Multiple Ground Stations (MSMGS) networks. In particular, a network capacity analytical framework is established by solving a corresponding maximum flow problem with delivery delay and transmission constraints. The numerical results show that, compared with space-time graph and event-driven graph methods, the proposed method presents obvious improvements with respect to expected network capacity with limited complexity.

Peng Yuan, Zhihua Yang, Nan He, Qinyu Zhang

Overview of Asymptotic Capacity Analysis in Wireless Network Interference Management

In the wireless communication interference network, it is very difficult to calculate the capacity area accurately. The asymptotic capacity analysis of the interference network becomes one of the important means of the current capacity analysis. Therefore, the asymptotic capacity analysis and interference of the multi-cell interference channel Management technology is an important research issue in wireless communication. Based on the research background, this paper analyzes the status of the asymptotic capacity analysis of wireless network interference management, and it explores the research direction of the next step, and provide reference for the further development of progressive capacity analysis.

XiaoLin Jiang, Ming Diao, XiaoJie Chen, YanQiu Du

Data Analysis of Measurement Report and Diagnosis of Mobile Network Malfunction Based on K-Means Algorithm

With the rapid development of mobile networks, the number of mobile subscriptions has continued to increase. To efficiently assign mobile network resources, the network operator needs to process and analyze information and statistics about each base station and the traffic that passes through it. This paper presents an application of data analytic by focusing on processing and analyzing datasets from MR (measurement report) data form the actual mobile network. An analysis method based on k-means algorithm for the main service cell uplink SINR (Signal to Interference plus Noise Ratio) analysis of the base station is presented. The analysis of MR data includes data cleaning and K-means algorithm. The purpose of data cleaning is to remove duplicate information, correct existing errors and provide the data consistency. The K-means is an algorithm used for clustering the main service cell uplink SINR in MR data. Finally, through the simulation results, The reason for the malfunction of the base station is obtained. The result can provide support for network optimization and maintenance.

Kaisa Zhang, Gang Chuai, Weidong Gao, Xuewen Liu, Yifang Ren

Interference Analysis of Frequency Sharing in Satellite Terrestrial Integrated Mobile Communication System

One of the key technologies in integrated systems is frequency sharing. However, there is an unavoidable interference problem in heterogeneous networks. In this paper, through establishing Satellite Terrestrial Integrated Mobile Communication System, we analyze the problem of frequency interference in Satellite Terrestrial Integrated Mobile Communication System and calculate link budget. Based on the calculation of Carrier-to-Interference power ratio(C/I), this paper determines that some interference can be reduced by parameter coordination, but some interference requires some interference suppression techniques to realize the frequency sharing in Satellite Terrestrial Integrated Mobile Communication System.

Shujing Zhang, Mingchuan Yang, Xinye Shao, Xiaofeng Liu

Research on Location Management Strategies of LEO Satellite Communication System

With the continuous development of satellite communications, satellite communications have gone into the personal communication period, the corresponding location management strategy is particularly important in order to achieve hand-held terminal and personal communication globalization. In this paper, it is studied that the location management strategy for Fuxing low-orbit satellite communication system and proposes a two-layer database structure which includes the central database and the local database, and defines the location update and the location paging process as well as the detailed process design. At the same time, a paging optimization strategy based on the planning sequence algorithm is proposed for the subscriber stations with different speeds. As a result, the algorithm can reduce the paging signaling cost by 8% to 40% or so, to achieve the optimization effect. Finally, the corresponding influencing factors are analyzed according to the simulation results.

Ruixue Zhang, Zhuo Sun, Wenbin Guo

Downlink Analysis of HetNets with Millimeter Wave Small Cells

In this paper, the performance of a heterogeneous cellular network with both traditional sub-6GHz and millimeter wave (mmWave) links is investigated. Different from prior analysis, the interference in mmWave frequency band is incorporated into our model. Using the tools from stochastic geometry, the SINR coverage probability under maximum bias average received power association strategy is derived. The effect of sub-6GHz and mmWave small cells (SCs) density on the coverage probability is also analyzed to give insights on the network deployment. Simulation results validate the accuracy of our analysis, and reveal that different kinds of SCs have various influence on the network and need to be deployed properly.

Minwei Shi, Xianle Cao, Wanxuan Tan

Energy Oriented Resource Allocation in Heterogeneous 5G Networks

The development of 5G wireless communication systems are changing the daily life. Both transmission speed and Quality of Service (QoS) are developing fast. However, the increasing demand of data traffic brought about the number of base stations, which lead to the additional consumption of system power. Therefore, some of the power consumption is unnecessary by achieving same system performance. In this work, we discuss the resource allocation method in different policies to reduce energy consumption without losing the performance. Both theoretic and system level results are given in this work.

Yuan Gao, Hong Ao, Zenghui Feng, Weigui Zhou, Su Hu, Yixuan Huang, Xiangyang Li

The Design of Monitoring and Management System for Satellite Communication Network

Aiming at the problem that the frequency resources of the satellite communication network are easy to be occupied illegally and difficult to control, the time-division multiplexing technology is used to realize the monitoring and management of the satellite signaling channel. The signaling channel dual backup means is used to ensure the reliable transmission of the communication signal and realize the main service channel when the interference is automatically switched to the standby channel. This design improves the satellite communication availability and link stability.

Wangzong Huang, Jiangnan Huang

On the Downlink Outage Throughput Capacity of Hybrid Wireless Networks with MIMO

In this paper, the downlink capacity of MIMO fading channels in hybrid wireless networks is studied. First, we set up a wireless network model, with a wired network of base stations to support the remote communication of wireless nodes. MIMO technology is used to overcome the capacity bottleneck of the downlink. Then, we analyze the outage probability of the downlink and get the closed expression of the throughput capacity of the base station. Finally, the effectiveness of MIMO technology in hybrid wireless network is proved by computer simulation.

Baoju Zhang, Yuyin Wang, Wei Wang

Detection and Parameter Estimation of MIMO-LFM Signals by Fractional Autocorrelation Envelope

This paper proposed an improved method based on fractional Fourier transform (FRFT) for multicarrier LFM signals of MIMO radar (MIMO-LFM) by analyzing its characteristics. First, the intercepted signal model and FRFT are analyzed. Then the signal detection and parameter estimation of MIMO-LFM signals based on FRFT autocorrelation envelope is derived after analyzing the superiority and shortage of conventional FRFT. After that, the detection performance of the proposed method is deduced, and the theoretical results show that this method outperformance the conventional time-frequency method for MIMO-LFM signals processing. Finally, the simulation results demonstrate the validity of the proposed method.

Yifei Liu, Mingyue Kongxiang, Zhaoyang Qiu, Bin Tang

Rate Efficient Channel Coding Techniques and Estimation of Channel Reliability

Channel coding is a way of encoding data in a communication channel that adds patterns of redundancy into the transmission path to lower the error rate. Such methods are widely used in wireless communications. In this paper, an effort has been made to estimate the reliability of channel using the concept of channel polarization on polar codes. The legacy coding schemes like Turbo and LDPC codes outperform the basic polar codes successive cancellation decoding algorithm. A performance analysis has been to compare the schemes and it has been shown that there is a need to improve the basic successive cancellation decoder in terms of error performance for channel coding, as a result of which the performance of List decoding has been proven to outperform the basic decoding scheme but with a higher decoding complexity.

Supreet Huilgol, Qilian Liang

Energy Efficiency Maximizing with Power Allocation for Multi-user MIMO Systems Based on GZI Precoding

This paper investigates the problem of energy efficiency with power allocation for multi-user MIMO systems. Based on a practical power consumption model, the optimal transmit powers of the MU-MIMO downlink system are derived in the form of analytical expressions in order to maximize energy efficiency with satisfying quality of service requirements. Reducing the dimensions of variables and applying the properties of the Lambert function to solve the equations with the log function, this study solves the highly complicated optimization problem by deliberately manipulating the Lagrange function. Hence, a closed-form solution to the energy efficiency maximization problem for MU-MIMO systems is eventually achieved. Simulation results validate the efficacy of the proposed optimization scheme.

Feng Tian, Yue Yu, Tingting Zhao, Dapeng Li, Lin Gao, Zhen Yang

Utility-Based Delay Tolerant Networking Routing Protocol in VANET

Because traditional Internet architecture is not suitable for hash network environments like sparse distribution and intermittent connection of nodes, Delay Tolerant Networking (DTN) is proposed to address the delays and disruptions. In this paper, we propose a utility-based DTN routing protocol in Vehicular Ad Hoc Network (VANET). Through considering node distance, node speed, node direction angle, and node activity, the utility of node is defined and is computed to select node for forwarding messages. We simulate the proposed DTN routing protocol and six typical DTN routing protocols in a VANET environment. The simulation results show that our proposed utility-based DTN routing protocol is able to achieve a comparable performance.

Yongliang Sun, Yinhua Liao, Kanglian Zhao, Weixiao Meng

The Multi-user Scheduling Algorithm Based on BDMA Transmission in the Massive Multi-Input Multi-Output (MIMO) System

This paper makes use of the feature of space channel of the massive MIMO which means that the channel of each user in the beam domain focus on part of the beam to propose a kind of multi-user scheduling algorithm based on BDMA transmission. This algorithm takes the system and the rate as the principles to simplify the uplink and rate expression. The expression only needs to perform the calculation of the determinant according to the received related matrix of the base station. The dimension is only related to the quantity of the beam received by a single user. This paper obtains the instantaneous channel status information on the maximum beam of channel gain of each user through the estimation of the LS channel, also provides the transmission method selected by the beam, proposes to simplify the greedy algorithm for the user scheduling and at last perform the simulation directly at the multi user MIMO system user scheduling and characteristics of BRE which highlights the advantages of the algorithm.

Guanglong Yang, Xiao Wang, Wenbin Zhang, Yi Wang

A New Beam Selection Transmission Method in the Massive Multi-Input Multi-Output (MIMO) System

This paper makes use of the feature of space channel of the massive MIMO which means that the channel of each user in the beam domain focus on part of the beam to propose a kind of BDMA transmission. this paper takes advantage of the beam domain features of channel gain concentration to perform air separation multi-access transmission, In the Frequency division duplex (Frequency Division Duplexing, FDD) system, using the differences between channels, which will resolve the bottleneck of the pilot frequency brought by the massive antenna array in the mean time of matching the features of the massive MIMO system. The simulation directly at the downlink base SCM, thus considering that the base station uses only the beam selection transmission scheme where several antenna beams corresponding to its strongest direction are used to communicate with users. at last perform the simulation directly at the single user MIMO system user scheduling and characteristics of BRE which highlights the advantages of the algorithm.

Guanglong Yang, Xiao Wang, Shizeng Guo, Yi Wang

Construction of Check Matrix for B-LDPC and Non-binary LDPC Codes

In the high speed data transmission, Low-Density Parity-Check (LDPC) channel coding scheme is widely studied for its near Shannon limit and its good performance in the circumstance of low signal to noise ratio. The LDPC codes have several advantages over the Turbo codes and are one of the hottest topic in today’s coding theory research. Based on the research background, this paper has proposed the method for constructing a Check matrix of Binary LDPC. Secondly, the Tanner graph of B-LDPC is introduced in detail. Finally, The construction of Non-binary LDPC is investigated. Important rules of Non-binary LDPC are put forward. The factors that influence the performance are discussed and it explores the research direction of the next step.

ZhongZhi Lv

Performance Analysis of Asymmetric Two-Way Relay Channels with Physical-Layer Network Coding

Up to now, most of the researches about physical-layer network coding (PNC) are based on symmetric two-way relay channels. In this paper, we mainly study PNC in asymmetric two-way relay channels with Rayleigh fading channels and classify the systems into five asymmetric cases. So as to describe the asymmetric cases, we will introduce the asymmetric factors. We simulate the BER performance of PNC for symmetric and asymmetric cases with asymmetric factors fixed. After that we analyze the BER performance of PNC with one of the asymmetric factors is variable when two channels are relatively unreliable. Finally, we give the conditions that one kind of asymmetric scenario transforming to other kind. Also, in the matter of anti-noise performance, uplink asymmetry is the worst case and the phase asymmetry-downlink is the best case.

Bo Li, Zejia Shi, Hongjuan Yang, Gongliang Liu, Xiyuan Peng

Physical-Layer Network Coding in Shallow Sea Underwater Acoustic Channels

To improve the limited-bandwidth in shallow underwater acoustic communication, we propose to apply the physical-layer network coding (PNC) to this communication system. This paper analyzes the model of shallow underwater acoustic channel – “Ray Model” and uses the adaptive equalization technique to eliminate the inter-symbol interference (ISI). Besides, we also study the principle of PNC and research the demodulation and mapping scheme in relay node. Finally, we combine the channel model and PNC technique in two-way relay communication (TWRC) system. The performance simulation of PNC is compared with the traditional multi-hop scheme and network coding (NC) scheme. The result shows that PNC scheme can improve the throughput of system but do not increase the bit error rate (BER) in the shallow underwater acoustic communication. It provides a new research direction for shallow underwater acoustic communication, and also expands a new field for PNC applications.

Bo Li, Xuesong Ding, Hongjuan Yang, Gongliang Liu, Xiyuan Peng

Combined Denoise-and-Forward and Superposition Coded Physical-Layer Network Coding in Data Length Asymmetric Two-Way Relay Channels

To improve the bit error rate (BER) performance of physical-layer network coding (PNC) in data length asymmetric two-way relay communication systems, a new PNC scheme named combined denoise-and-forward and superposition-based physical-layer network coding (DNF-SC-PNC) is proposed, and the decoding algorithm of the scheme is improved. In the scheme, the mixed information is denoised and superposed in the relay node, which will be broadcasted to destination node. The destination node will use SIC or LLR algorithm decoding. Theoretical analysis and simulation results show that DNF-SC-PNC can provide better BER performance and better throughput rate performance when the data length is asymmetric. Furthermore, we also proved the LLR algorithm can provide better BER performance and better throughput rate performance than SIC algorithm when the data length is asymmetric.

Bo Li, Wenjing Cui, Hongjuan Yang, Gongliang Liu, Xiyuan Peng

The Joint Channel Equalization and Estimation Algorithm for Underwater Acoustic Channel

Underwater acoustic channel (UAC) is one of the most challengeable communication channels in the world, owing to its complex multi-path and absorption as well as variable ambient noise. Although adaptive equalization could effectively eliminate the inter-symbol interference (ISI) with the help of training sequences, the convergence rate of equalization in sparse UAC decreased remarkably. Besides, channel estimation algorithms could roughly figure out channel impulse response and other channel parameters through several specific mathematical criterion. In this paper, a typical channel estimation method, Least-Square (LS) algorithm is applied in adaptive equalization to obtain the initial tap weights of least-mean-square (LMS) algorithm. Simulation results show that the proposed method significantly enhances the convergence rate of the LMS algorithm.

Bo Li, Yu Zhao, Hongjuan Yang, Gongliang Liu, Xiyuan Peng

Adaptive Transmission Combining Physical-Layer Network Coding and Successive Interference Cancellation for Two-Way Relay System

When two wireless terminals exchange information through an intermediate relay, physical-layer network coding (PNC) improves the spectrum efficiency by allowing concurrent message transmission. In two-way relay systems, the performance gain of PNC under practical limits has been investigated. The results show that generally the performance would be significantly degraded by channel impairments like asymmetric channel gain at the multiple-access phase. As an alternative interference exploitation scheme, successive interference cancellation (SIC) works well when multiple sources’ signals have different power levels at the destination to successfully decoding. In this paper, an adaptive transmission scheme combing PNC and SIC is proposed for the two-way relay systems. Separate sum-rate simulation results for PNC and SIC show the opposite tendency with the channel impairment in two-way relaying, which means combining them would get a smooth sum-rate gain and let the system be more robust to dynamic scenarios.

Hailong Wang, Gang Wang, Bo Li

Joint Energy and Spectrum Allocation for Wireless Networks with Renewable Energy Supply Commonality

In this paper, a renewable energy supply commonality wireless network is studied. In the considered model, two BSs buy spectrum from their dedicated spectrum owners and purchase green energy from their common local renewable utility firms to produce resource blocks (RBs) to satisfy stochastic mobile users’ traffic demand and the process is controlled by the wireless network operator. And different BS’s RB consists of different units of renewable energy and spectrum. Toward this end, we use a game theoretic approach to explore the system and present the optimal solution under decentralized decision making. Finally, we provide numerical results to validate the optimal solutions.

Pengpeng Deng, Zhi Chen, Dapeng Li, Lin Gao, Feng Tian

Angle Estimation of Noncircular Source in MIMO Radar via Unitary Nyström Method

In this paper, a unitary Nyström method for joint direction of departure (DOD) and direction of arrival (DOA) estimation of noncircular sources in multiple-input multiple-output (MIMO) radar is proposed. Firstly, the noncircularity of the signals is used to enlarge the virtual aperture for improving the estimation performance. Then the real-valued signal subspace is achieved by using the unitary transformation and Nyström method, and finally the DOAs are estimated by combing with conjugate unitary ESPRIT (CU-ESPRIT) algorithm. The proposed method not only achieves the signal subspace without the estimation and eigenvalue decomposition (EVD) of the covariance matrix, but also involves real-valued processing. Thus, compared with the conventional conjugate ESPRIT and conjugate unitary ESPRIT algorithms, the proposed method has lower computational complexity. In addition, the proposed method provides comparable angle estimation performance. Simulation results are used to verify the effectiveness and advantages of the proposed method.

Xianpeng Wang, Mengxing Huang, Chunjie Cao, Hui Li

Analysis on Network Transmission Delay of Intelligent Substation

The various factors are resumed which affect the network transmission delay in intelligent substation. The accumulate calculation method of network transmission delay in intelligent substation is introduced particularly. The method is applied to calculate the network transmission delay of simple Ethernet, IEC61850-9-2 communication network, complex Ethernet, mixed network communication theoretically. At last, the impact of the indexes on the network transmission delay is analyzed.

Tiecheng Li, Liqiang Sun, Shaofei Guo, Li Zhang

A Social Aware Routing Protocol with Multi-social Features in Opportunistic Mobile Social Networks

With the widespread popularity and usage of ICT around the world, the ubiquity of data collection and transmission change our daily life and the society. Opportunistic Mobile Social Networks (OMSNs), formed by people moving around with mobile devices, enhance spontaneous communication among users that opportunistically encounter each other can be exploited to improve the performance of data forwarding. Existing protocols take advantage of spatial contact frequency and social characteristics to enhance transmission performance. However, they have not exploited enough of the relations and the effects between geographical information, social features and user interests. In this paper, we first evaluate these three characteristics of users and design a routing protocol call Geo-Social-Interest (GSI) protocol to select optimal relay nodes. We adopt Improved Optimal Routing (IOR) strategy to enhanced dynamic social features to more capture node’s social behavior to efficiently improve the routing protocol. We compare the performance of GSI to Epidemic and SimBet routing protocols using real INFOCOM06 data sets. The experiment results demonstrate that GSI overcomes the other protocols with highest data delivery ratio and low communication overhead.

Yibo Yang, Honglin Zhao

Research on Network Time Synchronization Method Based on SDH/PTN Transmission Network

On the IP network platform, based on SDH/PTN transmission network, Adopting the PTP standard protocol technology, a method of network time synchronization using Ethernet, POS and E1 is proposed. The method above is used in actual application environment, and the PTP network synchronization mode is optimized in the network environment that does not support the PTP protocol. On this basis the ideal network synchronization precision is obtained.

Wangzong Huang

A Cooperative Skip HO Scheme Based on Dwell-Time in Dense Small Cell Networks

In order to meet the growing demand for traffic, in the next generation (5G) mobile communication network, the network densification is adopted to achieve greater spatial spectral utilization rate. Thus it can improve the overall network capacity. However, the network densification brings a series of challenges, especially for the mobility management in UDN. The dense deployment of base station (BS) makes the handover (HO) rate too high, which in turn leads to too much HO signaling delay and cost. Thus it may offset the throughput gain that benefit from intensive. In order to solve this problem, this paper proposed a cooperative Skip HO scheme based on estimated dwell time. In this scenario, when the predicted dwell time is less than the threshold, a skip HO will be triggered to enter the cooperative transmission phase. Moreover, in this paper, the method of stochastic geometry was used to derive the triggering probability of the skip handover, the outage probability of the entire network, and the average user throughput. The simulation results show that the proposed method has improved the throughput performance compared with the traditional best connection method and the alternate skip handover method proposed in other literatures.

Han Yan, Gang Chuai, Weidong Gao

The Optimization of Power-Inversion Algorithm Based on DSP

Global Positioning System (GPS) is widely used in military and civilian fields. However, satellite being far from the ground, the signal is so weak that it is highly vulnerable to the influence of interference. When the power of interference exceeds the spreading gain offered via the global navigation satellite system, the receiver will unlock the satellite signal, which lost its ability to navigate. Power-inversion, as one of the most common used anti-jamming algorithm with antenna arrays, still has a large computation complexity. Hence, DSP chips are always used in this field because of its real-time signal processing capacity. In this paper, an optimization scheme of power-inversion algorithm is addressed based on TMS320C6678 DSP platform. Firstly, power-inversion algorithm is realized on DSP platform. Then we use library function optimization, QR decomposition (QRD) algorithm and compile options optimization methods to further increase the code efficiency. Exactly processing times are given before and after every optimization method. It can be seen from the experiment results that the optimized results is correct and the processing time is distinctly decreased after optimization.

Danyang Zhang, Xihua Wang, Jie Li

How Quick Is QUIC in Satellite Networks

Quick UDP Internet protocol (QUIC) was proposed by Google in 2012 as a reliable protocol on top of UDP. Compared with the widely used TCP for HTTP protocol, it is a new multiplexed and secure transport optimized for HTTP/2 semantics. The improvements of QUIC in terrestrial networks have been proved by previous researches, but few works have been done yet to evaluate the performance of QUIC via satellite links. In this paper, for the first time we evaluate the performance of QUIC, in comparison with HTTP/2 and HTTPS, via GEO satellite Internet access emulated on a dedicated testbed. The results of the experiments and our analysis confirm that QUIC does help reduce the overall page retrieval time in satellite networks. It is noted that QUIC outperforms HTTPS and HTTP/2 especially when the propagation delays are long and the packet loss rates are high, which is normal for GEO mobile satellite communications.

Han Zhang, Tianqi Wang, Yue Tu, Kanglian Zhao, Wenfeng Li

Study on the Magnetic Field Properties of Coil Array

As the degree of dependence on the mobile equipment such as smart phones, smart watches, wearable equipment, is more and more serious, the battery seems to be the restricts for people. In order to overcome the battery technology bottleneck, one method is quick charge, and the other method is wireless charging. However, quick charge often impacts the service life of the physical battery. Thus, the technology of wireless charging becomes the reasonable method. In the wireless power transfer system, the structure of the coil will determine the systems’ performance. In this paper, a novel coil array will be designed and analyzed. The quantitative results will give a global study base for the wireless power transfer system.

Xiu Zhang, Hao Qi

Research on Disaster Emergency and Data Recovery with Wireless and Satellite Networks

With the continuous development of the Internet, the scale of the data center is larger and larger, how to quickly carry out the data recovery and provide services has become a hot research topic in the disaster area. Wireless network communication system with flexible deployment characteristics and LEO satellite networks with covering a wide range are vital for disaster emergency operation and disaster recovery. In this paper, wireless networks and LEO satellite networks integrated regional disaster emergency communications and data recovery system are proposed. We design system architecture of the network and put forward a distributed data storage based on network coding. The network coding method for the distributed data storage and the data recovery principle is described in detail. The effect of network connectivity and the bandwidth demand based on network coding method is analyzed and the conclusion about network k-connectivity and data recovery for MDS (n, k). Finally the simulation analysis is done.

Chunfeng Wang, Shuai Yun

GIS and Signal Processing


Staring Beam Forming Method for LEO Satellite Communication System

Using LEO satellite systems to achieve personal mobile communication has many advantages compared to the geosynchronous orbit satellite system. It is a hotspot of research in recent years. However, due to its low orbital height and fast movement speed, LEO system is facing problems such as the user needs to switch beam continually, the effective communication time is too short etc. These phenomena increase the expense of the system. Adaptive beam forming method based on array antenna is an important way to solve those problems. In this paper, a beam forming method of “Staring” is performed. The method proposed can stare at the specific user during the period when the satellite is visible, the computational complexity is reduced by introducing the adaptive algorithm. Thus the satellite can effectively increase the duration for communication, reduce the frequency of beam switching and the system expense.

Yuqi Xu, Yumeng Zhang, He Zhou, Mingchuan Yang

A Novel Optimization Method of Building Joint Navigation System

This article aims to establish an emergency navigation systems rapidly when BeiDou Satellite System (BDS) breaks down for some target areas. A small satellite-BDS joint navigation system is proposed. The system supports to rebuild navigation service rapidly by using the least number of small satellites. In this plan, a creative method named the Backtracing Deletion Model is built. It could be used under the condition that some small satellites recover the navigation function of BeiDou Satellites. This scheme could arrange the whole satellite system efficiently under emergency, and it provides 24-h navigation service for some specific areas. The simulation results indicate the usefulness of proposed scenario and the scenario can be taken as a reference for the dynamically reconfigurable satellite system in future.

Jingxuan Hong, Qingyu Zhang, Youjun Hu, Tiantian Zhang, Houlian Gao, Ke Zhang

Land Ecological Condition Quality Comprehensive Assessment Based on RS and GIS in the Midwest Inner Mongolia

Land ecosystem is a historical complex of natural, social and economic, and it is the material carrier of human survival and development. What scientific problems to be solved are making an area systematic evaluation of land ecological quality and identifying the master factors impact it. This article using RS and GIS technology, integrating economic and social data, making a comprehensive evaluation on land ecological quality in the Midwest Inner Mongolia by AHP and comprehensive evaluation method, the results showed: land ecological basis of the research region was mainly affected by precipitation, ecological condition get worse along with the precipitation reduce from the southeast to the northwest. Land use type, pattern, patch’s diversity and land degradation is changes with the water resources quantity and human activity intensity. The population and GDP growth rapidly in the study area, but the ecological land reduced gradually, the ecological deficit, less construction, lack of protection.

Ruiping Zhou, Yanru Wu

The Analysis of Dynamic Change of Benchmark Land Price on Shuanghe Town of Togtoh County Based on GIS

The benchmark land price is a barometer of a land market activity. The research of dynamic changes of the benchmark land price has important significance for guiding the land market. Based on the benchmark land price updated results in 2011 and 2015 on Shuanghe town of Togtoh county. Comparing the ratio index of the benchmark land price internal structure, the change of benchmark land price of Shuanghe town was analyzed and the changing rule of ratio was summed up. The results showed that the price of commercial land was the highest, then the residential land, while of industrial land was the lowest. Commercial land at all levels of land as a whole are on the decline, the residential land at all levels of land are on the rise, and the grade four has the largest raise. In addition, the industrial land prices at all levels are rising. According to analysis on the four indices, as I found, the factors had great influence on land price of different level in Shuanghe town of Togtoh county include economic development, infrastructure and public service facilities, location, industrial structure, population and transportation and so on.

Xiao-Jing Li, Rui-Ping Zhou

Study on Desertification in Acukeerqin Banner Based on Albedo-NDVI Feature Space, ENVI, GIS and Computer

The study built Albedo-NDVI feature space model by using Landsat TM remote sensing image during 2007-2013, analyzed desertification situation of Acukeerqin Banner. The results showed that: these years, Mild desertification area of study area increased from 466.73 hm2 to 495.96 hm2, increased by 29.23 hm2. By 2013, the slight desertification area reached 591.82 hm2, have accounted 40.2% of whole area. During the study period, the moderate desertification area increased from 316.06 hm2 to 345.16 hm2, increased by 29.1 hm2, but the servere desertification land area decreased 43.82 hm2. It is shown that the land desertification problem has improved, overall has a good trend, severe desertification has slowed down under the management of preventive measures, as it change into moderate or mild desertification interval. The main causes of desertification in the study area are the excessive reclamation, population growth, reduction of rainfall and temperature rise.

RuiYan Wu, Yiliqi, Dun Er, Cai-Yun Yang, Ming Zhao, Rui-Ping Zhou

Study on Land Use Change of Energy-Rich Area in Western China Based on GIS and Computer

Dongsheng district as Chinese important resource of energy rich region, and belongs to the typical ecological fragile zone, the contradiction between the development of energy resources and the protection of the ecological environment has become increasingly acute, and land use change is the embodiment of the contradiction. This paper takes the land use change of Dongsheng as the research object, 1993, 2005 and 2014 land use database as the data source, using GIS software, combined with the land use changes spatial dynamic degree and land use change trend index model and other research methods, analysis of the Dongsheng District of various temporal and spatial variation of land use types and influencing factors during twenty-one years. Research shows that: the grassland, woodland and arable land changed most frequently. The area of agricultural land reduced the 125.514 km2, construction land increased 125.275 km2, agricultural land and construction land area changes in relative balance. In space, the change in spatial distribution characteristics of arable land and construction land is most obvious. The effects of land use change in Dongsheng region is mainly affected by the implementation of the national economic and social development and reform policy.

Yiliqi, Rui-Ping Zhou, Dun Er, Cai-Yun Yang, Rui-Yan Wu, Ming Zhao

Geospatial Object Partition Based on Angular Second Moment Kernel

Improvements in Synthetic Aperture Radar (SAR) image collection has revealed the ability to semantically describe scene complexity and abundant details. It is difficult for the traditional pixel-based methods to partition geospatial objects. A practical geospatial object partition method based on angular second moment kernel (ASMK) for SAR image is proposed. Firstly, a new kernel termed ASMK is designed in order to obtain accurate classification results. Then, based on classification results, river and urban areas as typical geospatial objects are partitioned. In order to obtain urban border accurately, a likelihood function to evaluate the possibility that one pixel belongs to urban area is established. Results of experiments with high-resolution TerraSAR-X spotlight data of the urban of Rosenheim in Germany demonstrate that the proposed method’s effectivity and accuracy in object partition.

Nengyuan Liu, Chuan Lu, Ming Zhang, Zongyong Cui, Zongjie Cao, Rui Min

Micro Drone Detection and Parameters Estimation Based on Micro-Doppler of Blades

Small unmanned aerial vehicles (UAVs) or micro drones are widely used for many applications in these years. But the misuse of micro drones may cause security issues. The problem of micro drone detection and parameters estimation is considered in this paper. Micro Doppler signatures of the drone’s rotating rotor blades are applied to identify micro drone. Firstly, the signal mathematical model of drone’s rotating multi-rotor blades is built and the flashes are used for detection. Then, the relationship between the micro Doppler signatures and the parameters of drones is analyzed. Furthermore, parameters, such as the number of blades, the number of rotor, the rotation rate and the length of blade, are estimated in this article. Finally, the results show that the effectiveness of the proposed method.

Xin Fang, Chuan Lu, Ming Zhang, Rui Min

An Enhanced Dynamic Neuro-Space Mapping Technique for Nonlinear Device Modeling

Accurate modeling of nonlinear microwave devices is critical for reliable design of microwave circuit and system. In this paper, a more general Neuro-SM method, i.e., an enhanced dynamic neuro-space mapping (Neuro-SM) is proposed to fulfill the needs of the increased modeling complexity. The proposed technique retains the ability of the existing dynamic Neuro-SM in modifying the dynamic voltage relationship between the coarse model and the desired model. The proposed Neuro-SM also considers output/current mapping besides input/voltage mappings. In this way, the enhanced dynamic Neuro-SM can produce a more accurate model of microwave devices with more dynamics and nonlinearity. The validity and efficiency of the enhanced dynamic Neuro-SM method are demonstrated through a high-electron mobility transistor (HEMT) modeling example.

Lin Zhu, Jian Zhao, Wenyuan Liu, Lei Pan, Deliang Liu

Research on Optical Fiber Location System of Coal Mine Based on Φ – OTDR

In view of the low sensitivity and the poor spatial resolution of the OTDR distributed optical fiber vibration sensing technology used in the underground positioning system of coal mines. Based on this theory, a distributed fiber vibration sensing technology based on Φ-OTDR (phase sensitive time-domain reflectometer) is proposed, and its structure and positioning principle are analyzed. Experiments show that the performance of the positioning system based on Φ-OTDR is better than that of OTDR, which improves the sensitivity and spatial resolution of the system effectively. Therefore, when a mine disaster occurs, the system can pinpoint the trapped personnel in the mine.

Jikun Guo, Sihan Chen, Qing Zhao

A Fast Vision-Based Indoor Localization Method Using BoVW-Based Image Retrieval

With the increasing demand for indoor localization service in our daily life, vision-based indoor localization has become a hot topic since image recording and application are very popular in the indoor environment. Based on the epipolar geometry algorithm, more images are required in the database to achieve better localization performance, which would inevitably lead to high time consuming for image retrieval. Therefore, in this paper we propose a vision-based indoor localization method by using the BoVW (Bag of Visual Word)-based image retrieval method, which could achieve less time consuming and good localization performance. The experiment results show that the localization error of the system by utilizing our proposed method could achieve an accuracy of less than 2 meters by a chance of 75%, while the time for localization sharply decreases by 60%. Compared with the traditional localization system, the proposed method could make a balance between the localization accuracy and efficiency in practice.

Lin Ma, Tong Jia, Xuezhi Tan

Efficient and Reliable Communication of Beidou Short Message in Smart Grid

Communication infrastructure is an essential part to the success of the emerging smart grid. Various communication technologies, such as EPON, PLC, Industrial Ethernet and GPRS/CDMA, have been widely used, which cannot adapt to remote mountain communities and natural disaster areas suffering earthquake, flood and so on. The unique short message subsystem of Beidou satellite navigation system provides a feasible solution to the above-mentioned problem. Unfortunately, there are some resource limitations about Beidou short message, i.e. limited capacity, limited frequency and unreliable transfer. The Automatic Repeat reQuest (ARQ) mechanism preserves reliability by resending the lost packets, which leads to performances degradation of goodput and delay. Whats worse, the transmission will be interrupted under communication constraints. To solve this issue, this paper presents an Adaptive Hybrid Error Correction (AHEC) protocol, which combines the advantages of Selective ARQ and Front Error Correction (FEC). Since the degree of redundancy injected into the coding is adjusted with the feedback information, namely, decreasing when the network is well-behaved and increasing when it is not, transmission performance using AHEC protocol can be obviously improved. The experimental results show that our methodology can increase the goodput significantly and the performance of AHEC protocol is 21.11% higher than the typical ARQ protocol in the case of 20% packet loss.

Dongjie Zhou, Xiaochen Tang, Jian Wang

Research of Entire Digital UAV Framework and Operating Mechanism Based on Simulate Training

Aiming at the modeling requirements of entire digital UAV, the structure and operating mechanism of entire digital UAV based on simulation training are studied. The class library structure of entire digital UAV model is established by using object-oriented and application framework technology. The operation process of entire digital UAV model list, the timing chart and execution flow chart of all kinds of objects are analyzed, and the operating framework of entire digital UAV is set up, laying the foundation for the further realization of UAV simulation training system.

Sen Yang, Guanghong Gong, Hairui Dong, Changlin Liu

A Multipath Redundant Transmission Algorithm for MANET

MANET is a new pattern of networking communication, and its application environment under battlefield is usually filled with the complex electromagnetic spectrum, the frequent hostile monitor and hostile interference. Thus the research on the anti-jamming and anti-interception for MANET is crucial. Our paper proposes a new multipath redundant transmission algorithm combining the multipath routing protocol with the packet redundant coding algorithm: when packet loss occurs due to the interference, the destination can recover the original data well by the other packets received. Moreover, owing to the multipath transmission, if a certain link is intercepted, it will be impossible for them to recover the intact data.

Xianlei Liu, Jun Han, Guanghua Ni, Chunhui Zhang, Yutao Liu

Periodic Cooperative Spectrum Sensing Optimization for Multichannel Cognitive Radio Network

In order to improve spectrum sensing performance of multichannel cognitive radio (CR) network, the optimization of periodic cooperative spectrum sensing is investigated. We seek to obtain spectrum efficiency maximization (SEM) and energy efficiency maximization (EEM) of cooperative spectrum sensing through jointly optimizing sensing time, subchannel allocation and transmission power. We have formulated a class of optimization problems and obtained the optimal solutions by alternating direction optimization and Dinkelbach’s optimization. The simulation results have indicated that SEM can achieve higher spectrum efficiency while EEM may get higher energy efficiency.

Xin Liu, Min Jia

Cooperative Spectrum Sensing-Based Wideband Cognitive Radio System Design

Cooperative spectrum sensing can improve detection performance of cognitive radio (CR) when the channel is in severe fading and shadowing environment. In this paper, we have designed cooperative spectrum sensing-based wideband CR system including transmitter and receiver. Each CR user marks the spectrum availability through energy detection and gets the sub-basis function through doing Inverse Fast Fourier Transform (IFFT) with the product of the spectral marker vector and the random phase vector. The cooperative spectrum sensing can be realized by cascading the sub-basis functions of all the users. The simulation results have shown that the proposed system can avoid the interference caused by the primary user and outperform the spread spectrum system.

Xin Liu, Min Jia, Weidang Lu, Feng Li, Deyue Zou

Diffuse Fingerprint Search Algorithm

Fingerprint positioning is a commonly choice for indoor positioning. It has a room-level positioning accuracy which is most necessary for indoor positioning because of efficient apply and circumvention of the occlusion and reflection of complex indoor structures. Clustering is a method commonly used in fingerprint positioning to reduce the workload of the search, but both the artificial clustering and automatic clustering have their own limitations. This paper proposes a diffusion-based fingerprint search strategy to accelerate the process of fingerprint positioning by using the results of the previous positioning as prior information. The simulation result shows that the proposed algorithm is superior to the traditional strategy in which we do clustering firstly and then positioning. At the same time, the positioning speed of our new algorithm is the same as the traditional one’s.

Deyue Zou, Qi Zhang, Xin Liu

Vulnerabilities in UMTS Location Update Procedure and Its Countermeasures

Mobile communication systems have been developing for decades. Universal Mobile Telecommunications System (UMTS) is a third-generation mobile cellular system for networks based on the GSM standard. As an evolved technology of GSM, UMTS has adopted a more reliable security mechanism. Integrity protection and mutual authentication were added in UMTS. However we carefully analyzed UMTS location update procedure specifications and uncover several vulnerabilities in UMTS. By sending specific types of LOCATION UPDATING REJECT messages during location update procedure, the rogue base station can deny all services to a target UMTS device. We also present several countermeasures including increasing the rate of TMSI reallocation, rebooting or re-inserting the SIM/USIM card and installing the protection application on UE to resist these vulnerabilities.

Zengshan Tian, Weiguang Li, Yujia Yao

Distributed Spectrum Detection Algorithm Based on Reliability and Diffusion Strategy

In cognitive radio networks, cooperative detection algorithms can be divided into two types: centralized and distributed. Traditional centralized algorithm need a fusion center to get the information from all cognitive users (CU), which will requires nontrivial routing resources. According to the defect, we propose a distributed spectrum detection algorithm based on reliability and diffusion strategy. The algorithm use SNR as reliability for the construction of network topology and fusion matrix. Through the diffusion strategy, CUs exchange information with their neighbors and make their own judgments independently. Simulation results show that the proposed algorithm has been improved in robustness, accuracy and speed of detection compared with centralized algorithm and non-cooperative algorithm.

Chaoxuan Fu, Chenglin Zhao, Yongjun Zhang

Cooperative Vehicle Sensing and Obstacle Avoidance for Intelligent Driving Based on Bayesian Frameworks

Vehicular Adhoc Networks (VANET) based vehicle sensing and obstacle avoidance is of importance and widely addressed in intelligent driving. Due to the difficulties in the data fusion from various types of observations from different vehicles, a dynamic non-parametric belief propagation (DNBP) method based on the Bayesian framework for target detection and localization is presented. Furthermore, the target detection performance can be jointly improved by adopting observations from multiple vehicles, based on the presented frameworks. The presented method is validated through simulations. The performance advantages achieved from joint detection from multiple vehicles are also evaluated.

Yuan Ma, Tingting Zhang, Xuanxuan Tian

LSODMRP: Improved-ODMRP Multicast Routing Protocol Based on Local Broadcast and Stable Links for MANET

ODMRP which is robust to node-moving because of its grid structure is one of most important multicast routing protocols used in MANET. However, periodically broadcasting join query messages over the whole network easily leads to a high network overhead. Inspired by the idea of locally searching widely used in objective tracking, we propose LSODMRP to address this issue. In this protocol, the join query messages are broadcasted over nodes nearby the multicast-related nodes smartly. To correct the deviation from the right forwarding nodes, a mixed global broadcasting of join query messages is implemented periodically. We also propose a GPS-free stable link selecting policy based on learning to improve the performance further. Finally, we compared the performance between ODMRP and LSODMRP in terms of overhead, end to end delay and number of delivered packets in node-independent scenario and group-uniform scenario. The simulation results show that LSODMRP can outperform ODMRP.

Chunhui Zhang, Yutao Liu, Xiaolei Ren, Yantao Guo

3D Sensing Techniques for Multimodal Data Analysis and Integration in Smart and Autonomous Systems

For smart and autonomous systems, 3D positioning and measurement is essential as the precision can severely affect the applicability of the techniques for a number of applications. In this paper, we summarize and compare different techniques and sensors that can be potentially used in multimodal data analysis and integration. These will provide useful guidance for the design and implementation of relevant systems.

Zhenyu Fang, He Sun, Jinchang Ren, Huimin Zhao, Sophia Zhao, Stephen Marshall, Tariq Durrani

Knowledge Based Fundamental and Harmonic Frequency Detection in Polyphonic Music Analysis

In this paper, we present an efficient approach to detect and tracking the fundamental frequency (F0) from ‘wav’ audio. In general, music F0 and harmonic frequency show the multiple relations; therefore frequency domain analysis can be used to track the F0. The model includes the harmonic frequency probability analysis method and useful pre-post processing for multiple instruments. Thus, the proposed system can efficiently transcribe polyphonic music, while taking into account the probability of F0 and harmonic frequency. The experimental results demonstrate that the proposed system can successful transcribe polyphonic music, achieved the quite advanced level.

Xiaoquan Li, Yijun Yan, Jinchang Ren, Huimin Zhao, Sophia Zhao, John Soraghan, Tariq Durrani

A Novel Nearest Feature Learning Classifier for Ship Target Detection in Optical Remote Sensing Images

Satellite remote sensing data is becoming more and more abundant, In order to realize automatic detection of ships on the sea surface, this paper presents an adaptive intelligent ship detection method, a novel nearest feature learning classifier (NFLC), which combines the scale invariant feature transform (SIFT) feature extraction with nearest feature learning classification. Due to the wide variety of detection ships, the NFLC can obtain a better experimental result than conventional detection methods. The detection accuracy is enhanced by the feature training in large databases and the performance of the system can be continuously improved through the target learning. In addition, compared to convolutional neural network algorithm, it can save the computation time by using the nearest feature matching. The result shows that almost all of the offshore ships can be detected, and the total detection rate is 89.3% with 1000 experimental optical remote sensing images from Google Earth data.

Bo Huang, Tingfa Xu, Yuxin Luo, Sining Chen, Bo Liu, Bo Yuan

Review of Evaluation Techniques for Infrared Imaging Seeker

This paper reviews the evaluation techniques at home and abroad on the development of performance in terms of Infrared imaging seeker. Introducing the design and development of infrared imaging seeker performance evaluation system. The anti-jamming performance, the target recognition ability and the working distance of the infrared imaging seeker are introduced, moreover, the corresponding evaluation method is introduced in detail. And the comprehensive performance evaluation of the seeker has been studied. The development trend of infrared imaging seeker evaluation technology is prospected.

Yongheng Zhou, ShaoHui Cui, Dan Fang

Hierarchical Topology Algorithm Based on Type of Service in PON

Passive Optical Network (PON) is a crucial access network which is widely deployed in modern society. With the development of network convergence, PON carries many differentiated services from not only the Internet, but also the telecom, TV broadcasting and smart grid. However, there exists different Quality of Service (QoS) requirements for the different services and it challenges our network on both the routing strategy and network management. Aiming at achieving load balance when there exists multiple services on network, we propose HTA-ToS algorithm, which provides load-balanced routing strategy for every type of service (ToS) while discriminating them according to their QoS requirements in routing process. To verify our algorithm, we design the scheme and implement it in the software defined network (SDN) controller Floodlight. The results show that the algorithms can improve the efficiency of load balance, and fulfill the QoS requirements of ToS to some extent.

Jiangzhou Li, Tao Luo, Yijun Guo, Huanhuan Luo, Guiping Zhou, Botao Yu

A New Binocular Stereovision Measurement by Using Plane-Space Algorithm

Aiming at the shortcomings in the existing measurement technology, this article presents a new measurement algorithm by Binocular Stereovision. First, find the coordinates of the target object in two different image sensors, then change the values of the coordinates according to the space coordinates system. According to the theories of space analytic geometry, the real coordinates of the target point will be calculated. Choose proper boundary points of the target, whose spatial information will reflect the spatial information of the target object. It is known by experimental data that the error rate within 1 m is less than 2%.

Enshuo Zhang, Shubin Wang, Yujuan Sun

Hyperspectral Image Vegetation Change Detection Based on Biochemical Parameters Inversion

Change detection of remote sensing images is a technology that one can get the change information by observing images of the same place obtained at different times. Hyperspectral remote sensing images can record detailed spectral information and reflect subtle differences between target and background. Hyperspectral change detection methods focus on changes between the different categories of feature, without fully taking the changes within the single ground type into account. In this paper, a hyperspectral vegetation change detection method based on biochemical parameters inversion is proposed. The change can be extracted from the vegetation biochemical parameters image by analyzing leaf water content, lignin content and other biochemical parameters. Experiments are conducted on both airborne and ground-based observation data. It shows that the change detection method based on biochemical parameters inversion reaches a high detection rate of 87.5% with a low false detection rate, which demonstrates superiority of the change detection methodology we proposed compared to other traditional methods.

Qingyan Wang, Junping Zhang

Implementation of a Pipeline Large-FFT Processor Based on the FPGA

This paper presents a scheme of pipeline large Fast Fourier Transform (FFT) processor on FPGA which is based on radix-2 Multi-path Delay Commutator architecture. For N-point FFT, the design uses log2N counters to control the working state of each stage of FFT and shift registers with storage of size 3N/2 − 2 to cache the intermediate calculated data. Compared with the dual-port RAM pipeline architecture with 2N memory sizes, the complexity of logical control is low because the intermediate calculated data is not stored and read by RAMs. The consumption of the memory resources is reduced. The proposed design is implemented of 1024-point FFT on an Altera Stratix II EP2S30F48414N FPGA. The highest operating frequencies are 250 MHz, and the time required to calculate FFT is about 6.3 ms. The results show that the design of the FFT processor meets the real-time requirement, and can be applied to large-point FFT computing.

Yongkui Ma, Henghao Liang

Online Automatic Test System Hardware Design for Certain Radar

Considering the high error probability of BIT and the excessive ATE of offline, this paper studies and designs an on-line automatic test system. The test system was designed, and the test requirements were analyzed in this paper. The interface signals of radar line replaceable units (LRU) on working condition are leaded out by three-port conversion card and conditioned with insulation technology, making the effect of the test system on radar minimum. Then the signal is acquired by virtual instruments based on PXI bus. Experiments verify the well test performance and efficiency of the test system.

Wanling Li, Peng Chen, Xiangjun Song, Deliang Liu

A Miniaturized Antenna by Loading Curved Branches for UWB Applications

In this paper, a compact Vivaldi antenna with a pair of curved branches is proposed. Compared to the traditional Vivaldi antenna, by adding a pair of curved branches, an additional resonant frequency is added in the low frequency band, and the bandwidth edge of the antenna at the low frequency band extends to 2.45 GHz, and the sidelobe level of the radiation pattern is reduced. In the operating band, the gain of the antenna is also improved a lot. In order to verify the validity of this proposed design, the proposed antenna model was fabricated and measured. The measured results show that this proposed antenna can cover a wide operating bandwidth of 2.45 GHz–11.5 GHz in a compact size of 30 mm × 36 mm and achieve good directional radiation characteristics. In the operating band, the measured gain is higher than 4 dBi. In addition, the measured group delay of this antenna is around 1.6 ns, and its variation is less than ±0.5 ns.

Qingsong Wang, Deqiang Yang, Hua Xiao, Dongdong Geng

Demodulation of 8PSK Signal with Gardner Bit Synchronization Using FPGA

In this paper, a new method of bit synchronization of 8PSK signal based on Gardner algorithm is proposed. When using Gardner bit synchronization, some improvements must be made to accommodate the demodulation of the 8PSK signal. Firstly, a detailed analysis of mathematical model for the Gardner bit synchronization is made, and then the algorithm simulation is accomplished on Quartus and ModelSim joint platform by Verilog HDL. The implement result by FPGA shows the feasibility and the stability of the proposed algorithms.

Honglin Zhao, Yun Gong

Digital Modulation and FPGA Implementation of MSK Based on SDR

With the rapid development of communication technology, the development of new communication systems and standards has been continuously raised, the demand for communication multimedia traffic has increased dramatically and the communication spectrum resources are becoming scarce. The minimum frequency shift keying (MSK) modulation is one of the constant envelope modulation schemes, which can produce modulated signals with constant envelope and phase continuity. In this paper, the related software radio technology is used to carry on the related research to the MSK, introduces the transmitter part and the receiver part of the digital modulation of the MSK and the related key technology. The MSK signal is generated by Matlab and the related principle is simulated. Finally, the digital modulation and demodulation of MSK is realized in FPGA design.

Zhaoxu Zhang, Zhigang Li, Zheng Dou

Fault Diagnosis and Health Assessment for Super-Heterodyne Receivers Based on ITD-SVD and LR

As a typical device widely used in electronics and information systems, the super-heterodyne receiver plays a key role in the whole system. This study proposes a method of fault diagnosis and health assessment for super-heterodyne receivers based on intrinsic time-scale decomposition (ITD)-singular value decomposition (SVD) and logistic regression (LR). First, a state observer based on radial basis function (RBF) neural network is designed to calculate the residual error between the actual and estimated signal outputs. Second, proper rotation components of the residual error are obtained by ITD. Then the singular values of the components are extracted by SVD to form feature vectors. Finally, a second RBF neural network is trained by the features to realize the classification of common fault modes, and the LR model is trained to estimate the health state of the super-heterodyne receiver. The feasibility and effectiveness of the proposed scheme are demonstrated by the results of simulation experiments.

Manxi Wang, Jinwen Sun, Chen Lu, Le Qi

Integrated Broadband PMR and Commercial Network for Multimedia Information Sharing

The development of broadband access technologies makes it possible for PMR network to improve both the performance and capacities. However, a fully deployed PMR network requires a long time and huge investments. The integration of dedicated and commercial networks could be a promising solution to this problem. This article contributes to the evolution of PMR networks by proposing a novel system for the integration of PMR and commercial networks. This system enables Internet users to communicate with PMR users by various access networks ranging from Ethernet to wireless networks like LTE and WiFi. Therefore, any authorized user can exchange multimedia information with PMR user with any device having access to Internet. Based on the extended SIP, a uniform interface of multimedia services is proposed for multiple access technologies. The functional and technical performance of the system is checked out on integrated test bed.

Jinsong Chen, Zufeng Xu, Hanqin Zhao, Jian Wang

Dynamic TDD Interference Mitigation Using Graph Theory Based Cell Clustering in 5G Ultra-Dense Network

Dynamic time-division duplex (TDD) is considered a promising solution to handle the unbalanced bursty and quick varied traffic in 5G ultra dense networks. However, dynamic TDD also bring out additional cross-link interference that may degrade the system performance. Since the network scenario of 5G becomes denser compared to LTE, the distance between user equipment (UEs) is smaller, UE-UE cross-link interference becomes more important and should be mitigated together with BS-BS cross-link interference. In this paper, we use cell clustering to deal with the cross-link interference. We find a better threshold for clustering and proposed a novel cell clustering algorithm based on graph theory. Simulation results show that the novel algorithm offers significant gain in UE SINR and UE rate compared with dynamic TDD without clustering and dynamic TDD with traditional clustering.

Mengli Guo, Gang Chuai, Weidong Gao, Yuhan Zhang

DTI Image Denoising Based on Complex Shearlet Domain and Complex Diffusion Anisotropic Filtering

Diffusion tensor imaging (DTI) is an imaging modality that has developed in recent years. It is a non-invasive technique and needn’t contrast medium. However, the SNR of DTI data is relatively low and clinically polluted by noise, which can bring serious impacts on tensor calculating, fiber tracking and other post-processing. In order to reduce the influence of noise on DTI images and improve the efficiency of diffusion tensor imaging effectively, a new DTI denoising scheme is proposed by combining the complex Shearlet transform and complex diffusion anisotropic filtering. The experiment results acquired from the simulated and real data prove the good performance of the presented algorithm.

Shuaiqi Liu, Pengfei Li, Ming Liu, Qi Hu, Mingzhu Shi, Jie Zhao

Analysis on Impact of Frequency Diverse Array Channel Errors on Beam Forming

In this paper, the influence of the channel errors on the Frequency Diverse Array is analyzed. The conclusion is different from phased array antenna. The channel error has a great influence on the beam pointing, but has little influence on the mainlobe gain of the beam pattern. And the sidelobe level is reduced and the main lobe is widened. Firstly, the channel error is modeled. The channel errors are modeled and the antenna pattern formulas with channel errors are derived. Finally, this conclusion is verified by Matlab.

Qingxiang Zhang, Xutao Guo, Wei Wang

A New Target Tracking Method Based on Morphological–Hough Transform

To start the tracking of targets in the environment with heavy clutters is always a problem in radar data procedure. In this paper, a Hough Transform method based on Morphology is proposed to solve the problem of starting track in radar system. This method first uses morphological method to reduce clutter and noise in imagery domain, then use the Hough transform to detect the starting tracks. Simulation results show that the method well detected the short straight lines of target starting track.

Tianjiao Feng, Jintao Cao, Yun Zhang, Hua Zong, Qinglong Hua

Study on the Change of Land Use Landscape Pattern Based on GIS in the West Development Zone of Inner Mongolia

Using GIS technology and landscape ecology method, taking Ordos Dongsheng area as an example, the landscape pattern change characteristics and driving factors of Inner Mongolia western energy development zone were studied. Based on the data of 1993, 2005 and 2014, a variety of landscape pattern indices were used to analyze the change characteristics of regional land use landscape pattern in the course of the study. It was found that during the study period, the land use landscape changed violently in the study area, the proportion of different landscape types area increased, the land use structure was mixed, the degree of landscape fragmentation became larger, and the landscape shape increased. Because of different natural, economic and social conditions, the land use landscape has different characteristics. Analysis of the driving process of the change of landscape pattern of land use in the study area that population growth and urbanization is the main driving force to change the landscape pattern of land use; Also the development of industrialization is another important driving force.

Cai-Yun Yang, Ming Zhao, Rui-Ping Zhou

Study on the Spatial and Temporal Changes of Land Use in the Typical Development Zones of Mineral Resources Based on GIS Technology

In this article, we study the spatial and temporal changes of land in the typical development zone of mineral resources. The research area is in Dongsheng district, Erdos city. Methods of ArcGIS spatial analysis technology and some models are employed in the article. The author using the land use Dynamic-degree change model dynamic measuring speed, through the transfer matrix of land-use, research and analysis the direction of the transfer of various land use types. The results show that: (1) From year 1993 to 2014, great changes had taken place in both quantity and structure of the land use of Dongsheng district; (2) During the study period, the variation range of woodland, cultivated land, grassland and urban- village industrial and mining land was larger. All in all, the dynamic changes in land use in the overall flat, but the urban construction land changes faster; (3) From year 1993 to 2005, the transfer of each land use type were larger than the 2005–2014. And the transfer of land was mainly between the cultivated land, grassland, Urban and villages land.

Er Dun, Rui-Ping Zhou, Yi Liqi

Wireless Communication


A Successive SLNR with GMD for Downlink Multi-user Multi-stream MIMO Systems Based on Pre-processing Matrix

Aiming to co-channel interference (CCI) and multi-stream for LTE downlink multi-user multiple input multiple output orthogonal frequency division multiple (MIMO-OFDM) system, a successive signal to leakage plus noise ratio (SLNR) with geometric mean decomposition (GMD) for downlink multi-user multi-stream MIMO systems based on pre-processing matrix is proposed. The algorithm utilizes precoding matrix based on SSLNR scheme to process emission signal at the transmitter, and the known leakages is canceled by dirty paper coding (DPC) algorithm. GMD is applied to cancel the known leakages, as all subchannels for this system have identical signal noise ratio (SNR), it is more convenient to reduce the influence of gain. Moreover, the received signal is treated by preconditioned matrix, the interference between different users is eliminated in further, the sum-capacity is improved by pre-processing Matrix. Meanwhile, the proposed scheme has no restriction of the number of antennas. The performance improvement is verified by simulation, the proposed scheme has superior bit error rate (BER) performance compared with the existing algorithm, when BER is 10−4, SNR is improved about 4 dB.

Liu Haitao, Xiao Jing, Zhang Yongjian

A Novel Sparse Channel Estimation Method for Multiuser MIMO Systems

Recently, smart terminals are getting more and more popular. With massive users accessing to the communication network, traditional medium access control protocals lead to high control overhead and low efficiency of resource usage. A novel multiple access control (MAC) scheme was proposed in [1] without resource allocation for small packet services. In their work, the channel state information (CSI) was assumed to be perfectly obtained at the BS. In our work, we study the performance of the MAC scheme with imperfect CSI and derive the theoretical analysis of channel estimation. Simulation results show that the performance degradation is small. The gap between the perfect and the estimated CSI is less than 0.5 dB with no more than 100 pilot symbols, which is enough to fullfill the demand in the MAC scheme.

Zhang Kun, Wendi Wang, Xiaohui Chen, Guo Wei

An Analysis for the Inter Bit Interference in Reading a Metal Barcode Label

The impedance change of the exciting coil caused by a linear metal barcode label was given. The expression of the inter bit interference (IBI) was investigated and it was similar to the inter symbol interference in the communication theory. The conditions for avoiding IBI were investigated. These predictions had been proven quite reliable by simulations. Some further suggestions on trading-off IBI against the barcode density were also given.

Hong-guang Xu, Yin Zhao, Qin-yu Zhang

Dynamic Pilot Assignment in Massive MIMO Systems with Time-Shifted Pilot

The time-shifted pilot with downlink data overlap considering an infinite number of antennas in base station can mitigate pilot contamination well, but there is still interference between the cells in the same group. Different from the conventional random pilot assignment method, this paper proposes a dynamic pilot assignment method based on the interference degree of cells in the same group of the system. For the system with severe inter-cell interference, we use the pilot assignment method which maximizes the center cell’s minimum uplink SIR considering the total interference to the user to mitigate pilot contamination. For the system with slight inter-cell interference, we use the pilot assignment method which maximizes the center cell’s average uplink SIR considering the total interference to the user to improve its performance. The effectiveness of the pilot assignment method proposed in this paper is verified by simulation experiments.

Shuangshuang Jiang, Bin Wang

Widely Linear Adaptive Beamforming Algorithm Based on Minimum Sensitivity and Eigenspace

The conventional minimum variance distortionless response (MVDR) beamformer becomes suboptimal for the noncircular signals, and deteriorates when the training samples are limited. The eigenspace-based (ESB) WL MVDR beamformer is proposed, which utilizes the eigenstructure of the correlation matrix to enhance the performance of the WL MVDR beamformer. Further, an eigenspace-based widely linear beamformer for noncircular signals using the minimum sensitivity criterion is proposed, which can be used for reducing the performance degradation when the dimension of the SI subspace can not be estimated correctly. Simulation results show that the proposed method has a better performance.

Liping Huo, Xingpeng Mao, Liang Xin, Yunmei Shi, Guangyan Li

Low-Complexity Signal Detection Based on SOR Method Exploring an Efficient Relaxation Range for Massive MIMO Systems

In order to reduce the complexity of Massive multiple-input multiple-output (MIMO) signal detection, the iterative method is utilized for signal detection. Based on the implementation and analysis of the successive over relaxation (SOR) iterative algorithm, it can achieve near-optimal performance and can reduce an order of magnitude for the computational complexity. The simulation results that employing optimized relaxation factor can achieve the low bit error rate with less iteration and an efficient relaxation range is obtained to guide the relaxation factor selection.

Yigang Zhou, Lin Wang, Liming Zheng, Yu Mao

Pre-decision Method for MWC-Based Wideband Spectrum Sensing

The solution to high sampling rate plays a key role in the development of wideband spectrum sensing (WSS), and MWC system is considered as a popular choice under the sub-Nyquist framework for WSS due to efficient hardware implementation. However, MWC system runs under the assumption that PU signals are present in the concerned frequency band. Obviously, it may cause high false-alarm probability and unnecessary waste. In this paper, the Grouping Random Extraction Ratio (GRER) pre-decision algorithm is proposed to address the above issue. By using the MWC compressed sample, closed-form expression of the decision threshold is derived under the Neyman-Pearson criterion. Simulation results are provided to demonstrate the performance of the proposed algorithm.

Xue Wang, Min Jia, Xuemai Gu

A Multipath Effect Suppression Algorithm Based on the GM-PHD Filter in Skywave-OTHR

The target detection mechanism of Skywave Over The Horizon Radar (Skywave-OTHR) endows itself many advantages, causing meanwhile a series of problems in detection and tracking. Among the rest, the effect of multipath sharps focus. In this paper, based on the application of Gaussian mixture probability hypothesis density (GM-PHD) filter in the tracking of skywave radar, a multipath effect suppression algorithm is proposed. In order to determine whether the multipath phenomenon is existed and suppress its effect, the target states, which are the results of the inversion calculations of the radar measurements, will be transferred into the real trajectory of the targets after the processing of GM-PHD. The algorithm is verified by computer simulation.

Di Chen, Xiangyu Zhang

Design of Rateless Transmission Scheme Based on Punctured Polar Codes

In this paper, a parallel concatenated punctured polar (PCPP) codes is designed to realise the rateless property of polar codes. First, an improved random puncturing pattern of polar codes is proposed to archive better performance than random puncturing. Then, the optimal initial code rate is analyzed for multiple PCPP code blocks transmission in slow fading channels, which the optimal initial code rate of each new PCPP code block is determined by the overhead of the previous successful decoded code block and each packet can be transmitted with encoding construct of a 2-level PCPP codes.

Sha Wang, Jian Jiao, Bowen Feng, Shaohua Wu, Shushi Gu, Qinyu Zhang

Performance Analysis for Multi-pair AF Massive MIMO Systems with Imperfect CSI and an Eavesdropper

In this paper, we consider a multi-pair amplify-and-forward (AF) massive MIMO system, where an eavesdropper (Eve) can intercept the information which sent to multiple destination users form multiple source users via a relay. The system performance will be analyzed for different power-scaling laws when zero-forcing reception/zero-forcing transmission (ZFT/ZFR) is employed at the relay. And minimum mean-square-error (MMSE) estimator is utilized due to imperfect channel state information (CSI). Analytical results reveal that with the number of relay antennas tending to infinity, the user’s achievable rate will increase to a fixed value, and the eavesdropping information will decrease to a fixed value. Simulation results well validate analytical results.

Jie Ding, Yang Liu, Meihua Zhou

Bounds on the Finite-Length RaptorQ Codes Under Maximum Likelihood Decoding

In this paper, we analysis the maximum likelihood (ML) decoding failure probability (DFP) of finite length RaptorQ codes with a high-order low density generator-matrix (LDGM) code as the pre-code. By investigating the rank of the product of two random coefficient matrices, we derive upper and lower bounds of DFP on the RaptorQ codes under ML decoding algorithm. Finally, we verify the accuracy of derived theoretical bounds through the Monte Carlo simulations with different degree distributions. The high accuracy bounds can be used to design near-optimum RaptorQ codes with short and moderate lengths.

Ke Zhang, Jian Jiao, Shushi Gu, Shaohua Wu, Qinyu Zhang

Timing Design for LTE Protocol Stack on General Purpose Processor

Achieving LTE protocol stack on general purpose processor (GPP) faces a crucial issue, in which the computing power of physical (PHY) layer is weaker than that of the embedded prototype and the gap cannot be narrowed in short term. In this paper, we design a compromise method to the issue where medium access control (MAC) can reserve enough time for PHY and the overall performance of the system degrades slightly. In particular, to meet the requirements of the scheduling in advance and the hybrid automatic repeat request (HARQ) timing, we first spread the two requirements into seven demands in scheduling diagram. Then, we can get the final scheduling timing accordance with the seven demands. The theoretical analysis and the functional test results of the prototype are finally provided to verify the feasibility of the MAC timing design.

Shuzheng Liu, Siqi Liu, Weilian Kong

MAX-SIR Based Optimal Modulation Order Selecting of Generalization Hybrid Carrier Systems Under Doubly Selective Channels

To find the optimal modulation order of generalization carrier system (GHCM) under doubly selective (DS) channels, we in this paper proposed an optimal order selective algorithm based upon maximum signal interference ratio (MAX-SIR). We first provide the GHCM employing multi-weighted type fractional Fourier transform (M-WFRFT). Moreover, we also elaboratively derive the MAX-SIR based optimal selective algorithm. The proposed algorithm, employing some numerical simulations, has been demonstrated to be effectiveness under DS channels.

Yong Li, Zhiqun Song, Xuejun Sha

An MMSE Beamforming Algorithm Based Hybrid Carrier System over Doubly Selective Channels

In this paper, we proposed an MMSE Beamforming algorithm based hybrid carrier (HC) system over doubly selective channels. HC system based on 4-weighted fractional fourier transform (4-WFRFT) has been proved to be a better choice over doubly selective channels. By exploiting 4-WFRFT, the modulation mode of the system can be switched between single carrier (SC) system and orthogonal frequency division multiplexing (OFDM) system and can be matched with the characteristics of doubly selective channels. This paper presents an adaptive MMSE beamforming algorithm for HC system with a linear array antenna. The optimal weight vector of the algorithm is derived by pilot signals. In case of knowing the exact direction of arrival (DOA), HC system with MMSE beamforming algorithm can achieve a great improvement of BER performance, in comparison to that without MMSE beamforming algorithm. Moreover, HC system, under proper modulation order, performs better than SC and OFDM system with MMSE beamforming algorithm over the typically doubly selective channels.

Bo Yang, Zhiqun Song, Yong Li, Xuejun Sha

Polar Channel Coding for the Ultraviolet Communication System Combating Path-Loss Propagation and NLOS Effects

With little interference from atmospheric environment, the prospect of ultraviolet (UV) communication in the solar blind region (220 nm–280 nm) is promising. Due to the large path-loss propagation and the no-line-of-sight (NLOS) attenuation, the intensities of UV beams may be severely degraded, and thereby the efficient transmission distance is heavily decreased. In this paper, we design and implement a scheme of UV communication system, with polar channel coding to enhance the efficient transmission distance. Both numerical and experimental results show that our scheme is able to reach a longer efficient transmission distance in contrast with the existing low-density parity-check (LDPC) scheme and uncoded OOK scheme, in the UV communication system.

Wenxiu Hu, Min Zhang, Dahai Han, Qingbo Chen, Menglong Wu, Lin Ai

Outage Performance of Cooperative Deep-Space Downlink with Backbone Relaying in SBINs

In this paper, we investigate the performance of cooperative deep-space downlink with an amplify-and-forward (AF) backbone relaying in Space-based Information Networks (SBINs). In this SBINs communication scenario, we assume both the source-destination and relay-destination links undergo the shadowed-Rician fading, and the source-relay link follows the Rician fading distributions, respectively. Moreover, the effect of satellite perturbation of backbone relaying satellite is considered, and the maximum ratio combining is implemented at the terrestrial destination. Based on this setup, we first derive the approximate statistical distributions of signal-to-noise ratio of the system, then the closed-form expressions are obtained to efficiently evaluate the outage probability (OP) of the system. Finally, some simulation results are provided to verify our analysis.

Houlian Gao, Jian Jiao, Rui Zhang, Shaohua Wu, Shushi Gu, Qinyu Zhang

Differentiated Data Transmission Based on Instantly Decodable Network Coding

In order to solve the problem of the differentiated data transmission caused by different terminal processing capabilities, we propose a method to transmit differentiated data based on the improved IDNC (instantly decodable network coding). The scheme divides data into layers according to the quality and gives a high priority to the basic layer at retransmission to ensure low delay for low-processing capability terminals. Then a heuristic largest clique algorithm maximum weight clique (MWC) is proposed to adapt to this retransmission process. Simulation results show that the method can indeed realize the differentiated transmission of data. Furthermore, the proposed MWC algorithm can significantly reduce retransmission times compared to the traditional retransmission method without IDNC.

Weixia Zou, Yang Zhao, Ting Jiang

Methods of Subframe Number Detection and Timing Offset Estimation of Non-signaling Test Based on LTE

Along with the popularization of 4G communication technology, non-signaling test technology of mobile terminals becomes increasingly important. Since it eliminates the process of signaling interaction and uplink synchronization, the measuring equipment must primarily find the starting position of a subframe in the received data to extract all data of this subframe and acquire the subframe number before performing a test. According to the connection between demodulation reference signal (DMRS) and subframe number, in this paper, we propose two blind detection methods of which the first one is the bimodal interval detection method that only exploits DMRS and the other one is the position contrastive method which exploits both DMRS and cyclic prefix (CP). Furthermore, the corresponding simulation model is established and evaluated respectively. Finally, a joint method combining the advantages of these two methods is suggested. Both real test and simulation prove the joint method is of good performance.

Qiao Li, Siqi Liu, Yuan Yao

Constant Envelope OFDM RadCom System

A joint radar and communication system would constitute a unique platform for future intelligent transportation networks effecting the essential tasks of environmental sensing and wireless communication. While the inherent high peak-to-average power ratio (PAPR) question of OFDM system cannot be solved. This paper introduces a constant envelope multi-carrier RadCom approach with the advantages of high data rate, high ability of anti-fading, simple radar processing, and constant 0 dB PAPR. Constant envelope OFDM RadCom system is able to solve the high PAPR question perfectly, promote efficiency of power amplifier and resistance to fading.

Yixuan Huang, Qu Luo, Shiyong Ma, Su Hu, Yuan Gao

Block Adaptive Least Mean Square Algorithm for Satellite Multi-beamforming

Modern satellite communication systems are designed to meet broadband, high-capacity and high-speed service requirements, but spectrum-limited and quality-of-service issues due to spatial multiplexing of spectrum resources can not be ignored. Because of the multicast mode, the interference problem between multi-users in satellite communication is very serious. Therefore, multi-beam forming in the digital domain is the development trend of multi-beam forming structure. In this paper, we propose a block-adaptive least mean square algorithm, which is based on the strong rainfall attenuation of the Ka-band GEO satellite system. The algorithm is applied in the use of 37 array elements evenly arranged phased array antenna to form 7 spot beams. The convergence and tracking characteristics of the improved algorithm are analyzed by comparing the typical LMS algorithm. Finally, a pattern of the given coverage area beam is formed.

Yumeng Zhang, Xiaofeng Liu, Mingchuan Yang

Analysis of the Relay Multiple-Receiver WPT System

The magnetic coupling resonant Wireless Power Transfer (WPT) for multiple-receiver has a wide application prospect. In this paper the relay method is applied to multiple-receiver wireless power transfer systems. In order to analyze the energy efficiency of the multiple-receiver WPT system with relay coil, an equivalent method is proposed, in which the multiple-receiver system is equivalent to a single receiver model. It is proved that the multiple-receiver WPT with relay coil is more efficient than the general multiple-receiver system when the coupling coefficient between the transmitting coil and the relay coil is sufficiently large. It is pointed out that the multiple-receiver WPT system with relay coil is more suitable for long distance, small size, high load and so on. The conclusion is proved by numerical simulation.

Yuming Huang, Li Li

GFDM System PAPR Reduction Based on MCT Method

The most serious problems of OFDM are the high Out-Of-Band (OOB) Radiation and high Peak-to-Average Power Ratio (PAPR). So that it can’t use the fragmented spectrum and will also increase the system operating costs, reduce efficiency as well. Thus the Generalized Frequency Division Multiplexing (GFDM) comes into being as a candidate for the fifth generation (5G) wireless communication. GFDM can reduce the out-of-band radiation effectively but still suffer from pretty high PAPR. To solve this problem, studies have shown Clipping method can be used to reduce PAPR. However the computational complexity will increase along with the increase of the subcarrier number, and lower clipping threshold will cause severer impact on the signal distortion which is because the Clipping causes irreversible loss on large signals. In this paper, we propose a new method called majorizing compressing and expanding technique (MCT) to suppress the high PAPR of GFDM system. This method compresses high power signals, and expands low power signals at the transmitter and makes the inverse transformation at the receiver, so that the signal amplitude fluctuation is smaller and closer to the average, thus reduces the PAPR. Our simulations also reveal that there is a tradeoff between PAPR reduction and bit error rate(BER) performance. And a comparison between Clipping and MCT will be given to show that MCT performs better.

Yaqin Zhao, Chentong Wu, Longwen Wu, Chunliu Li

The Bit Error Rate of Binary Communication System Under Digital Modulation Jamming

Based on the background of high efficient electronic warfare and a lack of theoretical analysis of optimal jamming, this paper proposes an accurate formula for bit error rate (BER) of binary victim signal corrupted by two-dimensional digital modulation jamming and added white Gaussian noise (AWGN). It is shown that the binary communication receiver usually adopts maximum likelihood (ML) reception as the optimal criterion. Based on this property, the formula of BER is applicable for modulation schemes including BPSK, 2ASK, 2FSK etc. Results of transmission performance of binary communication system under various jamming are evaluated by simulation. Jamming performance against BPSK modulated signal is discussed as well.

Xiaotong Zhang, Tianyu Xu, Zhiguo Sun, Changqing Deng, Hong Xie

Design of Low Density Parity Check Codes for Secure and Reliable Communications

With the symmetric cryptosystem based on error correcting codes and the concept of equivalent matrix, this paper puts forward a secure communication scheme based on linear block codes. The proposed scheme realizes the secure and reliable integrated communication by hiding and changing the coding matrix (parity check matrix or generator matrix) randomly and simultaneously without decreasing the error correction ability of linear block codes. And also, based on RDF (Random Difference Families), we propose a design method of QC-LDPC codes based on the proposed secure and reliable communication framework. The proposed QC-LDPC codes have a large number of performance equivalent parity check matrix with the same parameters. At the same time, the LDPC codes hold better reliability of transmission and flexibility of design. Finally, the security and reliability of the proposed LDPC codes are verified by analysis and simulations.

Fengcheng Lyu, Zhiping Shi, Rui Tang, Liuyue Gan, Yajun Ren

Research on Threshold Selection Algorithm for Adaptive Modulation and Coding Scheme

With the satellite communication as a key technology to achieve global seamless coverage, how to meet the different types of business needs and achieve reliable transmission of information under the conditions of limited resources have become an important issue that we need to face currently. Adaptive modulation and coding technology has good link adaptive effect in the satellite mobile communication fading channel. By assessing the merits of the channel state, the sender changes the various parameters of signal dynamically to achieve the purpose of improving system performance in different channel environments. Therefore, in order to make the system have the best adaptive transmission effect, it is necessary to select the most suitable MCS. In this paper, we first discuss the MCS selection algorithm, and simulate in the three different satellite channel environments to determine the thresholds of modulation and coding scheme.

Hao Cui, Zhigang Li, Zheng Dou

Massive MIMO Uplink Synchronization Scheme Based on Selected-Beam Combining

In wireless communication systems that potentially operate in interference, acquisition and temporal alignment of a transmitted signal by a receiver can be the most fragile component of the link. In this paper, we study multicarrier multiuser multiple-input multiple-output (MU-MIMO) system, in which the base station employs an asymptotically large number of antennas. For Massive MIMO uplink synchronization transmission, we work out a selected-beam combining method to enhance performance in beam domain channel. Simulations demonstrate the performance boosts by taking advantage of the selected-beam combing.

Yue Zhao, Jiajun Zhang

A Low Complexity Primary Synchronization Algorithm in LTE System

In LTE (Long Term Evolution) system, Primary synchronization effects calculation of physical cell identity and the recognition of full duplex mode directly. This paper presents an improved algorithm based on FFT fast correlation to realize the search for half frame data with the method of combining overlapping and segmented correlation, and make the preceding data cyclic shift to guarantee sequence integrity. The improved algorithm greatly improves the synchronization speed, and can meet the time delay requirements for time-frequency two-dimensional search. Theoretical analysis and experiments show that the algorithm can effectively reduce the amount of calculation and the synchronization time.

Zengshan Tian, Jian Xu, Xiaolong Yang

Research on Beamforming Algorithm for Group Scenario in Broadband Trunking System Downlink

In recent years, broadband trunking system has attracted much attention as its high rate, which can replace narrow band trunking system in private network. Beamforming technology, developed from smart antenna technology, sending the signal precoding processing, can effectively improve the system’s energy efficiency. In this paper, the multicast beamforming algorithm based on the group user CSI is proposed to improve the energy efficiency of the system. Multi-user beamforming technology can improve the energy efficiency of BSs in group scenarios of broadband Trunking system, and guarantee the QoS of group users. The two optimization problems are both NP-hard. The paper adopts SDR, dropping some constraints in the original optimization problem, transform the original optimization problem into SDP to achieve the approximation solution. The improved algorithm guarantees the QoS of the group users by changing the priority of the user. Multi-user beamforming technology can improve the energy efficiency of base stations in group scenarios of broadband Trunking system, and guarantee the QoS of group users.

Chengwen Zhang, Xuanhong Yan, Shizeng Guo, Chenguang He

Crosstalk Among OAM Modes Through Air Channel: A Simulation Perspective

OAM modes can be used to increase the information capacity in the free-space optical (FSO) communication systems. The air turbulence, however, contaminates the wavefront of OAM-carrying beam. The crosstalk among OAM modes are induced, which degrades the performance of FSO systems significantly. We studied the crosstalk among OAM modes resulting from the air turbulence from a simulation perspective in this paper. The OAM-carrying beam propagating through air channel has been emulated by Monte-Carlo phase screen and Fresnel diffraction approaches. The numerical results revealed that the air turbulence effect could induce the partial energy of transmitted OAM mode leaking into its neighboring modes, thus causes the crosstalk remarkably.

Ming Li

Average Capacity and Power Optimization for Full-Duplex DF Relaying with Large-Scale Antenna Array at the Destination

Full-duplex relaying system, which allows the relay node to transmit and receive at the same time and over the same frequency, can realize a significant enhancement of spectral efficiency. Besides residual self-interference, there exists another challenge for the full-duplex relaying system, i.e., the destination always treats the source-to-destination link as interference. To overcome this challenge, the large-scale antenna array is employed at the destination. By using the characteristic that the channel vectors of source-to-destination and relay-to-destination become asymptotically orthogonal, the system average capacity is derived and the optimal transmit power of the relay is obtained by maximizing the average capacity. Numerical results show that the system average capacity can be enhanced significantly compared to direct transmission and the optimal transmit power of the relay is determined by the residual self-interference.

Liang Han

Channel Estimation Using Pilot Method for Underwater Filter Bank Multicarrier System

Filter bank multicarrier (FBMC) modulation is well-thought-out as a promising contender for communication systems, it may perhaps substitute orthogonal frequency division multiplexing (OFDM) in terrestrial communication and in underwater acoustic communication (UAC). Herein this paper, we insinuate the channel estimation by means of coding pilot and auxiliary pilot technique for underwater FBMC system. We contemplated multipath underwater acoustic channel with additive white Gaussian noise. Herein we equated the BER performance between OFDM and FBMC, the experimental outcomes ascertained that the BER of FBMC is better than OFDM exploiting multipath underwater acoustic channel.

Naveed Ur Rehman Junejo, Jiaquan Yan, Saifullah Adnan, Hailan Chen, Haixin Sun

Random Back-Off Mechanism for Contention-Based Uplink of SCMA

In the 5G mobile communication network, massive connectivity is one of the requirements. In this paper, we study the SCMA contention-based uplink to achieve massive connectivity. SCMA can provide a higher overload with limited resources. On this basis, the uplink users adopt the mechanism of random back-off to contend to access the system. The number of access users can be further increase. The traditional OFDMA and SCMA with a scheduling method were compared in the simulation. The simulation results show that our approach has a good performance in the number of access users and throughput over a certain limit.

Wei Wu, Yong Hao

Channel Compressed Estimation Based on k-Nearest Neighbor Learning

MmWave communication is receiving tremendous interest by academia, industry, and government for 5G cellular systems. Due to the short wavelength, the millimeter wave experiences high path loss and penetration loss. Compensating for path loss will require beamforming, which is based on channel estimation. However, in the actual environment, the number of multi-path is unknown. In order to solve the problem in millimeter wave system, this paper estimates the number of multi-path by utilizing k-Nearest Neighbor learning. Then we use the OMP algorithm to estimate the channel. The simulations show that the k-Nearest Neighbor learning can get better performance of channel estimations in the mmWave MIMO communication.

Hua-Feng Zhang, Chen-Guang He, Wen-Bin Zhang, Kuo Zhao

Research on the Effect of Near-Field Plates to Electromagnetic Field

The technology of wireless power transfer (WPT) is used to transfer the power wirelessly through the magnetic field in the space and to charge the electrical equipment such as computer, mobile phone, electric vehicle, implantable medical devices. During the process of transmission, the radiation of magnetic field will reduce the systems’ efficiency. In order to address this problem, in this paper, a near-field plates (NFP) is designed and analyzed to interfere electromagnetic wave generated by the transmitting loop in near field, so that NFP can improve the performance of the WPT system through focusing the electromagnetic field. When the NFP is places in the WPT system, the electromagnetic field in the vertical direction of the transmitting loop will be concentrated, while the others direction of the electromagnetic field is weakened. Thus, the electromagnetic field radiation into the surrounding environment will be reduced. In this paper, the simulation results indicate that the NFP can enhance the intensity of magnetic field and restrain electromagnetic radiation.

Xiu Zhang, Zhihan Zhang

Review on Cognitive Radio Technology for SatComs

The demand on the crowded spectrum in satellite communication (SatComs) is greatly increasing due to the explosive growth of mobile terminals and applications. However, the present spectrum allocation policy suffers from a lot of drawbacks, because it leaves spectrum holes for the incumbent users. At present, much attention is paid to cognitive satellite technology because it copes with these drawbacks. In this paper, we investigate several major aspects of cognitive satellite communication technology. First, we sort out main scenarios of cognitive SatComs. Then, we list the development of the essential techniques in cognitive radios for SatComs. More specifically, we elaborate three techniques including spectrum sensing, interference modeling and beamhopping. At last, we make a conclusion and prospect of cognitive SatComs.

Hao Yin, Zhenyu Na, Zhian Deng

Performance Analysis of MRC Technique in DF Cognitive Relay Networks

A common combing technique that Maximum Ratio Combing (MRC) in decode-and-forward (DF) cognitive relay network has been studied in this paper. The direct links are available and the maximum relay selection is utilized to select the ideal relay for communication in our system, and all channels are Rayleigh fading channels. We present the secrecy outage probability (SOP) for measuring the system performance and observe that the diversity order is $$K+1$$ from the asymptotic SOP, where K refers to the number of relays. Simulation results are also provided to inspect the veracity of analytic results.

Jie Ding, Qiqing Yang, Yunyue Xie

A Social Centrality-Aware D2D Multicast Scheme for Content Dissemination

Device-to-device (D2D) communication is conceived as a vital component for 5G cellular networks to improve spectral reuse, and enhance system capacity. For content dissemination, D2D communication also provides an efficient way, and the influence of social interactions among mobile devices has attracted substantial attention due to its potential impact on resource allocation. Aiming to enhance the dissemination efficiency and link stability, a social-aware D2D multicast scheme that exploits social network property of centrality for content dissemination is proposed. Based on the multi-dimensional centrality we defined, a multicast clustering scheme is proposed. Then, a bipartite graph is constructed to represent the matching problem of multicast clusters and channel resource, and Kuhn-Munkres (KM) algorithm is introduced to solve the channel allocation problem optimally. Simulation results demonstrate the effectiveness of our proposed scheme, which significantly improves the efficiency of content dissemination.

Shaoshuai Fan, Hui Tian, Weidong Wang, Shuo Wang

Adaptive Multi-feature Fusion for Correlation Filter Tracking

Robust visual object tracking is a challenging task in computer vision. Recently correlation filter-based trackers (CFTs) have aroused increasing interests because of the good performance and high efficiency. However, most feature representations for CFTs are not discriminative enough, which makes the trackers unreliable in complicated and changing scenarios. To address the problem, this paper presents an adaptive multi-feature fusion method based on kernelized correlation filter (KCF) framework. First we select HOG, LBP and grayscale feature for fusion to obtain more complementary and powerful feature. Then we propose a novel multi-feature fusion strategy, and adaptively calculate the feature’s fusion weight using probability separability criterion. The experimental results show that our method not only achieves better accuracy compared with existing features for KCF tracker, but also achieves state-of-the-art performance when running at 87 frames per second.

Linfeng Liu, Xiaole Yan, Qiu Shen

Research on the Resource Allocation Algorithm in the WFRFT-Based Hybrid-Carrier System

In high speed mobile communication environment, time dispersion caused by multipath interference and frequency dispersion caused by Doppler shift weaken the effect of traditional frequency domain resource allocation algorithms on WFRFT-based hybrid-carrier systems. In order to solve this problem, this paper proposes a fractional domain resource allocation algorithm which is able to take the channel conditions into consideration. By adjusting the fractional order, the proposed method can suit different transmitted signals, therefore has better performance in time-frequency doubly dispersive channels. Simulation results show that the proposed fractional domain resource allocation algorithm has better BER performance than traditional frequency domain one in the hybrid-carrier system.

Hongwei Niu, Liang Ye, Zhuoming Li, Jifu Shi

Radar Techniques


ISAR Imaging of Object with Varied Rotation Rate by Polynomial Coefficients

The new technique of inverse synthetic aperture radar (ISAR) imaging for object with varied rotation rate is introduced. It is assumed that the polynomial phase signal (PPS) model is appropriate for the radar echo signal, and the radar image could be achieved via the polynomial coefficients. Here, the radar echo signal is modeled as PPS with order three, and the polynomial coefficients are estimated by the improved form of Chirplet decomposition. Numerical results show the correctness for the proposed technique.

Yong Wang, Bingren Ji, Bin Zhao, Rongqing Xu

Sliding DFT for Spectrum Analysis of Coherent Wind Lidar

The Pulse Coherent Wind Lidar has a wide practical prospect in the field of atmospheric sounding. However, it confronts the contradiction that the spectral resolution and the range resolution can’t be improved at the same time under the technology of conventional spectrum analysis. Based on the motion’s continuity of the aerial aerosol and the air molecular space, this paper proposes a time-domain sliding DFT, which expanded the number of points in the database, to analyze the radial sampling data. then, the spectrum analysis results of traditional DFT, sliding DFT and windowing & sliding DFT were simulated in this paper; finally, the speed accuracy of above three methods were compared. The result shows that sliding DFT can effectively improve spectrum resolution and range resolution, but the speed accuracy is significantly influenced by wind speed shear, and the window functions can be adopted to restrain spectrum peak widening/multi-peak phenomenon so as to effectively control the speed accu-racy.

Fugui Zhang, Yang Qi, Haijiang Wang

Doppler-Radar Based Hand Gesture Recognition System Using Convolutional Neural Networks

Hand gesture recognition has long been a study topic in the field of Human Computer Interaction. Traditional camera-based hand gesture recognition systems can not work properly under dark circumstances. In this paper, a Doppler-Radar based hand gesture recognition system using convolutional neural networks is proposed. A cost-effective Dopper radar sensor with dual receiving channels at 5.8 GHz is used to acquire a big database of four standard gestures. The received hand gesture signals are then processed with time-frequency analysis. Convolutional neural networks are used to classify different gestures. Experimental results verify the effectiveness of the system with an accuracy of 98%. Besides, related factors such as recognition distance and gesture scale are investigated.

Jiajun Zhang, Jinkun Tao, Zhiguo Shi

Research on Clutter Suppression Method of UWB Signal in the Mine Under the Landslide

When the signal of UWB through the coal mine tunnel, the signal of effective target scattering is formed, and the strong back-scattering clutter signal which comes from the roadway wall is also produced. In order to suppress or eliminate the interference of the roadway wall clutter, this paper presents a clutter suppression algorithm based on Kalman filter model and SVM. In this method, the Kalman filter model suitable for the underground environment is constructed. The clutter estimation and the target-clutter separation are treated as the process of mutual influence. The target probabilities are tested by the conditional probability of each model. Then the SVM classifier suitable for the underground environment is constructed, and the filtered clutter signal is further suppressed and separated. The simulation results show the effectiveness of the proposed algorithm.

Jikun Guo, Qing Zhao

Frequency Diverse Array Radar Beamforming Algorithm Based on FFT

The frequency diverse array radar has a linear increasing frequency offset between the array elements, which produces a range-angle dependent beampattern. And it overcomes the disadvantages of the phased-array providing range-independent beampattern and offers many promising advantages for radar applications. Fast Fourier Transform was considered on beamforming to improve the efficiency of algorithm. Due to the linear frequency offset between the array elements, each element carry out Phase compensation. Then beamforming using FFT algorithm. As the array element increasing heavily, this algorithm can reduce the operation and improve the running speed effectively as data show. In addition, this algorithm reduces the requirement of hardware and can be realized easily.

Xutao Guo, Qingxiang Zhang, Wei Wang

Optimal Transmission Policy Based on POMDP over Ka-Band Channels in SINs

The Ka-band channels can provide an appealing capacity for the future deep-space communications and space information networks (SINs). In this paper, the noise temperature of time-varying rain attenuation at Ka-band channels is modeled to two states Gilbert-Elliot channel, to capture the channel capacity that randomly ranging from good to bad state. An optimal transmission scheme based on Partially Observable Markov Decision Processes (POMDP) is proposed, and the key thresholds for selecting the optimal transmission method for space information networks (SIN) are derived. Simulation results show that our proposed scheme can effectively improve the throughput.

Xindong Sui, Jian Jiao, Shushi Gu, Shaohua Wu, Qinyu Zhang, Weiqiang Wu

The Multi-parameter Analysis of the Influence on Internal Wave Imaging by Space-Borne SAR

Synthetic aperture radar (SAR) is widely used in remote sensing and surveillance area, including observing internal waves (IWs). In this paper, the basic form of IW is studied in order to find out the affection of radar parameters, which can help improve the precision of IW parameter estimation by SAR sensor. A new method is proposed to analyze the influence of internal waves. Simulations and experiments are drawn, and the result proved the proposed analyzing method efficient for understanding the internal waves and the influence of radar parameters.

Jintao Cao, Yun Zhang, Yinsheng Wei, Yicheng Jiang, Yunyun Meng

High Resolution Range Profile Analysis in an OFDM Integrated Radar-Communication System

Due to the data transmission requirements in traditional orthogonal frequency division multiplexing (OFDM) radars, the phase-coded OFDM (PC-OFDM) waveforms in which the PC sequence is controlled via transmitted messages are presented for radar-communication integrated applications. A radar data processing algorithm that achieves high range resolution profile (HRRP) for the single-scatter-point target is presented. Theoretical and numerical results show that, the proposed method can achieve HRRP on target detection along with the relative high data rate wireless communications.

Xuanxuan Tian, Tingting Zhang, Qinyu Zhang, Zhaohui Song

Research on the OFDM Passive Radar System for Low-Altitude Target Detection

Detection of low-altitude targets such as Unmanned Aerial Vehicles (UAVs) has practical implications on aviation regulation. In order to achieve a low cost-benefit ratio, a passive radar system based on the OFDM communication signal is applied to study the echo processing methods. In this paper, the receiver is elaborated by the adaptive filter, Constant False Alarm Rate (CFAR) and several modules. The wideband ambiguity function (WAF) is derived then the contributing parameters are employed as the basis of base stations selection. Theoretically, two conclusions are verified: MQAM-OFDM is fit for passive detection on account of pin-shape WAF; employing an improved CFAR may achieve the probability more than 90%.

Xiaoqi Yang, Weidong Jiang, Kai Huo, Jingjing Zhao

False Target Recognition Method Based on RCS Fluctuation Characteristics

In this paper a false target recognition method based on RCS fluctuation characteristics is proposed for one radar. The RCS fluctuation information of the false target is used for the false target discrimination. The RCS of true target usually fluctuates, however the RCS of false target with track characteristic is constant. According to the radar equation we can estimate the RCS base on the SNR estimation and range estimation. Then the test statistics are constructed based on the RCS estimation. At last the logical decision is used to improve the algorithm performance. The effectiveness of the proposed approach is verified using two simulations and the algorithm has excellent performance on the recognition of false target and true target.

Dianxing Sun, Xiang Chen, Ke Xu, Jianwei Wan

Compressive Sensing in UWB Echoes

Ultra-wide band (UWB) signals have very wide bandwidths. On the basis of Nyquist sampling theory, it is too difficult for A/D converters to sample such signals. This issue confused people for a long time until compressive sensing (CS) was proposed. CS in UWB was brought into focus once it appeared because CS can get useful information with abandoning a lot of redundant data and UWB signals are easily sparse. Hence it is usually used in UWB to deal with sampling problems. This paper mainly describes the principles of CS and its mathematical theory, and then compares the different transform matrices, measurement matrices and reconstruction algorithms based on UWB echoes. Finally, find a best method to recovery UWB echoes with Gaussian white noise.

Jie Ren, Jing Liang, Jian Zhang

Detection of Single and Double PSs Based on Scattering Characteristic in SAR Tomography

Synthetic aperture Radar (SAR) tomography has been widely used in 3D reconstruction in urban area. Nevertheless, how to exactly detect persistent scatterers contained in one range-azimuth resolution pixel still requires further researching. In this paper, a new detection method based on scatterer’s characteristics is proposed. The model is built under the hypothesis test theory and determines threshold according to probability of detection and false alarm. In the experiment with SAR images acquired by TerraSAR-X, this method has exhibited good performances in detecting single and double persistent scatterers.

Zhenyu Hou, Hui Luo, Zhen Dong

Rateless Coding Scheme Based on Autoregressive-Moving-Average Model over Ka-Band Links

Future deep space explorations and spatial information networks (SINs) are with the increasing demands for high data rate services, the application of Ka-band channel is viewed as a primary solution. However, the Ka-band channel is much more sensitive to the weather conditions than S/C/X-band channels. In this paper, the noise temperature on Ka-band channel is modeled as N-states Markov channel, and a practical time-varying rain attenuation prediction model is proposed based on the Autoregressive-Moving-Average (ARMA) model. By considering the tradeoffs between transmission latency, reliability and power allocations consumptions, we design an adaptive rateless coding scheme based on the analog fountain codes. Simulation results show that our proposed scheme can effectively improve the throughput and efficiency.

Jian Jiao, Bowen Feng, Rana Abbas, Shaohua Wu, Shushi Gu, Qinyu Zhang

Resource Allocation for Secure Communication in Cooperative CR Networks

This paper investigates joint resource allocation to provide information security in a five nodes CRNS system, which includes a primary transmitter (PT), a primary receiver (PR), a secondary transmitter (ST), a secondary receiver (SR) and an eavesdropper (E). To ensure the security of the information, PT and PR are allowed to use part of power to transmit artificial noise to confuse the eavesdropper. PT firstly transmits signal containing secrecy information and artificial noise by using all power and bandwidth resources. Then ST as a trusted relay accesses to the licensed bandwidth and allocates a fraction of bandwidth resources to forward primary information in decode-and-forward (DF) mode. As a reward, it can utilize the remaining bandwidth to transmit its own information simultaneously. We study joint optimization of the bandwidth, time and power allocation to maximize the secondary rate while satisfying the secrecy transmission rate requirements of PR. Numerical results demonstrate that our strategy can realize win-win result.

Weidang Lu, Kecai Gu, Zhanghui Lu, Hong Peng

Parallel Processing Implement Construction of Target Echo Simulation Based on Real Track

In order to produce large amounts of timeliness data rapidly and simulate the echo signals effectively, this paper proposes a digital reconstruction model which uses real track information extracted from Google Earth route to construct the echo and utilizes the corresponding processing algorithms to realize the track. Due to the time of the original CPU platform producing the same amount of echo signal data is an extremely protracted process, the method of applying high-speed parallel capabilities of the Graphics Processing Unit (GPU) based on the CUDA platform to participate in echo reconstruction and track simulation is presented to improve the operating speed. Comparing the real track with which obtained by the echo simulator, the results not only verify the validity and consistency of the two processing algorithms based on the real track reconstruction of Google Earth, but prove the fast floating-point computing capability of GPU whose power has great advantages of enhancing the performance of simulated echo signals and echo signal simulation algorithms.

Min Hu, Shibo Yan, Qiang Yang

Space Objects Recognition Based on ISAR Image

In this paper, a method of spatial object recognition based on ISAR image is studied, and the recognition result of four kinds of spatial objects is given by simulation. Firstly, the feature of ISAR image is extracted based on two-dimensional wavelet transform and Gabor wavelet transform, and then the sub-optimal search method is used to compress the feature to improve the efficiency. Finally, the BP neural network is used to identify the target. The simulation result validates the effectiveness of the proposed algorithm.

Zhenyuan Ji, Hongyan Jin, Yun Zhang, Encheng Hu

Target Detection Based on High-Level Image Information for High-Resolution SAR Images

With the rapid development of sensor technology, the higher resolution SAR images we can acquire. Therefore, we pay attention to not only the low-level image information but also the high-level image information when we detect target. Due to the multiplicative speckle noise largely interferes with its use, active contour model (ACM) is not appropriate for the target detection in SAR images, but we can make the most of the high-level image information (contour) offered by the method for target detection. Therefore, we introduce a target detection method based on ACMs in the paper. Two groups of comparison experiments show that the proposed method not only overcomes the difficulties that traditional ACMs are applied in target detection for SAR images, but also outperforms classical Markov random field (MRF) model in terms of accuracy. Besides, the proposed method is appropriate for the design of the SAR automatic target recognition (ATR) because of the use of ACM.

Qi Li, Ye Zhang

A Network Intrusion Detection Algorithm Based on Outlier Mining

A spectral clustering and Local Outlier Factor (LOF) based outlier mining algorithm, which is aiming to solve network intrusion detection problem, is proposed in this paper. First of all, the structure of similarity matrix method in spectral clustering is used for data preprocessing to find out the smaller similarity objects. During this process, the pruning of the outliers is completed, and a set of candidate outliers is obtained. Then, we calculate the local outlier factor of each data object in this set through LOF algorithm. And the final results of detection of outliers are acquired. The experimental results show that the proposed algorithm improves the accuracy of detecting outliers and the effectiveness of network intrusion detection.

Tianyi Ding, Min Zhang, Dongjie He

Accurate Approaches to Extracting Bragg Peaks Based on High-Frequency Ground-Wave Radar Under Complex Background

The noise and targets or the spectral splitting often make the conventional method of extracting Bragg peaks from high-frequency radar Doppler spectra inaccurate. Since the echo R-D spectra have a typical image feature and the energy of Bragg peaks are relatively high, the multi-threshold segmentation is used to eliminate the targets. Then, the least-squares method and the energy-centroid method of extracting Bragg peaks are presented. By analysis of numerous measured data, it proves that compared with the conventional method, the methods presented in this paper have a higher precision and a stronger applicability. Moreover, the least-squares method is the best. Finally, compare the wind direction inversion results of measured data with the forecast information which provided by the National Marine Environment Forecast Center, meanwhile the cause of error is analyzed.

Yingning Dong, Yanjing Zhang, Helei Zhang, Weibo Deng

Reconfigurable Radar Transmitter Based on Nonuniform Channelization

Radar reconnaissance system requires the transmitter can simultaneously transmit many signals whose bandwidth, center frequency and other parameters can be configured in real time. The system requires the transmitter has the ability to transmit wide-band signals. Aiming at the actual demand, this paper proposes a reconfigurable nonuniform channelized radar transmitter system based on software radio technology. The system uses DDS as the signal generation source and achieve the simultaneous transmission of Multiple signals through the digital channelization technology, we deduce the poly-phase filtering channelized radar transmitter model. To deal with the cross-channel problem when generating wide-band signals, the paper proposes a nonuniform channelized technique to achieve the reconstruction of the signals to be transmitted. Finally, the corresponding MATLAB simulations are carried out to verify the correctness and feasibility of the transmitter system.

Wen-xu Zhang, Bing-hua Yuan, Zheng Dou

Three Dimensional SAR Imaging Algorithms via a UWB Radar Sensor

Combining SAR imaging technique with a UWB radar sensor can realize high resolution imaging of targets. It has important research value in environment investigation and inter surveillance. In this paper, three dimensional SAR imaging is investigated based on the one dimensional echo signal of UWB at different locations and time. The UWB SAR image reconstruction is realized by Hamming window function optimization, image registration and interpolation. The reconstruction imaging of the metal ball with centimeter resolution is realized, which verifies the feasibility of the imaging system in this research for 3D SAR imaging.

Zhenzhen Duan, Yuan Zhao, Huaiyuan Liu, Jian Zhang, Yang Zhang, Jing Liang

Soil Moisture Retrieval Using UWB Echoes via ANFIS and ANN

This paper introduces a new soil moisture (SM) retrieval approach based on ultra-wideband (UWB) echoes. The approach employs two fuzzy logic systems (FLSs) -adaptive network-based fuzzy inference system (ANFIS) and type 1 fuzzy logic system (T1FLS) respectively, to extract features in soil echoes. Artificial neural network (ANN) is applied to classify with different volume water contents (VWCs). 9 types of UWB soil echoes of different texture and VWC are collected and investigated using our approach. Final analysis shows ANFIS with ANN provides a better VWC correct recognition rate (CRR) than T1FLS with ANN at high SNRs.

Xiaoxu Liu, Xiaofeng Yu, Jie Ren, Jing Liang

Height and Relative Velocity of Pedestrians Estimation Based on Radar Micro-Doppler Signatures

Radar micro-Doppler of human motion can provide signatures for target recognition. It is very difficult to extract motion parameters from radar echo of walking human because of its complexity. This paper presents a method for estimating the relative velocity and height of human walking. The relative velocity is defined as the average walking velocity normalized by the height of the human. In this method, the m-D spectrum of real data is extracted from linear frequency modulation signal first. Then we simulate the radar echo of different parameters and extract the m-D spectrums simulated. A priori knowledge is obtained by performing pulse compression on the signal to improve the accuracy of the simulation. At last, the correlation is compared to find the parameters corresponding to the m-D spectrum of real data, where the frequency component of foot is considered to be the main component and is separated and used to compare the correlation. Simulation results show that this method can accurately estimate the height and relative velocity parameters of pedestrians and is not sensitive to noise.

Wen Cui, Chongyi Fan, Xiaotao Huang, Zhimin Zhou

Rainfall Attenuation Characteristic Analysis in Ka-band Satellite Communication System

Using Ka-band (30/20 GHz) to form a satellite communication system is the development trend of satellite communications in the future, and it is significant for the future development of China’s satellite communications to research and develop the Ka-band satellite communication system. But the rainfall attenuation is one of the important factors affecting the transmission quality in Ka-band satellite communication system. This paper analyzes the effects of altitude, radio frequency and satellite position on rainfall attenuation based on the rainfall rate of major cities in China, according to the rainfall attenuation prediction model given by ITU-R. The results can be used to design the Ka-band satellite communication system to reduce the influence of rainfall attenuation.

Ming Liu, Zhi-gang Li, Zheng Dou

FPGA High-Speed Data Transmission Based on Bit Self-revised Technique

With the application of real-time high-speed signal processing in UWB (ultra-wide band) radar receiver as background, a dynamic self-revised scheme is put forward. The scheme is based on FPGA (Field-Programmable Gate Array), which can improve high-speed data transmission quality. It can guarantee that every bit can be sampled at the best time to conquer the logic error and bit error which are brought by static hazard in high data-rate condition. The scheme can realize 400 Mbps high-speed data transmission using a single SelectIO and the test results prove the feasibility and stability of the design.

Bo Wang, Zhongjin Zhang, Lang Zhou, Mei Xiang

High Gain UWB Antenna with Miniaturized-Element Frequency Selective Surfaces

UWB (Ultra-wideband) communication system is a short distance communication mode with low power and high speed. In order to improve the performance of UWB Antenna and increase the number of the FSS units in the Finite plane space, an UWB MEFSS unit structure is proposed. The size of the proposed unit is compact, which is 2 mm × 2 mm. And it has the characteristic of band-stop filtering in the UWB frequency scope. The proposed structure has stable filtering property for the electromagnetic wave which had different incident angle. Two-dimensional array consists of 11 × 11 MEFSS units which proposed in the paper. The two-dimensional array was placed under the elliptical monopole UWB Antenna as the reflection plane of the antenna. The analysis of frequency domain performance of the antenna shows that the antenna with MEFSS structure all had good impedance matching in the UWB frequency scope compares to the elliptical monopole UWB antenna, and the gain is increased 7.08 dB at most, which show that the proposed MEFSS structure can increase the gain of elliptical monopole UWB antenna effectively, and improve the radiation performance of antenna.

Qichao Song, Xiaoming Zhu, Yanping Li

The Evaluation and Simulation of Radar Separation Based on Reference System Comparison Method

In recent years, with the rapid increase in air traffic flow, flight conflict is becoming increasingly. It is very necessary on air safety risk quantitative analysis research. Especially in China, radar control is being gradually implemented, in order to ensure air traffic safety, the study of quantitative analysis and evaluation of radar control on security risks has become great significance and practical value. This paper studies the safety assessment method of aircraft radar separation in the case of air traffic flow increasing. Based on the close approach probability (CAP) model and the reference system comparison method, consider the various factors that affect flight safety, the radar separation evaluation model is established. Using statistical knowledge and measured data, the method of this study is verified by compare, the result is displayed in the premise of ensuring flight safety, radar type is related with radar safety separation. Reduced radar separation can greatly improve air traffic flow, ease flight delays, enhance control efficiency.

Bo Wang, Yong Zhang, Lang Zhou, Mei Xiang

Evaluation the Impact of Maglev Railway on Primary Surveillance Radar

Primary Surveillance Radar (PSR) is of significant importance to civil air traffic in term of providing important surveillance information. The surrounding terrain and facilities are the main factors that affect the PSR’s performance. To ensure aircraft flight safety, it is necessary to evaluate the influence of terrain and facilities around the radar site. Take airport in the eastern China region as an example, which is planning the construction of maglev railway in near area, this research analyses and evaluates of the railway influence on primary surveillance radar. The results indicate: peak noise magnetic field in created when maglev train tracts and brakes; the peak and the average field strength will not affect the normal operation of the ATC primary radar; when maglev railway train is passing by, the operation of the PSR is able to maintain its normal performance.

Yong Zhang, Jiming Zhang, Xiaowen Cao

Data Association of AIS and Radar Based on Multi-factor Fuzzy Judgment and Gray Correlation Grade

This paper proposes a data association algorithm based on multi-factor fuzzy judgment and gray correlation analysis, in order to improve the correct correlation between AIS and radar targets. The target track is formatted into a sequence of four factors in this algorithm, such as distance, bearing, speed and course. We compute preliminary the algorithm of multi-factor fuzzy judgment based on four factors. And if the target satisfies the preliminary associated conditions with four factors, we continue to do the gray correlation analysis. Compared to the multi-factor fuzzy judgment, the simulation results of this paper show that the algorithm can reduce the probability of false association effectively. And compared to the gray correlation analysis, the algorithm can reduce the calculation range effectively.

Chang Liu, Tongtong Xu, Tingting Yao, Zhian Deng, Jiacheng Liu

Fusion Technology of Multi-radar Target Based on VTS

In this paper, an adaptive track fusion algorithm is proposed based on the fusion algorithm combining the optimal weighting and recursive least squares method. Simulation results show that the method can effectively improve the accuracy of target detection in longitude, latitude, speed and heading. The ship tracks are more accurate after multi-source information fusion.

Huabin Liu, Zhiqi Wu

Digital Signal Processing, Digital Image and Video Processing


An Algorithm to Recognize Digital Modulated Signals Based on High Order Cumulants

The recognition of digital modulated signals is a main process of the signal processing. The performance of the recognition algorithm always decides the latter signal processing, even the whole system’s success or failure. Many note algorithms have been presented to achieve a better recognition performance, while these methods cannot handle the effect of noise well. The paper proposes an algorithm based on high-order cumulants to recognize the modulation type of signals, which can not only overcome the interference brought by noise, but also can recognize multiple modulation signals. Experiments have been made to justify the performance and reliability of the proposed method.

Bingren Ji, Yong Wang, Yang Gao

Parameter Optimization for the Detector Based on Fractional Lower Order Moments in Alpha-Stable Distributed Noise

In impulsive noise modeled by the symmetric alpha stable ($$S\alpha S$$) distribution, the detector based on fractional lower order moments (FLOM) is a good choice for signal detection due to its simplicity and satisfied performance. The moment order is a priori parameter of the FLOM detector. However, there is no quantitative result to help us to choose a good moment order in the literature. In order to calculate the optimal value of the moment order for the FLOM detector, we first derive a novel asymptotic expression for the detection probability and then calculate the optimal value of the moment order by the Genetic algorithm. The effect of different parameters on the optimal moment order is discussed and some useful conclusions are drawn. Simulation results prove that the optimized moment order makes the FLOM detector achieve the best performance in different $$S\alpha S$$ noise.

Jinjun Luo, Shilian Wang, Eryang Zhang

Uncertainty Principle of the Special Affine Fourier Transform for Discrete Signals

The special affine Fourier transform (SAFT) encompasses series of famous transforms, and it has been proved as an effective way to solve problems of signal processing and optics. The product of the spreads of a signal in time and SAFT domains is limited, and the lower bound is given by the uncertainty principle of the SAFT. Unfortunately, this uncertainty principle is only established on the analog signal instead of discrete signals, which are more common in practice. This paper aims to introduce a novel uncertainty principle of the SAFT for discrete signals. First, the definitions of time and SAFT-band durations in discrete signals are given. Then, a minimum of the product of time and SAFT-frequency spreads is determined. Some related properties are also discussed.

Mo Han, Jun Shi, Xuejun Sha, Min Jia, Qingzhong Li, Naitong Zhang

Modified PSO Optimizer for Arrays Pattern Optimization by Efficient Estimations of the Optimum Particle Initial Values

When particle swarm optimization (PSO) is used to optimize antenna array pattern, all particles are always initialized randomly, but here a new initialization method are presented to improve PSO optimizer convergence. On the basis of desired pattern the corresponding aperture weights are solved by analytical techniques which can to a great extent ensure that these weights are efficient estimations of the current optimum particle initial values. Then they are assigned to a particle as initial values, but all other particles of the swarm are still initialized randomly. Except this new initialization step nothing is changed in the standard PSO optimizer. The simulation results prove that this new optimizer converges faster and deeper than the standard PSO especially in more complicated optimization problems. So the presented new PSO optimizer is more effective and can achieve better optimized solutions which can meet the specifications well.

Shuchun Zhang, Yongbin Chou, Xin Wei, Zongquan Deng

The Optimization of Generalized S-Transform Based on Aggregation Measure

Time-frequency analysis theory is frequently-used in signal processing field. The S transform (ST) and its generalized form are the improved forms of wavelet transform (WT) and the short time Fourier transform (STFT). In generalized S transform (GST) algorithm, the key problem is the choice of the window function and the optimization of the parameters. This paper proposed a method to solve this problem. Linear FM signal and nonlinear FM signal are used to verify the effectiveness of this method.

Yuning Zhao, Xiaodong Yang, Yun Lin

Time-Frequency Ridge-Based Parameter Estimation for Sinusoidal Frequency Modulation Signals

In this paper, the time-frequency (TF) ridge technique is employed to obtain the accurate parameters estimation of the sinusoidal frequency modulation (SFM) signals. By extracting the TF ridge, a high energy-concentrated time-frequency representation (TFR) of the given signal can be obtained. And then a TF ridge-based method for estimating parameters of the SFM signal is proposed. The advantages of this method over the S-method-based method are (1) it can be easily implemented, (2) it costs less computation and storage space, and (3) it has a high precision. Numerical results provided in this paper show the superiority of the novel method.

Zhaofa Wang, Yong Wang, Liang Xu

Linear Canonical Transforms’ Discretization Formula Based on the Frequency-Domain Convolution Theory

The Linear Canonical Transforms’ (LCT) domain not only contains the informations of time and frequency, but also includes the informations of varying frequency with time. Because of these characteristics which makes it have a unique advantage in dealing with nonstationary signals, it attracts more and more scientists and the engineers’ attention. Fourier Transform (FT), Fractional Fourier Transform (FrFT), Fresnel Transform and Scale Transforms can be seen as a special LCT’s form. And in the combination of time-frequency analysis method (Wigner distribution, short-time Fourier transform (STFT), Fuzzy function) [2] on the basis of Linear Canonical Transforms will have more development space. However, the discretization analysis of Linear Canonical Transforms is not clear enough, especially the discretization formula is not suitable for computer’s calculation. Therefore, based on the sampling theorem of bandpass signal, the discretization formula is deduced based on the frequency-domain discretization formula and the convolution formula, and the correctness and reversibility are verified on the computer’s calculation.

Qiwei Liu, Yanheng Ma

The Analysis and Optimization of Anti-jamming Performance Testability for Electronic Equipment

In this paper, the problem about analysis and optimization of anti-jamming performance testability for electronic equipment is studied, which is focused on the online evaluation of anti-jamming performance for electronic equipment. Firstly, the problem of electronic equipment anti-jamming performance testability is described. Secondly, the method of testability analysis is studied in this paper, and some typical cases were showed. Finally, a preliminary study on the problem of testability optimization is made.

Bao-hua Wei, Ming-ze Gou, Bao-chen Li, Hui-xia Jiang

A Novel Algorithm of Radial Velocity Estimation for MC-HRWS System

In multiple channels in azimuth high resolution and wide swath (MC-HRWS) SAR system, the azimuth signal reconstruction of moving target based on the space-time equivalent sampling principle exists a periodical phase error on account to the radial motion of moving target. For compensating the above phase error, this proposed algorithm combines the undersampling discrete-time fractional Fourier transform (DFRFT) with the Doppler centroid ambiguity estimation to obtain the radial velocity. Before the above process, this paper applies the displace phase center antenna (DPCA) to suppress the clutter for detecting the moving target. After the process of compensating the phase error, the reconstructed azimuth signal is focused unambiguously by the traditional azimuth focusing approach. By the experiments and performance analysis, the validity of the proposed algorithm is demonstrated.

Yun Zhang, Yiran Guo, Zhenyuan Ji, Huilin Mu, Lupeng Guo

Design of Multi-channel Array Signal Acquisition System

In phased array radar system, the quality of received array signal determines the accuracy of target detection. Traditional signal-acquisition board has few channels and complex system. In view of these problems, this paper designs an 80-channel array signal acquisition system. The whole system consists of ten boards, and each one has 8 channels. The sampling rate is up to 125 MHz. This novel introduces the principle of system and design of hardware circuit. After the test of the overall system, the board implements its function and has excellent performance.

Ning Zhang, Nanxi Jia, Xinchao Zhang

A Real-Time Obstacle Detection Algorithm for the Visually Impaired Using Binocular Camera

In this paper, a real-time depth-data based obstacle detection to assist the visually impaired people in avoiding obstacles independently is presented. Depth data obtained by the binocular camera, is analyzed to detect obstacles. With the help of the proposed method, the distance between the binocular camera and the obstacle can be calculated with the speed of 30fps. Our method further allows the computation of the position and the size of the obstacle. The proposed algorithm has been extensively tested on both real images and public Laundry data-set. Experimental results demonstrate that the proposed method is not only able to detect the obstacles correctly but it is also fast, efficient and stable.

Rumin Zhang, Wenyi Wang, Liaoyuan Zeng, Jianwen Chen

A Robust and Real-Time Full 3D Reconstruction Method Based on Multiple Kinect

Although 3D reconstruction of objects has been extensively studied, the robust and fast approach still remains challenging. In this paper, we present a VR (Virtual Reality) based social system that can produce realistic full 3D reconstruction of moving objects in real-time. In this system, we propose a novel method that can refine the point clouds from multiple Kinect streams and therefore generate accurate 3D reconstruction. Specifically, the original point clouds are first filtered to remove the edge noise by using optimal triangulation algorithm. Afterwards, the refined point clouds are registered by optimal registration method. In order to elevate the visual quality of the reconstruction result, RANSAC linear regression is used to adjust the color difference between the corresponding points in adjacent point clouds. The experimental results verify the effectiveness of our 3D reconstruction method in visual quality and time efficiency.

Xiongfeng Peng, Liaoyuan Zeng, Wenyi Wang, Zhili Liu, Yifeng Yang, Zhen Zeng, Jianwen Chen

A Two-Handed Gesture Recognition Technique on Mobile Devices Based on Improved DTW Algorithm

The majority of traditional gesture recognition relies on cameras, easily affected by environmental noises. Moreover, most of them are one-handed gestures, whose identifying speed and accuracy are limited. Therefore, this paper proposed a two-handed gesture recognition technology based on improved dynamic time warping (DTW) algorithm and common mobile devices. The data are collected by common carry on mobile communication devices instead of wearable devices. By constructing boundary linked list, traditional DTW algorithm is optimized, so we realized two-handed gesture trajectory recognition. The results show that, under the prerequisite of guaranteeing accuracy, the method can considerably reduce the algorithm’s computation complexity, and effectively improve the speed of recognition.

Xiao Han, Jiayin Xue, Qinyu Zhang, Qiao Xiao, Peng Zhao

Research on Performance Evaluation Method for Interferometric Phase Filtering

Interferometric phase filtering (IPF) is an important process of Interferometric Synthetic Aperture Radar (InSAR). The objective of IPF is to reduce the phase noise while preserving the details of the signal phase information, which affects the final quality of Digital Elevation Model (DEM) products directly. It is significant to evaluate the interferometric phase filtering algorithm. The filtering algorithm evaluation could be divided into subjective evaluation and objective evaluation. They all have advantages and limitations. However the present filtering evaluation methods are rarely able to keep the noise suppression performance and the detail preserving performance being truly quantitative and distinguished. Therefore the paper defines two new indexes: Noise Suppression Performance (NSP) and Detail Loss Performance (DLP), and realizes quantification of these indexes. Then the performance of these quantitative indexes and the filtered results of different phase filtering methods are shown and compared at the end of the paper through experiments carried on real datas.

Bowen Yang, Yang Wang, Haifeng Huang, Zhen Dong

A Method for Reducing the Complexity of Meggitt Decoder

The decoding principle of linear block code is based on the syndrome which determines the error location of the received codeword. When considering the Hamming code, there will be eight syndromes with eight decoding circuits when there is one bit error. Cyclic code is a special case of linear block codes which is still a cyclic code after cyclic shift. Therefore, it is possible to get another error pattern of the cyclic code after the cyclic shift of one error pattern. Meggitt decoder can take advantage of the cyclic shift characteristic to divide any error pattern and all the corresponding cyclic shift error patterns into one category. And the same type of error patterns can use the same decoding circuit which can simplify the complexity of the decoder. If the (n, k) cyclic code is to correct t bits error, it is easy to derivation the total number of the error patterns. But there exists error patterns that can be classified as one type. The total number of error pattern types will be discussed in this paper. And the computation complexity of error pattern types of Meggitt decoder will be reduced when using the method proposed in this paper.

Jiayan Zhang, Shuai Wang, Hao Lu, Hongchao An

Summarization of Credibility Evaluation of Missile Simulation Data

The missile weapon system often needs a lot of simulation test during the R&D test. Because people have doubts about using the simulation model instead of the physical credibility, it is often necessary to evaluate the reliability of the simulation results. Missile simulation results of the credibility of the assessment is a very important part of an effective assessment of data credibility can shorten the missile weapon system development cycle, cost savings. This paper summarizes the main theoretical methods and research and development direction of the reliability evaluation of missile simulation data at home and abroad. This paper analyzes the gap between China’s missile simulation data evaluation and foreign countries, and puts forward some suggestions on the future research and development of missile simulation data point of view.

T. Koch, Jinlong Ma, Liyuan Ma, Dan Fang

Research on Simulation Identification Technology of Loitering Missile

Aiming at the contradiction between the test cost and the confidence of the result, when identify loitering missile by the traditional method, propose the simulation identification technology of loitering missile. This paper briefly introduces the process and advantages of the simulation test identification technology of loitering missile, summarizes the key technologies of the technology and researches its current situation and development.

Xu Zheng, Suochang Yang, Dan Fang

Improved Single Pixel Camera via Fiber Collecting Strategy

Single-pixel camera can obtain images in a wide range of challenging scenarios, including MRI, remote sensing and aerospace exploration with fewer data and lower power. In this work, we demonstrate an imaging system with almost perfect signal collection, noise suppression and capable of reconstructing images with high signal-to-noise (SNR) using novel collecting strategy. We use fiber to replace the conventional lens to collect the linear projection of object scene. Furthermore, we introduce the specifics of our system. Meanwhile, we analyze the systemic factors such as active area of detector, reflectivity of object and system noise. Lastly, we perform high-speed mask and sensing the modulated light with single-pixel detector and reconstruct the scene for image resolutions of $$32\times 32$$ pixels. We compare the new strategy with conventional method and the results show that the new strategy have better visual quality and the fidelity. Moreover, since this approach does not use sensor array, it can be readily extended to other wavelengths, where the large array sensors are expensive and unable to operate properly.

Tiantian Zhang, Bo Wu, Chenghui Liu, Shaohua Wu, Junjun Xiao

Study and Improvement of the Resource Allocation Algorithm in TWDM-PON Based on the Correlation of Switching Periods

This paper focuses on the wavelength distribution in TWDM-PON. A novel fixed-dynamic wavelength distribution (FDWD) mechanism and a coupling algorithm are presented by using the periodic law of users’ traffic. Combining the historical statistics, the Poisson model and the autoregressive (AR) model are used to predict the bandwidth that the user may request. Based on the forecast data, users are distributed into different communities to transmit on different wavelengths, according to the constraints which include the load balance and minimizing tuning overhead. Compared with the existing work, the P-order AR model are presented to model the request traffic. The coupled packet algorithm is optimized by adding the correlation constraints of adjacent switching periods and the wavelength tuning distance is taken into account. The simulation results show that the FDWD can further reduce the tuning cost and improve the load balancing performance.

Xiaoning Liu, Jianjun Hao, Yijun Guo, Huanhuan Luo, Guiping Zhou, Xiangyu Kong

The Noise Characteristic Analysis of the Periodically Non-uniform Sampling

The noise is one of the main factors affecting the receiver sensitivity. And the periodically non-uniform sampling model is an effective way to break through the limitation of the Shannon’s sampling theorem. In this paper, we make an analysis about the linearity of the periodically non-uniform sampling system and its noise characteristics. Besides, we acquire the time-varying Gaussian probability density function of the output noise. And then the output noise after sampling is proved to be the colored noise, which is cycle-stationary and can be whitened through the method proposed in the paper. Finally, the simulation results are given to verify the correctness of the analysis.

Shuai Wu, Kaili Jiang, Jun Zhu

Investigation of CO-OFDM-6PolSK-QPSK Modulation

We analyzed the performance of CO-OFDM-6PolSK-QPSK modulation format and compared it with CO-OFDM-PM-QPSK. The results show that it can be used as an alternative way to PM-QPSK in a flexible-rate coherent optical communication system.

Yupeng Li

Features of Singular Value Decomposition and Its Application to the Vibration Monitoring of Turboprop Engine

The singular value decomposition (SVD) can decompose an original signal into a series of component signals linearly. By means of analyzing deeply the fundamental principle and existing problems of Hankel matrix-based SVD, This paper reveals the three basic features of SVD, including linear decomposition, reconstruction component frequency domain disorder and band-pass filtering. Based on those features a new SVD method is put forward. Numerical simulation results show that the proposed method not only solve the frequency domain disorder problem of traditional SVD, and can achieve a given linear band-pass filter bandwidth, complete recovery of original signal amplitude, frequency and phase characteristics in any given frequency nearby. Other signal processing methods have no such advantages. The proposed method has been successfully applied to the vibration signal extraction of a certain type of turbofan engine, and the results show that the method has excellent in the feature extraction.

Cheng Li, Chen Lishun, Liang Tao, Guo Li, Cheng Ming, Zeng Lin

Spatial Spectrum Analysis of Proposed Two-Dimensional Nested Cylindrical Array

In this paper, a new two-dimensional nested cylindrical array is proposed. According to the characteristic of cylindrical array, the two-dimensional rectangular nested array is extended to build the 2D sparse cylindrical array. Comparing with the one-dimensional sparse cylindrical arrays, this new structure could save more elements than the 1D sparse cylindrical array. Moreover, simulation results show that through augmented matrix MUSIC approach, 2D sparse cylindrical array could also detect all targets in the range, even if the number of targets is larger than the number of real elements in the array. However, both the uniform cylindrical array and the 1D sparse cylindrical arrays couldn’t find all the sources.

Na Wu, Qilian Liang

Parameters Identification via Cepstrum Analysis for Mix Blurred Image

Relative motion between the camera and objects leads to image blur and degrades video sequences. In order to achieve image restoration of the video intra-frames, the mixed blur that combines two common blur types, motion blur and defocus blur, is discussed in moving imaging. First, blur types are determined according to differences in spectrum features. Then, parameters of the point spread function (PSF) are identified quantitatively using the method of cepstrum analysis. Finally, experimental results show that the proposed cepstrum analysis for estimating the PSF can reach high accuracy.

Mingzhu Shi, Xianwei Gong

A Multi-target Velocity Measurement Method Based on Integrated Waveform LFM-MSK

Radar and communication integrated systems have a promising perspective in the future. LFM-MSK, as one of the integrated waveform, has the same range resolution as the LFM waveform and same bit error rate as the MSK waveform. However, its phase continuous characteristic also brings about difficulties in velocity measurement for which an effective solution hasn’t been proposed yet. In this paper, the waveform formula for multi-target velocity measurement was deduced using coherent integration method. The uncertain phase in the formula which influences the velocity measurement is analysed and a method using self-multiplication is proposed to eliminate the phase and measure the target’s information through two spikes. The influence of the cross term between the targets is concluded into three cases. The detective probability of LFM-MSK is lower than LFM waveform because of energy split and a Monte Carlo experiment result under different signal to noise ratio is given. The simulation results show that the method can measure the velocities of multi-targets with favourable accuracy.

Yicheng Jiang, Chen Du

Fast and High-Precision DOA Estimation by Iterative Interpolation on Spatial Fourier Coefficients

Among direction-of-arrival (DOA) estimation algorithms with narrow-band sensor arrays, eigen-based decomposition algorithms are hard to meet the demand of real-time signal processing because of the huge computation. To solve the problem of computational load, we propose and analyze a fast and high-precision DOA estimation algorithm based on spatial Fourier coefficient iterative interpolation. This method is shown to achieve identical asymptotic performance by constructing and interpolating the modified value at the adjacent bins of the maximum in spatial spectrum. An optimization method to reduce the iteration times is also given. The simulation results show that the proposed algorithm may achieve the same estimation precision as MUSIC in certain condition without the huge computation.

Yifei Liu, Jun Zhu, Kaili Jiang, Bin Tang

A Fast Nyquist Zone Index Estimation Algorithm for Pulse Radar Signal Based on Non-cooperative Nyquist Folding Receiver

Nyquist folding receiver (NYFR) is a novel wideband receiving structure. The NYFR uses the non-uniform sampling to fold the monitoring bandwidth and the input carrier frequency is transformed into an added modulation parameter. The added modulation parameter is called as the Nyquist zone (NZ) index. Under the non-cooperative receiving condition, the NYFR outputs will become hybrid modulated signals because of the unknown NZ index. To simplify the signal processing of the NYFR, a feasible way is to estimate the NZ index directly without the prior information of the signal modulation types and demodulate the hybrid modulated signal using the estimated NZ index. In this paper, a fast estimation algorithm is proposed to get the NZ index directly. The basic pulse radar signals are considered and they are constant frequency signal, binary phase coded signal and linear frequency modulation signal. Compared with the existing algorithm, the simulation results demonstrate the merits of the proposed approach.

Zhaoyang Qiu, Jun Zhu, Bin Tang

Image Fusion in WMSNs Based on Tetrolet Transform and Compressed Sensing

Wireless Multimedia Sensor Network is a new Sensor Network based on the traditional Wireless Sensor Network with the introduction of Multimedia information sensing function. The paper aims to solve the problems of the energy constraint in the Wireless Multimedia Sensor Network and the data of information encoded in the image has the characteristic of big size and high redundancy. The research can be conducted in the following two aspects. The first is to find a fast and accurate image registration algorithm which can be used to reduce the total amount of the extracted feature point and improve the matching precision. The second is to provide an image fusion approach which can be applied in the Wireless Multimedia Sensor Network. With this approach, the detailed features of the image can be highlighted, and the image clarity can be improved. The research in this paper can lay the theoretical foundation for research of image fusion in Wireless Multimedia Sensor Networks, and promote the development of wireless multimedia sensor network as an emerging cross-disciplinary science. The research are of important economic significance and social value in the informatization and networking of the fields of military, transportation, agriculture and etc.

Zhou Xin

A Novel Instantaneous Imaging of Ship Based on the Hybrid System of SAR and ISAR

It is difficult to image the moving ship imaging in the system of airborne SAR, that the echo includes multi Doppler component, caused by the three-dimension rotation, the motion of ship and the motion of airborne radar. In this paper, a method of the dual Range-Doppler (RD) model combining the hybrid imaging model of SAR and ISAR is proposed, which considers the airborne radar movement and the ship’s movement. Because of the complex motion of the target ships, the time-frequency analysis methods are studied to obtain the instantaneous images of the targets. The simulation of ship scatter model proves the feasibility and superiority of this way. The validity of the proposed algorithm is demonstrated by experiments.

Zhenyuan Ji, Xuechao Kan, Yun Zhang, Ziheng Wang, Hongyan Jin

Parameter Estimation and Imaging for Moving Targets in Airborne SAR with Single Antenna

This paper proposes a novel algorithm for moving target parameter estimation and imaging, which is especially applicable for single-antenna airborne synthetic aperture radar (SAR). Firstly, fractional Fourier transform (FrFT) is utilized to estimate Doppler parameters. We also simultaneously make the SAR range migration correction according to the estimated parameters. Next, an adaptive maximum amplitude extraction algorithm is proposed to separate a single target from multiple targets. After the completion of data extraction, we adopt the cross-correlation accumulation method and the Doppler centroid tracking method to realize motion compensation. Finally, the focused imaging results of several moving targets can be obtained. The proposed algorithm can estimate Doppler parameters accurately and image moving targets successfully. Its strong feasibility and high effectiveness are validated by SAR real data processing.

Yicheng Jiang, Hanyun Wang

Study on Image Processing Method of Egg Vessel Extraction

The image processing within the egg detection system mainly involves image segmentation, edge detection, and image demising. In this study, according to the characteristics of the egg vessel, the image is treated with adaptive histogram equalization and then anisotropic diffusion smoothing is performed. After the multi-adaptive Gaussian difference processing enhancement, the global threshold is selected to divide the image under the graph, and the target egg images are separated. The results show that the experimental technique can accurately extract the blood vessel image information and provide the technical basis for the egg detection system.

Ming-Shuai Bi, Jia-Song Mu

The Method of Compressed Sensing for TWTA Linearization

To reckon with the high feedback sampling rate of a digital predistortion linearizer for TWTA (Travelling Wave Tube Amplifier), a novel method with compressed sensing is presented in this paper. The Simulation results show that good linearity improvement can be attained for an X-band TWTA with low feedback sampling rate.

Xin Hu, Yinghui Zhang, Shuaijun Liu, Weidong Wang

Impact of Nonlinear Transformation on Signal Detection: A Minimum Error Probability Perspective

This paper investigates the impact of nonlinear transformation on signal detection from a minimum error probability perspective. Firstly, we derive the probability density distributions of three transformed received signal over binary input additive white Gaussian noise (BIAWGN) channel, including square transformation, abs (absolute value) transformation and changing the sampling times. Then, we derive the three optimal decision thresholds respectively for the three transformations under the criteria of minimum error probability. Furthermore, we make simulations to compare the minimum error probability of the three transformed ones with the original signal, trying to find the nonlinear transformation with smaller minimum error probability.

Feng Shen, Lizhen Chen, Guoru Ding, Qihui Wu

DOA Estimation of Coherent Wideband LFM Signals Based on Sparse Representation of FRFT Domain

In this paper, a DOA estimation method for wideband signals based on sparse representation in FRFT domain is proposed. This method establishes the DOA estimation model and the array popular matrix in the FRFT domain and reconstruct the spatial spectral function based on the sparse representation of the spatial angle, so as to realize DOA estimation of the wideband LFM signals. The algorithm is not only suitable for non-coherent signals, but also can process coherent signals directly without any decoherent operations. Simulation results show that the proposed method can achieve higher estimation performance than the traditional methods, especially at low SNR.

Xiuhong Wang, Xingpeng Mao, Yaliang Wang, Aijun Liu

A Primitive Research on Precipitation Observation Parameters with 35 GHZ Cloud Radar

Weather radar is a traditional remote sensing tool for precipitation observation and analysis. Compared with millimeter wave radar, it is less affected by attenuation, but at the same time, it has lower spatial and temporal resolution normally. Cloud radar has shorter wavelength and can detect basic information of cloud, such as cloud height, thickness and other parameters. It provides a fantastic technique to study fine structure for clouds. But due to the attenuation effect it is rarely used to analyze precipitation. In this paper, A cloud radar and a C-band weather radar nearby are used to analyze two precipitation processes. The Z-I relationship can be obtained by combining ground automatic precipitation observation at the same site of the cloud radar. By a primitive research in this paper, the characteristics of stratiform precipitation was obtained by analyzing the reflectivity vertical profiles, layer mean reflectivity and standard deviation from cloud radar and C-band radar, and it shows that some useful information can be retrieved using cloud radar observation even under precipitation conditions. So with the higher spatial and temporal resolution, more research work will be focused on the fine vertical structure characteristics retrieval from cloud radar observation in the future.

Chen Lai, Debin Su, Yang Qi

Adaptive Ensemble Clustering for Image Segmentation in Remote Sensing

Image segmentation is a fundamental computer vision task. Although many approaches have been proposed, obtaining accurate results in some special applications are still not easy. In this paper, we propose a novel image segmentation method for remote sensing based on adaptive cluster ensemble learning. The clustering parameter of each image is calculated with affinity propagation automatically. Then, multiple clusterers are trained separately and the predictions of them are combined under the ensemble learning framework. In this way, the robustness of each clusterer could be enhanced. Experimental results demonstrate the effectiveness of our proposed method.

Tingting Yao, Chang Liu, Zhian Deng, Xiaoming Liu, Jiacheng Liu

Quaternion-Valued Feedforward Neural Network Based Time Series Forecast

Currently, the quaternion-valued feedforward neural network (QFNN) has been proposed for image compression and has a more superior performance than the real-valued feedforward neural network (FNN). However, the used quaternion activation function is a split quaternion function, thus it may not preserve the cross-information within the components of the data and for time series forecast, the established model is a strictly linear model which may not be appropriate for noncircular quaternion-valued signal processing.In this paper, a fully quaternion activation function is employed to design the QFNN and an augmented QFNN (AQFNN) is proposed. They are derived by using recent studies in the augmented quaternion statistics and the HR-calculus. With the augmented quaternion statistics, the AQFNN can process quaternion-valued noncircular signals, effectively. Simulations on both benchmark circular and noncircular quaternion-valued signals, and real-world quaternion-valued signals support the analysis.

Xiaodong Li, Changjun Yu, Fulin Su, Aijun Liu, Xuguang Yang

Digital Watermarking Based on Wavelet Transform and Cultural Invasive Weed Algorithm

The robustness and the imperceptibility are important properties in a digital watermarking system. Since they conflict with each other, a traditional watermarking system is difficult to satisfy them at the same time. In order to solve the above-mentioned problem, a novel digital watermarking method based on cultural invasive weed algorithm (CIWA) is designed to resolve the difficulties of the robustness and imperceptibility at the same time. The proposed CIWA combines the advantages of cultural algorithm (CA) and invasive weed optimization algorithm (IWO), so the proposed CIWA has the capability to search for the global optimal solution. The robustness and the imperceptibility of the watermarking system were optimized comprehensively by CIWA searching optimal parameters of embedding strength and embedding threshold. Simulation results have proved that the proposed method is superior to other methods based on intelligent algorithms.

H. Y. Gao, P. F. Chi, Y. N. Du, Y. Wang, M. Diao

Automatic Image Segmentation Using PCNN and Quantum Geese Swarm Optimization

Image segmentation is a very important aspect in the fields of computer vision and pattern recognition. Although Pulse-coupled Neural Network (PCNN) is an effective method for image segmentation, the optimal parameters of PCNN are difficult to be decided. In order to effectively find the optimal parameters of the PCNN, Quantum Geese Swarm Optimization (QGSO) is proposed to evolve parameters of PCNN. The proposed QGSO applies quantum computing theory to Geese Swarm Optimization (GSO) for continuous optimization problems. Minimal combined weighting entropy which considers of Shannon-entropy and Cross-entropy is used as the fitness function of QGSO. Experiment results show that the proposed method can obtain better segmented image and has an excellent performance.

H. Y. Gao, X. Su, Y. S. Liang

Circuit Processing System, System Design, Coding, Encryption and Algorithm Design


Study on the Game Relationship Between Online-Taxi and Traditional Taxi Under the Taxi-Hailing Apps

For the aim of studying the competition and conflict between the online-taxi and the traditional taxi under the condition of Taxi-hailing apps participation, as well as exploring the coexistence and win-win relationship between these two modes of transport. In consideration of the establishment of the game model based on the cost parameters and the Bertrand model on account of the price competition, this paper analyzes the game relationship between the online-taxi and the traditional taxi in the aspects of the cost and the charge price. The experimental results show that different strategies schemes need to be developed for different costs and charge prices, in the condition of cooperation between the two sides can effectively improve the utilization of resources, alleviating the worsening traffic pressure, then achieving win-win results.

Yongan Guo, Ye Yang, Yiming Guan

A Relevance Vector Machine Based Probability Prediction Method of Channel Available Time

The uncertainty of spectrum resources will seriously affect the prediction results of cognitive radio, and then affect the communication channel allocation and spectrum access. Therefore, it is very important to judge, analyze and estimate the state change of the spectrum resources. This paper introduces the RVM (Relevance Vector Machine) theory and put forward the probability interval prediction method of channel state duration. Based on the traditional machine learning, RVM is integrated with the Bayesian inference framework, and it can give the estimate value of the prediction error and give the prediction interval, which can cover the real value well.

Zhenyu Xu, Dezhi Li, Shuo Shi, Zhenbang Wang, Jin Yao Jiang

Improve Energy Consumption and Packet Scheduling for Mobile Edge Computing

Mobile edge computing (MEC) has attracted great interests as a promising approach to augment computational capabilities of smart mobile devices by using computation offloading. In this paper, we jointly formulate an optimization problem to minimize both energy consumption and packet scheduling. By adopting Promoted-by-probability (PBP) scheme, we efficiently control packet jamming of different priority packets transmitting to MEC. A modified krill herd met heuristic optimization algorithm is presented for the purpose of obtaining the optimal results of minimizing the total overhead of MEC. The evaluation study demonstrates that our proposal can outperform efficiently in terms energy consumption and execution packet jamming.

Yibo Yang, Honglin Zhao, Xuemai Gu

A Sum-Rate Maximum Design of Transceiver and Relay for SWIPT Systems

Simultaneous Wireless Information and Power Transfer (SWIPT) system is considered in this paper, where the relay has no fixed power supply and thus needs to be charged by the source. We propose a new joint design of transceiver and relay architecture in terms of maximum sum-rate performance. We first propose a novel scheme for energy-constraint relay to harvest energy, when relay knows channel state information and each relay receives power or information judging by a certain threshold. For the proposed scheme we investigate the trade-off of information rate and energy harvest. When the relay transfer information, its power have to be subjected to the collected energy. Then we transfer the problem of sum-rate to the problem of minimum mean square error (MSE) and propose a low-complexity calculating algorithm to calculate joint precoding of transceiver and relay based on a duality relationship. By simulation, we show that the proposed scheme has a better trade-off when compared to traditional periodic switching scheme, and the proposed algorithm could get lower computation complexity.

Shiqi Wang, Lin Ma, Yubin Xu

Consensus-Based Privacy-Preserving Algorithm

In this paper, we use secure multi-party computation to protect privacy. Based on consensus-based distributed support vector machines, we present a new consensus-based privacy-preserving algorithm to conduct secure multi-party computation. The proposed algorithm run in parallel at each iteration, which reduce the running time. Furthermore, what needed to be communicated at each iteration is only a coefficient vector, therefore privacy is protected to the uttermost. The algorithm is proved to be convergent globally. Numerical experiments demonstrate the feasibility and efficiency of the new algorithm.

Heng Li, Fangfang Xu

Correction Method for Measurement of EUT with Dipole Antenna in GTM Cell

Gigahertz transverse electromagnetic (GTEM) cell is a promising alternative way to implement electromagnetic interference (EMI) and electromagnetic susceptibility (EMS) measurements for small transceivers due to its significant advantages on small space and low cost. However, different with full-wave anechoic chamber, only one wave absorption wall is setup in the GTEM cell at the opposite side of input port, a tapered waveguide cavity structure is used to produce uniformly distributed transverse field, that would raise another issue: coupling effect between the antenna under test (AUT) and the structure of GTEM cell. The effect of impedance deviation of AUT is studied in this paper, a formula to calculate the impedance of AUT under coupling situation is deduced. By using the model proposed in this paper, the transmission power reduction of equipment under test (EUT) due to the impedance mismatch caused by coupling issue can be numerically calculated, and result to more accurate measurement result.

Weijun Hong, Huanhuan Lin, Jian Guo, Hongjie Liu, Xiaoyang Liu

Design and Realization of General Test and Diagnostic Software Platform Based on AI-ESTATE

The increasing weapon equipments bring forth burdensome test and diagnosis tasks. Some problems that have been emerged in the developing maintenance and support system of multiform weapon equipments have been analyzed, such as the poor generality, the difficulty of sharing knowledge and interchanging information. A method of constructing universal test and diagnosis platform based on the AI-ESTATE standard is proposed in the paper. Aiming this, AI-ESTATE standard provides basic method to facilitate information exchange by defining a set of knowledge and data specification formats using information model, by defining formal services to form interface standards among diagnostic reasoner and other test system components. The system architecture of general test and diagnosis software platform applies the COM component technology to realize the separation of between test and diagnosis based on the principle of generalize and standardize. Then the function, constitution and realization of its general diagnostic software based on AI-ESTATET are researched in this paper. The realization of diagnosis model management services and reasoner manipulation services is described. This platform can test and diagnosis multiform weapon equipments, such as missile equipment, radar equipment and multiform artilleries. Especially, it solves the problem of sharing information and portability of software by information model and service.

Huixia Jiang, Cheng Wang, Xu Li, Baohua Wei

Broadband Notching Mask for Immunity Improvement of Onshelf UHF RFID Tag

Broadband design (860 MHz–960 MHz) of ultra high frequency (UHF) radio frequency identification (RFID) tag significantly propelled its worldwide application, however also make RFID system suffering interference with other wireless systems severely. A broadband notching mask which is consisted of a pair of split ring printed on flexible 0.3 mm polyethylene terephthalate (PET) is proposed in this paper. A wide band notching effect would be caused by attaching the mask on top face of RFID tag, which turned the wide band tag into a narrow band tag. Thus the immunity of the system can be greatly enhanced. Different notch frequency and bandwidth can be obtained by adjusting the size and geometry of the split ring. The simulations show that after attaching the mask on the tag, the original bandwidth of 750 MHz–1.14 GHz is changed to 670 MHz–890 MHz without any distortion on the radiation pattern of the tag except –1.18 dB gain reduction. The scheme proposed in this paper provides a simple way to avoid interference among RFID and other wireless systems, thus further lowered the threshold of the deployment of UHF RFID system applications.

Weijun Hong, Deken Chen, Huanhuan Lin, Jian Guo, Hongjie Liu

An Anti-desynchronization Light-Weight Security Protocol of RFID Based on the Time Factor

Aiming at the desynchronization attack problem of lightweight security protocol of RFID, a kind of anti-desynchronization protocol is proposed, which is based on time factor updated instantly. The time factor is stored in the tags, and its role is to ensure the freshness and non-repeatability of the interactive information. The protocol is only related to Hash calculation, XOR and cyclic shift calculation, so it can ensure the low computational complexity. The security of the protocol is proved by the security analysis and BAN logic. According to the results of analysis and proof, compared with the same kind of lightweight security protocols, this protocol can resist not only the general type of attacks, but also the desynchronization attack described in this paper, which ensures the privacy and security of the communication information.

Xinpeng Li, Ziming Guo, Xin Gao, Hao Zhang, Shengqi Lv, Yongzheng Mu, Yuexing Peng

MSE Analysis Based on Nearly-Oracle Estimation for SCoSaMP Algorithm

For the reconstruction of signals acquired with Sub-Nyquist sampling system based on redundant Gabor frames, SCoSaMP (Signal space-based CoSaMP) algorithm has excellent performance. However, there’s still no analysis about the MSE analysis under Gaussian noise and it is hard to estimate SCoSaMP algorithm reconstruction performance from a theoretical point of view. This paper presents an MSE analysis method based on nearly-oracle estimation to assess the error generated by Gaussain noise. With the proposed method, the upper bound of the MSE (Mean Square Estimate) is calculated, which shows how to improve the algorithm more quickly.

Peng Chen, Cheng Wang, Xiangjun Song, Deliang Liu, Wanling Li

Research on Amount of Information of Multi-satellite Electronic Reconnaissance Based on Joint Probability Data Association

With a number of satellite electronic reconnaissance as the background, based on the idea of joint probability data association (JPDA), a joint probability calculation model of multiple reconnaissance data for multiple targets is put forward. Based on the information entropy theory and the data association probability, an information acquisition of joint reconnaissance of multiple electronic reconnaissance satellites model is put forward. Simulation results show that compared with the amount of information before the data association, the association of the probability data can further improve the information acquisition and increase the efficiency of information processing.

Gang Yang, Xiangwei Liu, Jianpeng Guo

Fast CU Size Decision of Intra Prediction for Enhancement Layers in SHVC

A fast CU depth level decision algorithm with low complexity for Scalable High Efficiency Video Coding (SHVC) is proposed to reduce the computational complexity caused by the recursive quad-tree structure of Coding Unit (CU) inherited from HEVC. The proposed scheme enables the early termination for CU sizes for intra prediction in the enhancement layer (EL) by using the property of the energy distribution in the current CTU and the optimal coding depths of the neighboring CTUs. Based on an adaptive thresholds scheme, the texture complexity can be categorized to three types and the CU depth level range is therefore narrowed correspondingly. Besides, the spatial correlation existing in the encoded neighboring CTUs is utilised to further reduce the number of Rate Distortion (RD) evaluation. The coding time is therefore significantly saved. The proposed algorithm is evaluated in the reference software of SHVC (SHM12.0). The experimental results shows that the reduction in encoding time can be up to 42.95% in comparison with the original encoding scheme in SHM.

Chang Yu, Xin Lu, SongKai Li, Yue Hu

The Design and Optimization of DDR3 Controller Based on FPGA

Double Date Rate (DDR) SDRAM is the double rate synchronous dynamic random memory. It can sample twice on the rising and falling edges of the clock. Therefore, its sampling rate is theoretically twice the conventional SDRAM. However, due to other time cost, its bandwidth utilization is great lower than the theoretical value. DDR3 is the third generation and it has lower power consumption and higher sampling rate, so it is more suitable for data buffers than other SDRAM. Xilinx offers an IP core called MIG to simplify the interface of DDR3 SDRAM. This paper analyzes the problem of low bandwidth utilization, proposes an improved method, and designs a controller similar to the FIFO architecture based on the MIG core. In this way, the user-oriented interface is further simplified and the designer can use it easily. In addition, it has better portability.

Xuedong Wang, Lingyu Shen, Min Jia

A Novel Neuro-Space Mapping Technique Incorporating Self-heating Effect for High-Power Transistor Modeling

Accurate modeling of self-heating effect of high-power transistor is critical for reliable design of microwave circuit and system. In this paper, a novel neuro-space mapping (Neuro-SM) method incorporating self-heating effect is presented. By modifying the voltage and temperature relationships in the existing electro-thermal nonlinear model, the proposed Neuro-SM produces a new model exceeding the accuracy limit of the model. To accurately describe the self-heating effect, separate mappings for temperature and voltage at gate and drain are used as the mapping structure in the proposed method. The mappings combined with thermal sub-circuit including thermal resistance-capacitance parallel with thermal current are used to describe the self-heating effect. The validity and efficiency of the proposed Neuro-SM method incorporating self-heating effect are demonstrated through a modeling example of a high-power transistor used in cellular infrastructure market.

Lin Zhu, Jian Zhao, Wenyuan Liu, Lei Pan, Deliang Liu

Trilateral Game Aided Information Management for Open Complex Giant Systems

Nowadays, the management and control of open complex giant systems have become a hot topic. In this paper, based on the features of network topology, nodes’ heterogeneity and various information attributes, we propose a trilateral game to model the information flow management mechanism for open complex giant systems. Moreover, the players’ interactions and strategies are elaborated, followed by the derivation of the subgame perfect Nash equilibrium of this game. Furthermore, we provide a toy example relying on the K-anonymity algorithm to model the degree of ‘information transparency’ for the information supervisors. Finally, sufficient simulation results and theoretical analysis show the efficiency and feasibility of our proposed model.

Dewei Yang, Ruiyang Duan, Sanghai Guan, Jinwen Sun, Huifeng Xue

The Scheme Design of RFID Anti-collision in Mobile Tag Environment

Due to collision and mobile problems, it is difficult to use a single reader to identify a large number of mobile tags successfully. In this paper, a new anti-collision scheme is proposed, which combines the tag anti-collision algorithm and multiple reader deployment to solve the mobile tag collision problem. This scheme adopts grouped dynamic frame slotted ALOHA algorithm based on CDMA to deal with the collision which is caused by that large amounts of tags response to the reader. And it adopts the power control algorithm based on cellular model to deal with the collision between the readers. The simulation results show that the total number of slots needed by the tag anti-collision algorithm is less than other similar algorithms; the cumulative adjustment times of reader anti-collision algorithm are less than other similar algorithms, and the algorithm is more stability. It has certain application value in practical engineering.

Xuan He, Shizhong Li, Hongjun Wang, Quan Yuan

A Threshold Denoising Algorithm Based on Mathematical Morphology for Speech Enhancement

The presence of noise in speech signals can significantly degrade the performance of speech recognition systems. A threshold denoising method based on mathematical morphology is proposed to reduce background white noise. In the method we consider speech spectrograms as images and construct binary images from a normalized 256-level gray scale spectrogram image. We take advantage of a sudden slowing in the average value (ratio of the number of ‘1’ pixels to the total pixel number) of the binary image, and use it as the threshold value to zero spectrogram elements below the threshold, normalize the spectrogram, and finally, reconstruct the original speech signal to achieve the goal of speech enhancement. The main advantage of the algorithm is fast speed that is highly desired in real-time speech processing.

Guangyan Li, Caixia Zheng, Tingfa Xu, Xiaolin Cao, Mao Xingpeng, Shuangwei Wang

Automatic Sleeping Posture Detection in Ballistocardiography

Sleeping posture is an important factor in the quality of sleep. In this paper, we present a study on the feasibility of the automatic detection of personal sleeping posture from ballistocardiograms (BCGs) recorded by unobtrusive loadcell-embedded mattress. The proposed system is intended as a screening and monitoring tool in home-healthcare applications and provides reference for patients with chronic disease to adjust sleeping pattern. This work extracts the features of a heartbeat waveform pattern obtained from BCG and use the Random Forest classifier to classify various sleeping postures. The experimental results of this work indicate that the proposed algorithm can achieve high accuracy when sleep is stable and in the stage of sleep instability it can also make most of correct decisions about sleeping posture.

Min Wang, Peizhi Liu, Weidong Gao

On the Fly Belief Propagation Decoding Algorithm for LT Codes

As the first realisation of Fountain Codes, Luby Transform (LT) codes provide high reliability and scalability and low complexities for data transmission in networks. Two basic algorithms, Belief Propagation (BP) and Gaussian Elimination (GE), were introduced to decode LT codes. However, both of them execute their decoding process only after all the encoded symbols have been received by decoder, which results in the waste of time, storage space and computing resource. In this paper, an improved decoding algorithm termed on the fly belief propagation (OFBP) for LT codes is proposed. Based on the BP algorithm, OFBP performs the decoding processing once each encoded symbol arrives thus distributing the decoding work during all symbols reception. Compared with the traditional BP algorithm, the actual decoding time of the proposed algorithm is highly shortened. Moreover, without processing all the encoded symbols, the actual storage space and decoding complexity are greatly reduced while maintaining the same performance relative to the traditional BP decoding scheme.

Longlong Suo, Gengxin Zhang, Dongmin Bian, Jing Lv, Haiping Chen, Zijun Liu

An Improved OFDM Timing Synchronization Algorithm with Variable Length of Cyclic Prefix

The influence of the length of cyclic prefix to ML algorithm synchronization performance has been studied. On the basis, an improved algorithm with variable length of cyclic prefix is proposed. The proposed algorithm has better synchronization performance than ML algorithm at low signal to noise ratio.

Yanping Li, Qichao Song, Hui Gao, Dongyan Wu, Lingzhi Zhang

Generalized Space Shift Keying Modulation Combined with Convolutional Coding

In this paper, a Generalized Space Shift Keying modulation scheme combined with convolutional coding is proposed, and the convolutional coding structure is given. Firstly, the transmission model and the convolutional coding structure of the system are introduced. Secondly, the decoding algorithm of antenna detection used in the receiver is analyzed, and the complexity of the receiving algorithm is compared. Finally, the transmission performance of the scheme is simulated and analyzed in the Rician fading channel, and the advantages and disadvantages of the scheme, traditional Space Shift Keying modulation and Generalized Space Shift Keying modulation are compared. The results show that the proposed scheme can prove the anti-channel fading performance of the system.

Pengcheng Guo, Bingyin Ren, Yongxin Zhang

The Dynamic Real-Time FBG Wavelength Demodulation System Based on FPGA

Due to the temperature drift characteristics and drive element nonlinear characteristics, the detection accuracy of FBG wavelength demodulation system based on tunable F-P filter is insufficient. In order to enhance the detection accuracy, the dynamic real-time correction technology for FBG wavelength was studied. Two kinds of real-time correction methods with series and parallel structure were analyzed and compared respectively. Then the real-time correction system with improved series system was proposed. The high order polynomial function between transmitting wavelength and driving voltage of tunable F-P filter was adjusted in dynamic real time by low-cost reference FBGs model. As a result the demodulation precision of the system was improved. The signal processing was designed based on FPGA as the core. All digital circuits, such as data acquisition unit, peak-searching unit, triangle wave driving unit, data calculation and transmission unit were integrated in the FPGA, so the real-time performance of demodulation system is guaranteed. The experimental results show that the wavelength demodulation range is 1526–1566 nm, scanning frequency is up to 100 Hz and maximum error is ±3 pm. Being compared with reported real - time correction method and direct voltage method, the FBG wavelength detection accuracy of demodulation system is improved by 70% and 83.3% respectively.

Yang Jiao, Peng Wang, Xu Han

The Design of Multiband Semicircle Fractal Antenna Applied in the Wireless Communication

In this letter, a multiband communication antenna is presented. It is iterated a semicircle fractal structure to formation and achieved four resonant frequency. The overall size of the proposed antenna measures 30 × 32 × 0.50 mm3. The multiple iterated semicircle fractal antennas can be applied in multiple communication frequencies of the 2.3, 2.8, 4.1, 9.1 GHz at the same time. Using fractal structure design of fractal antennas not only can achieve the purpose of miniaturization, but also can satisfy the antenna work in multiple frequencies, have the ability to make communication more convenient.

Xiao Hua, Deqiang Yang, Dongdong Geng, Qingsong Wang

Design and FPGA Implementation of a Quasi-Cyclic LDPC Decoder

The excellent error correction performance of Low-Density Parity Check code has made it widely used in many modern communication systems, including space communication system. This paper describes a design and FPGA implementation of a quasi-cyclic LDPC decoder based on Min-Sum Algorithm. The partially parallel design solves the contradiction between the consumption of hardware resource and decoding efficiency. The decoder achieves up to a BER of 10−3 at 4 dB, and a throughput of 300 Mbps per iteration for a code length of 8176.

Honglin Zhao, Haiyue Zhang

Decoding on the Modified Pruning Trellis for Correcting Insertions/Deletions

Both forward and backward passes cost a large number of computations in the traditional decoding algorithm of the concatenated code for correcting insertions/deletions. In this paper, states in the forward pass are pruned according to not only the pruning threshold but also backward quantities. Similarly, the number of states in the backward pass is also reduced according to the forward quantities. Using this modified pruning scheme, the smaller trellis and low-complexity decoding algorithm are achieved, compared with the traditional decoding on the adaptively pruned trellis. Simulation results show that, the computation reduction in the forward-backward algorithm is achieved with no performance loss.

Yuan Liu, Ruiqing Xing, Xiaonan Zhao

Ultra-Wideband Ranging System Prototype Design and Implementation

Real-time and accurate range information is essential to a variety of wireless applications, such as anti-lost devices, indoor localization and navigation, and Internet of things. Ultra-wideband (UWB) signal can achieve high-accuracy wireless ranging performance via its huge bandwidth advantage. In this paper, we design and implement a UWB ranging system prototype using ScenSor DW1000 chip. Under the line-of-sight (LoS) conditions, indoor and outdoor experimental results show the high-accuracy ranging performance with centimeter-level error of the system.

Chen Wang, Yue Wang, Shaolin Ma, Yifei Yuan, Lei Wang, Xin Zheng, Guilin Wang, Jiaxi Wang

Design of FPGA High-Speed Paralleling M Sequence

To resolve the problem of processing clock frequency far below data generation rate for generating high-speed m sequence in FPGA, this paper adopts three methods of delay method, equivalent method and substitution method to design the parallel structure for generating paralleling m sequence and implements it on FPGA. The test results show that the generated paralleling m sequences fully meet the standard format requirements. This parallel structure achieves better application effects in the tests of scrambling and descrambling, BER, and coding and decoding in high-speed communication system.

Zhi-Song Hao, Zhi-Ming Zheng, Rui-Liang Song

The Method of Netted Radar Embattle Based on Immune Seeker Search with Particle Mechanism

For the netted radar embattle under the deception jamming, because of the requirement of the distance between the radars and the coverage of the netted radar system, the optimal sites of the netted radar system obtained by the conventional optimization algorithm is not ideal. In this paper, the method of netted radar embattle based on immune seeker search with particle mechanism (ISSPM) is proposed. This method establishes a mathematical model for the deployment of the netted radar, and combines with the constraint conditions to construct the joint optimization objective function. Then uses the immune seeker search with particle mechanism method to deal with the problem. This method can find the optimal sites of the netted radar system quickly and accurately without falling into the local optimum.

Zhongkai Zhao, Jiaheng Ruan, Hongyuan Gao

Study of Agent Cooperation Incentive Strategy Based on Game Theory in Multi-Agent System

The “Folk Theorem” in Game Theory proves that in the process of one-stage game, the game player with selfish behavior may produce cooperative behavior in the process of repeated game. This paper mainly studies the cooperative behavior of Agents in Multi-Agent System from the perspective of Game Theory, against the problem of the “Prisoner’s Dilemma” caused by malicious Agents in game, this paper analyzes the influence of three different incentive strategies on trust cooperation behavior of Agents in the process of repeated game, and then gives the equilibrium boundary conditions and corresponding inferences under the three incentive strategies which make the game equilibrium happen. It is found that the incentive strategy can motivate malicious Agents to participate in cooperation in the process of infinite repeated games. Finally, an experiment is carried out to verify.

Shuyin Wang, Limei Jiang

Toward Optimal Selective Beam Allocation with Guaranteed Fairness for Multibeam Satellite Systems

With the increasing of traffic demand in satellite systems, it is essential to maximize the efficiency of resource utilization due to the expense and scarcity of on-board resources. In this paper, we propose a selective beam allocation algorithm with guaranteed fairness for multibeam satellite systems. The algorithm can achieve an acceptable trade-off between the maximum total capacity and the fairness among the spot-beams by allocating the basic power and bandwidth for low priority beams. In addition, the resources allocated for low priority beams can be adjusted flexibly by introducing a lower bound of the capacity. Extensive simulations evaluate the performance of the proposed algorithm. The results demonstrate that the total capacity of the proposed algorithm is 99% of water-filling algorithm. Furthermore, comparing with common selective beam allocation algorithm, the Jain Fairness index is improved by 20%.

Shengchao Shi, Guangxia Li, Zhiqiang Li, Zijun Liu, Zhongwu Xiang

Research on Auxiliary Automatic Generator Control Marketing System in Hebei Grid

As the blueprint of China electric power revolution is drawn as transmission and distribution separation and competitive electricity retail, the market of ancillary service like AGC is urgent to develop. In this paper Auxiliary Automatic Generator Control Marketing (short for AAGCM) system is developed in Hebei grid. With the AAGCM system, the traditional AGC system can be developed to intelligent power utilization system. After obtaining real-time data from WAMS, the state estimation is carried out periodically. The formula of impact energy is given in the paper. With simulating AGC operations, it can be calculated for guiding the consumers to purchase ancillary service directly. The structure, hardware configuration and data exchange of the system are illustrated. The system is an important component of smart grid and power market, which leads to better power quality and the better pricing for both sides.

Xiao Yang, Nan Wang, Zhengyu Pan, Liang Meng, Wenping Hu

Analysis on Problems During GOOSE Technology Application in Substation

GOOSE is a fast message transmission service defined in IEC 61850. It is very important for the inter-operability of IEDs. This paper analyzes the influence on the design and commissioning of substation automation system when GOOSE model is applied. Several problems of GOOSE application are discussed and the solutions of them are proposed. All of this are consultive for the GOOSE that will be applied widely in smart stations.

Lei He, Peng Luo, Yuhao Zhao, Binghai Zhang, Xianzhi Wang, Qingquan Liu

Electrocardiogram System Performance Evaluation Based on the LabVIEW Virtual Instruments Development Platform

Electrocardiogram (ECG) is a kind of electronic signal which represents the condition of hearts. In order to analyze the electrocardiogram accurately and efficiently, the ECG signal acquisition system based on the LabVIEW 2011 platform has been proposed in this paper. The interference signal could be alleviated by using the filtering module. The USB6210 data collection card which was designed by the NI Company is used for the collection of ECG signal. The signal acquisition module could be matched with the data acquisition (DAQ) module. Meanwhile, a mass of data could be storaged by the data storage module. The results show that the ECG collecting system which was designed in this paper is a marvelous system that could be widely used in recent decades.

Xiaoyi Zhou

The Error Model of the Smart Meter Under the Influence of Low Temperature

This paper focuses on the impact of low temperature environment on the measurement performance of smart meter. Based on the actual test data of the smart meter in the low temperature environment and processing software such as Matlab and Origin, we can investigate the relationship and influence level among the low temperature environment, operating load and metering performance of the smart meter. The data from the test field of smart meter in the actual operating condition of low temperature is set up in Mohe county of Heilongjiang province. The test functions of the meter include short and long-distance detection system, load control system, protection system and environmental monitoring system. And the research results show that the low temperature environment induces a shift to negative direction of the smart meter error, so that we can obtain the mathematical model of the smart meter with the change of temperature at different loads.

Xin Yin, Huiying Liu, Cong Yin, Jiangxue Man

A Multi-layer Low-Frequency Broadband Membrane-Type Acoustic Metamaterial Sound Isolator

A multi-layer low-frequency broadband membrane-type acoustic metamaterial sound isolator were investigated. It is a multi-layer “plate-membrane-plate-membrane-plate” structure composed of light round whole plate and elastic rubber membrane. By simulation analysis towards single layer and multi-layer structure as well as different parameters that affect multi-layer structure, the corresponding acoustic insulation index of each frequency band was obtained. By comparison of the acoustic insulation curves under different circumstances, the acoustic insulation properties under different circumstances can be obtained by direct-view. The results of simulation analysis can enrich the research of multilayered metamaterials to a certain extent.

Haiying Xing, Yan Chao, Xiaonan Zhao

A Rate Control Method for Reducing Quality Fluctuation in the 3D Embedded Wavelet Video Coder

Current rate control schemes in MCTF-based wavelet video coding lack efficient GOP-level bit allocation due to the shortage of GOP rate-distortion (R-D) information and the limitations of real-time encoding. Exploiting the advantage of offline video encoding, a GOP-level bit allocation scheme based on GOP R-D data estimated from the wavelet decomposed temporal-spatial subband R-D is described. Each video sequence is encoded twice. In the first pass, the R-D information of the GOP is generated, and this is utilised in the second pass to implement GOP-level bit allocation appropriate for the available bandwidth and such that the video sequence is coded with near-constant quality. Experimental results demonstrate that the proposed technique achieves a smoother, and hence more visually acceptable, quality than existing methods.

Xuesong Jin

Integrated Numerical and Experimental Study on Thermal Management of Permanent Magnet Synchronous Generator

Nowadays, the researches of wind generator are mainly based on horizontal axis wind generator in the world. The permanent magnet synchronous generator in this thesis has following advantages: high efficiency, low noise and small volume, etc. The most important characteristic is the excited part of rotor which uses permanent magnet (NdFeB) so that we don’t need extra excited circuits. But magnetization curve of permanent magnet is sensitive to temperature. In most cases, due to the overheating of the generator, the performance of permanent magnet is declined and the coil winding is burned out, thus, the generator efficiency is reduced and the service life is shortened. Therefore, the main purpose of this thesis is to design an effective method to overcome the elevated temperature of generator. Above all, this thesis studies the heating efficiency of generator and uses the hydromechanics to analysis software. Then compare the consequence between experiment and simulation of prototype permanent magnet synchronous generator. Finally, in order to solve the problem of heat dissipation, the generator is improved by changing the fin of the generator shell. So it is enough to prove the simulated method and model structure are reliable in this thesis.

Xi-Feng Wang, Qi-Chao Song

A Multi-objective Network Optimization Algorithm Based on QoS in Distributed Constellation Networks

This paper proposes and analyzes a multi-objective optimization algorithm based on QoS in distributed constellation networks, combining the topology and routing algorithm to optimize and reconstruct the network, a new heuristic networking scheme is also proposed to balance the network cost and the requirement weight. The algorithm is capable of minimizing the total network delay, improving the link utilization and achieving optimization combined with multi-QoS. The simulation results show that our algorithm and scheme can meet the needs of different network designs, optimize the performance and solve the problem of dynamic networking and network reconstruction, providing a basis for the research in combination of topology and routing in satellite networks.

Huiyun Xia, Zhuoming Li, Junqing Qi, Dezhi Li, Liang Ye

Behavior Prediction for Industrial Control System

While the Industrial control system(ICS) is making great progress for the society, it is facing a huge security risk at the same time. There are some methods like upgrading system and updating patches to protect the ICS, but they are inevitable lagging behind anyway. Byte-level is useful for network intrusion detection and does not need knowledge of the device to be detected. Based on the network data in the industrial control system, we propose an adaptive DBSCAN clustering method for extracting the control instructions in the data packet, and then learning these instructions with the n-gram model. According to received instructions, we are able to predict the next possible instruction. Whether the system is being attacked can be recommended by comparing the instruction that we forecast with the real instruction. Experiments show that the behavior prediction has high accuracy.

Shen Wang, An Huang, Zhongchuan Fu

Genetic Algorithm-Based Dynamic Spectrum Allocation for Cognitive Networks

In cognitive networks, cognitive users sense idle spectrum with a spectrum sensing technology in order to utilize the spectrum of primary users. If a cognitive user does not control the transmitting power, then primary users and other cognitive users will be interfered and network performance will also be degraded. Therefore, this paper first studies the optimization of transmitting power based on genetic algorithm. Furthermore, we combine genetic algorithm and ant colony algorithm to optimize transmitting power. Meanwhile, genetic algorithm is also used for spectrum allocation. With the combination of hierarchical genetic algorithm and simulated annealing algorithm, spectrum allocation is optimized and network utility is improved. Simulation results prove the effectiveness of our proposed algorithms.

Yongliang Sun, Xuewen Wu, Kanglian Zhao

Examination of Gait Disorders in Hemiparesis Patients Using Foot-Mounted Inertial Sensors

Gait analysis system constructed of foot-mounted inertial measurement units (IMUs) provides an effective way for estimating gait symmetry. Unfortunately, gait asymmetry may not be visible in a single (spatial or temporal) dimension, and the dual-foot data may be out of phase in the time axis. This paper aims to explore a symmetry analysis method to give a close examination of gait disorders in hemiparesis patients using inertial sensor-based technology. Zero velocity updates (ZUPT)-aided Inertial Navigation System (INS) algorithm is used to estimate foot movements over multiple strides, and the accumulated INS error is further bounded using an inequality-constrained Extended Kalman filter (EKF). Fréchet distance is adopted to align the time series, thereby yielding the symmetry index between dual-foot data. Experiments were conducted along a straight-line path, and both healthy subjects and hemiparesis patients are participated. Experimental results demonstrated that the symmetry analysis with Fréchet distance could reveal gait disorders in both spatial and temporal dimensions.

Hongyu Zhao, Zhelong Wang, Sen Qiu, Ning Yang, Yanming Shen

The Scan View Planning Algorithm Based on the CAD Model

The surface of large-scale structure is large and complicated, and a lot of different positions under different pose are needed for the measuring system to get integrated three-dimensional surface data. The measurement accuracy could be improved by increasing sampling point number, but there are unavoidable problems like having larger data information and less efficient. When high measurement accuracy and high measurement efficiency are required, it is needed to plan the view point. In this paper, rectangle self-adaption sampling algorithm based on the CAD model is proposed. In this method, firstly, the least sampling points are determined by dividing up the large-scale structure surface area based on the camera measurement area. Secondly, the surface curvature of one view point is calculated and compared with camera incident angle. If all of the surface curvatures of the view point are less than the camera incident angle, the view point is saved. Otherwise, one view point is increased. Finally, the same operations are applied to all of the view points, and the final view point number is determined. Simulation and experimental results show that, the algorithm proposed can measure the surface of large-scale structure quickly and efficiently.

Yali Wang, Yun Hao, Ying Wang

A Comparison of Four Memetic Particle Swarm Optimization Algorithms for Continuous Optimization

Particle swarm optimization (PSO) belongs to swarm intelligence category. It is a famous prototype for dealing with continuous optimization problems, and its efficiency can be enhanced by hybrid with local search methods. Based on recently designed four memetic PSO algorithms, this paper investigates the effectiveness and running time of these algorithms. Experiments are conducted on a set of mathematical test functions. The effectiveness of algorithms are compared based on the quality of solutions found in repeated runs. Their running times are compared based on clock time metric. It is found that PSO hybrid with crossover operator is much more effective than the other memetic PSO algorithms.

Xin Zhang, Xingming Liu, Mingshuo Liu, Shouju Liu, Yanyu Xiao

Study of the Magnetic Field Strength in the Eight-Figure Coils

Along with the progress of the technology, people have an increasing demand of electricity. In the process of power transmission, the copper loss and wire aging will bring hidden trouble to the equipment. On special occasions, such as mining engineering and underwater working, the traditional power transmission system with wire will lead fatal harm to the workers. In this case, the technology of wireless power transmission has received more and more attention from all over the world. In this paper, an eight-figure coil is designed and analyzed to apply in wireless power transmission system. Compared with the circular coil and square coil, the eight-figure coil will generate relatively uniform magnetic field. When this coil is applied in wireless power transmission system, it will reduce the effect on the coil misalignment to the power transmission efficiency. Thus, it will broaden the application range of the wireless power transmission system.

Yankun Li, Xiu Zhang, Yanyu Xiao, Shanshan Peng, Rui Liu, Yuxin Huang, Kangrong Wu

Resource Allocation Algorithm for V2X Communications Based on SCMA

In this paper, we propose a resource allocation algorithm for V2X communications based on Sparse Code Multiple Access (SCMA). By analyzing the interference model in the V2X scenario, we formulate the problem which deals with resource allocation to maximize the system throughput. A graph color-based user cluster algorithm combined with resource allocation algorithm based on both result of clustering and SINR is presented to solve the problem. The simulation results indicate that the throughput performance of system based on SCMA is superior to which based on OFDMA, and the proposed algorithm can improve the system throughput and the number of access users.

Wei Wu, Linglin Kong, Tong Xue

An Infrared Target Tracking System and Implementation

To satisfy the demand of infrared image terminal guidance, this paper designs a micro image target tracking system containing key information processing unit based on DSP, and the out expansion, commanding signal dispatching processor based on FPGA. The advantage the hardware platform with DSP + FPGA is discussed, and the design of main module of DSP and FPGA is carried out. The detail flow of image processing software is also introduced. The system has certain flexibility, expandability and is real time.

Xiaochun Zhang, Zhihong Liu, Tianhao Jiang

Research on Non-contact Angle Measurement Based on AMR Effect

A non-contact angle measuring method based on AMR effect is proposed in this paper. The method improves the measurement sensitivity and resolution with a Wheatstone bridge. In this paper, the function of the output voltage of the Wheatstone bridge is derived, which is on the angle between the direction of the external magnetic field and the bridge. Besides, the magnetic field distribution of a radially magnetized permanent magnet is analyzed. A device for measuring the angle in the range of ±10° is designed, and the sensitivity of the device is about 15 mV/arcminute. The method introduced in this paper has advantages of simple structure, low cost, high sensitivity and free from space limitation.

Yinguo Huang, Shuya Zhuang, Zhiyi Wang, Xiaomei Zhang, Meirong Zhao

Research on Non-contact Torque Sensing Method by Magnetoelastic Effect

Torque measurement is widely used in the field of modern machinery industry, and plays an important role in the vehicle, tunnage, energy regeneration, petroleum and other fields. However, the existing torque measurement methods have some limitations in the face of complex conditions. Therefore, a new means based on self-inductance coils has a high research significance. This study investigated the sensing principle of self-inductance coil and the torque and deduced the relationship between the permeability u of soft magnetic material and self-inductance coefficient L. And the theoretical model of torque measurement based on self-inductance coefficient is established by using L as the new parameter to characterize the torque. We obtained experimental data through building experimental platform and conducting torque tests. The result shows the maximum non-linear error is 2.83%, the sensitivity is 0.107 uH/Nm, and the maximum repeatability error is 2.68% FS. This method of measuring the torque of the shaft by measuring the self-inductance coefficient is a new exploration and breakthrough of the problem of magnetoelastic torque measurement.

Yinguo Huang, Xiaomei Zhang, Shuya Zhuang, Hongxu Zhang, Meirong Zhao

Method of Torque Measurement Based on the Equivalent Theory of the Magnetic Field and Stress

The non-contact torque sensing application is used widely in modern measurement, but now the structure of torque measurement system was found to be relatively complicated. In this work, a non-contact torque measurement method based on the equivalent theory of the magnetic field and stress is proposed to detect the rotation angle of magnetization using thermodynamic equilibrium principle, and a theoretical model of equivalent stress and rotation angle of magnetization is established. The sensitivity of the torque measurement system reached 28.4 mV/(Nm) and the maximum nonlinearity error is 1.3%FS through the experiment, which verifies the feasibility of the torque measurement method.

Hongxv Zhang, Yinguo Huang, Xiaomei Zhang, Xinghua Li, Peilu Liu

Patten Recognition, Deep Learning Automata and Networking


A Parallel Genetic Algorithm with Three-Parent Crossover for Real Parameter Optimization

Genetic algorithm belongs to evolutionary algorithm category. It is a good algorithm prototype for handling real parameter optimization, and its efficiency can be enhanced by executing generations in parallel. Based on a three-parent crossover and a diversity operator, this paper investigates the running time of executing genetic algorithm in parallel. Specifically, parallel execution is realized based on multicore central processing unit of computer. Extensive experiments are conducted on a set of mathematical test functions. The running times of genetic algorithm with and without parallel execution are compared based on the types of optimization problem. Moreover, the results are presented from one core to eight cores. A time increase curve is fitted based on polynomial model, which could assist users to conduct parallel genetic algorithm to solve problems.

Xin Zhang, Qinglian Zhang

Ship Fuzzy Recognition Based on Superstructure with Maximum Membership Rule

The Automatic Target Recognition (ATR) of ship targets based on high resolution Inverse Synthetic Aperture Radar (ISAR) images has a good prospect of marine environmental protection, monitoring and traffic management. In this letter, a novel ship classification technique is proposed based on the ship superstructure by using the fuzzy recognition method. An improved segmentation algorithm of the ship silhouette is applied to obtain the segment comparative mean (SCM) feature. The SCM is used to calculate the target’s membership of each class and eventually the maximum membership rule is applied to determine the target’s class. The experimental results of applying the technique on real ISAR data demonstrate the effectiveness of the proposed approach.

Yong Wang, Pengkai Zhu

Chinese Dialects Identification Using Attention-Based Deep Neural Networks

This paper presents a novel Chinese dialects identification system. We use attention-based deep neural networks (AB-DNN) to obtain the Chinese dialects model as back-end. The front-end fuses identity vector (i-vector) with the global prosodic information as input used to describe the dialectal category information accurately. In the task, five kinds of Chinese dialects including Min, Yue, Wu, Jianghuai, Zhongyuan and standard Mandarin are selected as the identification objects. Experimental results show that 21.1% relative equal error rate (EER) reduction is obtained compared with regular deep neural networks (DNN) and further 14.5% reduction when apply global fusion features. The method based on AB-DNN combined with global fusion features observes 29.2% performance improvement compared to traditional DNN with MFCC.

Yuanhang Qiu, Yong Ma, Yun Jin, Shidang Li, Mingliang Gu

Probabilistic Model of Object Detection Based on Convolutional Neural Network

The combination of a CNN detector and a search framework forms the basis for local object/pattern detection. To handle the waste of regional information and the defective compromise between efficiency and accuracy, this paper proposes a probabilistic model with a powerful search framework. By mapping an image into a probabilistic distribution of objects, this new model gives more informative outputs with less computation. The setting and analytic traits are elaborated in this paper, followed by a series of experiments carried out on FDDB, which show that the proposed model is sound, efficient and analytic.

Fang-Qi Li, Xu-Die Ren, Hao-Nan Guo

Learning Automata Based SVM for Intrusion Detection

As an indispensable defensive measure of network security, the intrusion detection is a process of monitoring the events occurring in a computer system or network and analyzing them for signs of possible incidents. It is a classifier to judge the event is normal or malicious. The information used for intrusion detection contains some redundant features which would increase the difficulty of training the classifier for intrusion detection and increase the time of making predictions. To simplify the training process and improve the efficiency of the classifier, it is necessary to remove these dispensable features. in this paper, we propose a novel LA-SVM scheme to automatically remove redundant features focusing on intrusion detection. This is the first application of learning automata for solving dimension reduction problems. The simulation results indicate that the LA-SVM scheme achieves a higher accuracy and is more efficient in making predictions compared with traditional SVM.

Chong Di, Yu Su, Zhuoran Han, Shenghong Li

Application of an Improved MUSIC Algorithm in Ship-Borne High Frequency Surface Wave Radar

Sea clutter seriously affects the radar detection performance of the sea targets. For SBHFSWR (ship-borne high frequency surface wave radar), the widening first-order sea clutter because of the carrier’s movement obscures the ship targets and causes the difficulty in target detection. One potential method to distinguish the interested sea targets from the sea clutter background is to use spatial super resolution methods since the interested targets and interfering sea clutter usually have different arrival azimuth angles. In this paper, an improved MUSIC algorithm based on the oblique projection is presented. The algorithm not only uses the oblique projection operator to suppress the first-order sea clutter, but also makes full use of all the characteristic information of the noise subspace and the signal subspace to improve the estimation precision. The simulation results verify the effectiveness of the proposed algorithm.

Gaopeng Li, Siwen Wang, Kun Jiang

A Method for Modulation Recognition Based on Entropy Features and Ensemble Algorithm

Ensemble learning is a useful frame algorithm which could improve the performance of weak learners by combining them. It is well known AdaBoost algorithm is one of these successful boosting algorithms. In this paper, we choose it to complete ensemble frame. we compare the performance of three machine learning algorithms including SVM, AdaBoost and decision tree stump based on communication signal modulation scheme to prove the effect of AdaBoost. The AdaBoost algorithm combines decision tree stump and iterates 500 rounds in the training phase. And the result reveals the performance of AdaBoost is proximal to that of SVM. At last, experiment to examine the features’ working principle on signals is done. The features can identify 4ASK correctly in all SNRs.

Zhen Zhang, Yibing Li, Yun Lin

An Analysis of the Correlation Reception Applied in Reading a Metal Barcode Label

The reduction for the estimation of the impedance change caused by a metal barcode label was given. With this reduction, the correlation mask was presented. The optimal action distance was investigated and the inter-bit interference with a correlation receiver based on the bit interval was given by simulations.

Yin Zhao, Hong-guang Xu, Qin-yu Zhang

Diagnosis Based on Machine Learning for LTE Self-Healing

Self-Healing is one of the most important parts of self-organizing communication networks that offer detecting cells with a service of degradation, finding out the fault cause, and executing compensation and repairing actions. Diagnosis identifying the fault caused by problem cells is one of the most complex tasks. To perform the diagnosis, this paper presents two multi-classification diagnosis system based on machine learning methods, namely SVM (Support Vector Machine) and AdaBoost (Adaptive Boosting). Results show that the performance of the AdaBoost method compared to SVM with linear kernel is significantly better in terms of diagnosis error rate and undetected rate, but the false positive rate of AdaBoost is a little higher than SVM. SVM is more focusing on filtering normal cases, but AdaBoost is more inclined to find out fault cases. It indicates that the diagnosis system based on AdaBoost has high accuracy and reliability than SVM in this data set.

Xuewen Liu, Gang Chuai, Weidong Gao, Yifang Ren, Kaisa Zhang

Quantum-Inspired Teaching-Learning-Based Optimization for Linear Array Pattern Synthesis

In order to solve complex optimization problems, a novel intelligence algorithm called quantum-inspired teaching-learning-based optimization method (QTLBO) is proposed. By hybridizing teaching-learning-based optimization (TLBO) and quantum computing theory, QTLBO can be well evolved by simulated quantum rotation gate operation. Then QTLBO is used to resolve linear array pattern synthesis problems. Simulation results are provided to show that the proposed QTLBO method can solve this kind of problems efficiently and give out a superior solution than those obtained by previous classical intelligence optimization methods. The proposed QTLBO method can search for the global optimal solution of linear array pattern synthesis problems.

H. Y. Gao, X. T. Zhang, Y. N. Du, M. Diao

Multi-speaker Recognition in Cocktail Party Problem

This paper proposes an original statistical decision theory to accomplish a multi-speaker recognition task in cocktail party problem. This theory relies on an assumption that the varied frequencies of speakers obey Gaussian distribution and the relationship of their voiceprints can be represented by Euclidean distance vectors. This paper uses Mel-Frequency Cepstral Coefficients to extract the feature of a voice in judging whether a speaker is included in a multi-speaker environment and distinguish who the speaker should be. Finally, a thirteen-dimension constellation drawing is established by mapping from Manhattan distances of speakers in order to take a thorough consideration about gross influential factors.

Yiqian Wang, Wensheng Sun

Cloud Computing Platform Design and Machine Learning-Based Fault Location Method in Automatic Dispatching System of Smart Grid

In order to improve the effectiveness and efficiency of automatic dispatching of smart grid, fully exploiting the monitoring data and mining the inherent relation among the data are the key to the grid state monitoring, abnormality prediction and fast fault location for automatic dispatching service of the smart grid. With the rapid increase of grid scale and the type and volume of the monitoring data, distributed storage and computing-based cloud computing platform becomes the basic infrastructure of smart grid. In this paper, after the structure and function analysis of the current management and dispatching platform D5000, a cloud computing platform is designed and integrated into the D5000 platform. This cloud computing platform is constructed hierarchically, in which the Hadoop performs distributed data storage and computing via HDFS and MapReduce, while Spark implements data mining with the aid of Spark SQL when frequent data exchange and data computing is required. The data mining task includes modeling the state of the automatic dispatching subsystem, making early warning, and locating faults, for which machine learning-based algorithms are developed. The feasibility of the designed platform and the effectiveness of the proposed methods are verified.

Ziming Guo, Haibo Guo, Yongzheng Mu, Yuexing Peng, Xinpeng Li, Xin Gao, Yong Liu

Adaptive Sliding Mode Guidance Law with Terminal Impact Angle Constraint

Aiming at the requirements of some guided weapons with attack accuracy and terminal attack angle constraint, an adaptive sliding mode guidance law with terminal impact angle constraint is proposed based on sliding mode variable structure control theory. This guidance law chooses the angular rate of the line of sight as the sliding mode, introduces the angular constraint, regards the target maneuvering as limited disturbance, and the stability of the guidance law is analyzed by using Lyapunov theory. In the meanwhile, the chattering phenomenon is substantially weakened by the combination of variable switching term and saturation function. Finally, the simulation is made by applying the guidance law to the missile real model, and the results show that compared with traditional algorithm, the designed guidance law can hit the target with less miss distance and impact angle error.

Dan Fang, Kuanqiao Zhang, Xu Zheng, Renzhaxi Ci

Research on Human Body Communication Channel Characteristics

Human body communication (HBC) is a communication technology that uses the body of a person as a channel to propagate signals. Many characteristics of HBC present advantages over the most common radiation-based methods, which makes it an interesting alternative to implement the emergent body area networks. The characterization of the HBC channel presented in the literature still cannot provide a good and complete explanation for the channel behavior. Aiming at the problem, in this work, we present our attempt to characterize the signal in the HBC channel, and on the basis of the capacitive coupling, the model of HBC transceiver and prototype is designed. The relationship between the rate and bit error rate and the factors that affect the HBC channel such as transmission distance, electrode material, etc. based on the capacitive coupling are studied and simulated. The experiment results show that under the guarantee of high quality communication, the data rate of prototype can be up to 400 kbps. The channel has a feature of band-pass response, and the transmission distance and electrode materials have a non-negligible influence in the channel profile in the middle and high frequency range.

Liu Zhiyuan, Yang Peng, Tang Shengwu, Liu Hui

Feature Pooling in Scene Character Recognition: A Comprehensive Study

In this paper, we focus on the feature pooling methods for scene character recognition. We research three kinds of pooling methods: the average (sum) pooling, max pooling and weighted-based pooling methods. Specifically, various feature pooling methods are introduced, their merits and demerits are studied, and existing problems are discussed. Finally, we offer a specific comparison on the ICDAR2003 and Chars74k databases.

Zhong Zhang, Hong Wang, Shuang Liu, Yunxue Shao

Cramér–Rao Low Bound Estimation for MSE of SCoSaMP Algorithm

SCoSaMP (Signal space-based CoSaMP) is an algorithm with excellent performance proposed for reconstruct signals acquired with Sub-Nyquist sampling system based on redundant Gabor frames. However, there’s still no estimation of the lower bound of the error MSE under Gaussian noise and it is hard to estimate the reconstruction performance of SCoSaMP algorithm from a theoretical point of view. This paper presents the CRLB (Cramér–Rao Low Bound) estimation for MSE (Mean Square Estimate) of SCoSaMP algorithm and analyzes the impact factor for noise suppressing, which shows the road for further improving the algorithm.

Cheng Wang, Peng Chen, Huahui Yang, Wanling Li, Deliang Liu, Chen Meng

Task Scheduling Algorithm Based on Sectional Sorting and Standard Deviation for Intelligent Meter Cloud Testing

Task scheduling algorithm is the core of cloud computing. Due to the heterogeneity of hardware devices, most traditional scheduling algorithms are insufficient to handle the makespan and load balancing at the same time. To establish a scheduling algorithm adapted to the intelligent meter cloud testing platform, this paper proposes an algorithm based on sectional sorting and standard deviation. According to the characteristics of tasks and the performance of compute nodes, considering the idea of dynamic programming technology, the paper adjusts the expected execution time matrix-ETC with segmental method, and then calculates the standard deviation to optimize the algorithm. At last the experiment shows this algorithm outperforms traditional min-min algorithm in terms of makespan and load balancing.

Bing Zhao, Xin Gao, Ping Wang, Rui Wang

Secure Wireless Transmission of Smart Grid Based on Secret Coding

The wireless transmission of information in the smart grid requires high reliability and security. In China, LTE technology has been widely used for data transmission in smart grid system. How to effectively ensure the security of information transmission has become a very critical issue. In this paper, we propose a secure wireless transmission scheme to prevent the information from being eavesdropped by using the secret coding technology in the physical layer. Since the eavesdropper’s channel condition is deteriorated, it ensures the security of the data transmission in wireless scenarios. This scheme can prevent the eavesdropper from getting any information and ensuring the security of the data transmission.

Liming Chen, Xuzhu Dong, Zhengrong Wu, Zhiwen Liu, Yun Wu

A Beamformer Based on Sparse Array with Various Array Structures

The degrees of freedom (DOF) of the adaptive beamformer based on conventional linear array is limited by the number of physical array sensors. One way to enhance the DOF is to choose sparse array, whose DOF is greater than the number of sensors in the array. In this paper, we explore the adaptive beamformer based on sparse array with various sparse array structures. We evaluate the performance of different structures and get some useful conclusions on how to select the structure of sparse array. In addition, we also consider one robust beamforming technique to further improve the performance of sparse arrays. Simulations are provided to compare the results obtained by different strategies.

Yanqi Fan, Lei Yu, Yinsheng Wei, Rongqing Xu

Algorithm Design for Sleep Monitoring System Based on Mattress

In order to help health care provider monitor patient status such as respiration rate, body movement and apnea, we designed a low-cost sleep monitoring mattress based on pressure sensors in this paper. In particular, some mattresses have been used in nursing homes so that they can master the old people’s sleep condition at a minimal cost. Experimental results show that the respiration rate compared to medical equipment with the difference between one or less reached 92%. Body movement monitoring had a 95% accuracy rate. As for apnea, the accuracy of monitoring results was close to 90%.

Chen Shu, PeiZhi Liu, WeiDong Gao

Automatic Container Code Recognition System Based on Geometrical Clustering and Spatial Structure Template Matching

At present, at most ports the code of each container is registered manually, which is of a great potential safety hazard and inefficient. In this paper we present a container-code recognition system, which use the geometrical clustering of connected component extracted by MSER descriptor and spatial structure template matching for location and various CNN-classifiers for identification. Experiments confirmed the robustness and accurateness of the recognition algorithm on real images from ports.

Lin Cao, Zhigang Gai, Enxiao Liu, Hao Gao, Hui Li, Lei Yang, Heng Li

Through Wall Human Being Detection Based on Stacked Denoising Auto-encoder Algorithm

The application of ultra-wideband radar in the detection of through wall human being has been relatively mature. In this paper, the algorithm of Stacked Denoising Auto-encoder (SDAE) is applied to identify and classify the through wall human being status. The unsupervised learning method is used to train the autoencoder network in order to obtain more abstract feature of the original data, and then add a classifier at the end of the network. Use the supervised learning method to fine-tuning the network to get the optimization of the model. Finally, on the network model for testing. Experimental results showed that the Stacked Denoising Auto-encoder deep network can effectively classify and identify the through wall human being status.

Wei Wang, Yu Jiang, Dan Wang

A Novel User Preference Prediction Model Based on Local User Interaction Network Topology

As people’s decisions are influenced by their social relationships, social networks have been widely applied in user behavior analysis, preference prediction and recommendation. However, static social relationship in a network alone is insufficient to model interpersonal influence and predict user preferences. In this paper, we propose a local user interaction network topology (LUINT) model to calculate the social influence between neighbors, which takes into account three types of user interactions: “at” action, comment, and re-tweet. Moreover, we design and adopt a shortest path with maximum propagation (SPWMP) algorithm to model the influence propagation within the network. To evaluate our approach, experiments on data set KDD Cup 2012, Track 1 are conducted. The results indicate that the proposed model significantly outperforms the other benchmark methods in predicting preference of the users.

Siqing You, Li Zhou, Yan Liu, Hongjie Liu, Fei Xue

Anomaly Detection Based on Kernel Principal Component and Principal Component Analysis

Nowadays, behind wall human detection based on UWB radar signal, which it had a strong anti-jamming performance, was an important problem. In this setting, principal component analysis (PCA) as an anomaly detection method was used, but PCA could only deal with linear data. Thus, we introduced the kernel principal component analysis (KPCA) for performing a nonlinear form of principal component analysis (PCA). We obtained the different state data based on UWB radar signal for the behind wall human detection. These data were used as training and testing data to calculate the squared prediction error (SPE) values that detect anomalies. The experimental results showed that the introduced approach of KPCA effectively captured the nonlinear relationship in the process data and showed superior process monitoring performance compared to linear PCA.

Wei Wang, Min Zhang, Dan Wang, Yu Jiang, Yuliang Li, Hongda Wu

Evaluation on the Cross-Domain Cloud Databases

The cross-domain ground-based cloud classification is of great significance in meteorological research, and there is no such study in this field to our knowledge. In this paper, we first introduce several representative classification methods (BoW model, LBP and CLBP), including their motivations and feature representations. Then we make an evaluation of these three methods on two cross-domain cloud databases (the CAS and CAA databases). Finally, experimental results show that it is essential to make further research on the issue.

Zhong Zhang, Donghong Li, Wen Xiao, Shuang Liu

Evaluation Hand-Craft Features for Person Re-identification

Person re-identification obtains a major concern from researchers owing to its extensive applications and many challenges. Feature extraction is the first step for person re-identification, and a robust feature can promote the performance. In this paper, we mainly introduce channel-based and region-based feature representation methods and evaluate several representative features that combine the two above-mentioned methods on the VIPeR database.

Zhong Zhang, Meiyan Huang, Shuang Liu, Tariq S. Durrani

Target Recognition Method for High Resolution SAR Images Based on Improved Convolutional Neural Network

Deep Convolutional Neural Network (CNN) has obtained state-of-the-art accuracy in many image recognition tasks. It can learn hierarchical features from massive training data automatically. Since the number of SAR images is limited, using traditional CNN in SAR target recognition will yield severe overfitting. This paper proposes an improved CNN algorithm for high resolution SAR image target recognition. The CNN algorithm is trained by images with target rotation, target translation and random noise in target. With these training data, the system should be more robust and insensitive to these target transformations. During the training, a few strategies such as L2 regularization, batch normalization and dropout are investigated to restrain overfitting. Experimental results on Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset show that the proposed method could achieve high accuracy and be more robust.

Tongyu Zhu, Yicheng Jiang

A New Method of Moving Target Detection Based on OFDM Signal in Radar System

In recent years, with the rapid development of MIMO technology, the transmission efficiency of OFDM signal in radar system has been greatly increased, and OFDM radar has been widely studied with the good performance of OFDM signal ambiguity function. Based on the analysis of the OFDM signal frame format, this paper expounds the feasibility to detect the moving target. In this paper, we will analyze the resolution performance of the OFDM-base signal, then propose an applicable method to detect moving target based on the established echo model, and finally the simulation results and correlation analysis will be given.

Bin Zhao, Bin Wang, Yun Zhang, Huilin Mu, Xin Qi

Identification of Direction of Time in Vector Autoregressive Systems Using PC Algorithm

In this paper we study whether it is possible to identify the direction of time in vector autoregressive processes. We prove a result regarding time reversibility of such systems and propose an algorithm to identify the direction of time when the system is not reversible. We first show that it is possible to utilize the PC-algorithm to identify the directed acyclic graph corresponding to a vector autoregressive process. The identified directed acyclic graph is then used to determine the direction of time. We test our proposed algorithm both on simulated data and real data consisting of EEG recordings.

Borzou Alipourfard, Jean X. Gao

Joint User-Centric Overlapped Clustering and Load Balancing in Ultra Dense Networks

With the increase of cell density and explosive growth of data traffic, coordinated multi-point (CoMP) technology can be used to achieve inter-cell interference cancellation and users spectral efficiency (SE) improvement in ultra-dense networks (UDN). Users (UEs) select its cooperative small cells (SCs) according to their traffic needs and channel conditions. In dense deployment scenario with high load, cooperative clusters selected by different UEs may be overlapping, resulting in the emergence of overloaded SCs, that is, the resources of SCs in the selected cooperative cluster may be insufficient and can’t meet the demand of users. In order to solve this problem, we focus on the user-centric clustering and load balancing joint optimization problem. Since a global optimization is not feasible, a distributed two-step load-aware clustering algorithm is proposed. The first step is to propose a low-complexity user-centric overlapping clustering algorithm, which aims to optimize the spectral efficiency of the user. In the second step, a novel re-clustering algorithm is proposed to balance the load across the SCs, which realizes the offloading of highly loaded SCs, further reducing the number of unsatisfied users. The simulation results show that the necessity and superiority of joint CoMP clustering and load balancing algorithm proposed in this paper. Re-clustering algorithm in the second step further reduces the number of unsatisfied users caused by high load with minimal impact on SE.

Rui Tao, Gang Chuai, Weidong Gao

Sense-Through-Foliage Target Detection Based on EMD and UWB Radar Sensor Networks

In this paper, we propose to apply Empirical Mode Decomposition (EMD) approach to detect target hidden in foliage clutter based on data collected by Ultra Wide Band (UWB) radar. The EMD based target detection approach performs well when the radar signal quality is good. However, EMD approach fails to detect target when the radar signal quality is poor. In such case, Rake structure in RSN is applied to combine different radar echoes as preprocessing before EMD to achieve target detection task.

Ganlin Zhao, Qilian Liang

A Comparative Study of Persian Sentiment Analysis Based on Different Feature Combinations

In recent years, the use of internet and correspondingly the number of online reviews, comments and opinions have increased significantly. It is indeed very difficult for humans to read these opinions and classify them accurately. Consequently, there is a need for an automated system to process this big data. In this paper, a novel sentiment analysis framework for Persian language has been proposed. The proposed framework comprises three basic steps: pre-processing, feature extraction, and support vector machine (SVM) based classification. The performance of the proposed framework has been evaluated taking into account different features combinations. The simulation results have revealed that the best performance could be achieved by integrating unigram, bigram, and trigram features.

Kia Dashtipour, Mandar Gogate, Ahsan Adeel, Amir Hussain, Abdulrahman Alqarafi, Tariq Durrani

Satellite Networking Intrusion Detection System Design Based on Deep Learning Method

The satellite communication network intrusion detection system ensures the security of satellite communication by detecting the illegal intrusion in the satellite network. However, because of the complexity of the satellite network and the expensive communication link, many challenges arise while developing a flexible and effective NIDS (Networking Intrusion Detection System) for unforeseen and unpredictable attacks in satellite network. In this paper we propose a flexible and novel satellite network intrusion detection system framework based on based on deep learning technology. We present the satellite NIDS system constitution, and workflow, and analyze the advantages the means can bring.

Jianlong Zhu, ChunFeng Wang

Identification of Abnormal Weather Radar Echo Images Based on Stacked Auto-Encoders

Due to various factors, including climate, hardware failure etc., abnormal radar echoes were brought out, resulting in inconvenience for forecasting and warning applications. In order to improve the efficiency of the anomaly identification in radar echo image, a novel method combining the theory of classical image processing and deep learning was proposed. In the proposed method, firstly, radar echo image was converted to log-polar coordinates for better describing radar echo image rotation; secondly, based on integration projection theory, the radar echo image in the log-polar coordinates was integrated in horizontal and vertical directions respectively to extract the features of abnormal echo images; lastly, deep learning algorithm based on stacked Auto-Encoders was utilized to train and classify the abnormal echo images by the features extracted previously. The experimental results show that recognition rate of the proposed method can reach up to more than 95%, which can successful achieve the goal of screening abnormal radar echo images; also, the computation speed of it is fairly satisfactory.

Ling Yang, Yun Wang, Zhongke Wang, Yang Qi, Yong Li, Zhipeng Yang, Wenle Chen

Bright Band Observation with Weather Radar over Nyingchi in Tibet

Complex terrain around the radar station will seriously block the radar echo. The New Generation Weather Radar Station located in Nyingchi Prefecture is one of the most seriously blocked radar sites in China. Weather radars in Tibet Prefecture play an increasingly important role in the microphysics and dynamic observation of cloud and precipitation. However, the existence of bright band in radar echoes limits the performance of quantitative precipitation estimation (QPE), especially in high altitude area with complex terrain where melting layer is lower and the beam blockage happens frequently. In order to reduce the influence of the bright band on the precipitation estimation, it is necessary to identify the bright band. This paper mainly analyze melting layer characteristics observed with the C-band Chinese New Generation Weather Radar (CINRAD-CD) and Ka-band all solid-state vertical profile radar in Nyingchi Prefecture during the third Tibet Plateau atmospheric science field campaign in 2015. The processing algorithm consists of the following sections: Firstly, based on the volume radar data from CINRAD-CD, the vertical profile of the average reflectivity factor is calculated at the unblocked azimuth. Then, according to the vertical reflectivity factor profile of bright band, the macrophysics parameters such as the top height, the bottom height, the peak height and the bright band thickness of precipitation are calculated. Moreover, for cross validation, the vertical reflectivity factor data of Ka-band radar are extracted, and the correction of attenuated reflectivity factor is firstly carried out with the method of bin-by-bin correction in the groups. Besides, the corresponding macrophysics parameters of the bright band are calculated. Finally, the bright band identification of the two kinds of radar are validated through temperature profile captured with radiosonde at the closest time. Based on the observation data within a month, the following conclusions are drawn: (1) Two radars are able to consistently identify the bright band. (2) The mean height of peak reflectivity factor value in bright band is from ten meters to several hundred meters lower than the height of 0 °C isotherm. (3) Different from other low altitude areas, the bright band peak height of Nyingchi Prefecture is more closer to the height of 0 °C isotherm, and its thickness is smaller. (4) The vertical decline rate of reflectivity factor is larger in the bright band range.

Xu Wang, Jinghong Han, Jianxin He, Yitian Hao, Hua Chen, Yang Qi

Study of the Algorithm for the Classification of Brain Waves

The emotion belongs to higher nervous activity in the Cerebral cortex of human. Now many researchers use BCI in formal analysis, simulation, and phototyping to explore predicted system behavior between the subjective world of emotion and the objective world of the signal. This paper also compares various classifiers of emotion recognition, and then applies two sets of classifiers. The unsupervised classification include DBN, the supervised classification include Bayesclassifier and Fisherclassifier and SVM. The DNB method performed better than SVM in classification accruracy, and the Bayesclassifier is better than Fisherclassifier in run time. DBN has a higher classification accuracy and lower standard deviation, more suitable for EEG emotion recognition.

Xinfei Ma, Zhihong Liu, Tianhao Jiang, Xiaochun Zhang

Research on the Automatic Detection Technology of the Intelligent Substation Relay Protection Vector

This paper introduces the present situation of intelligent substation vector check, and puts forward a protection vector concentrated extract and automatic detection method, including building relevance between bay and logical node of protection vector, building power flow target value and status value database based on the relay protection, reading the status value of relay protection through MMS communication service of station level, and realizing the vector automatic diagnosis based on the target value of power flow.

Yuhao Zhao, Peng Luo, Jiangbo Ren

Research on Secondary Information Standardization Platform of Intelligent Substation Based on Configuration File

Intelligent substation configuration file is an important part in substation construction and operation. At present, due to management and technical irregularity, large numbers of configuration file and version error appeared. Taking the configuration file of intelligent substation as the breakthrough point, this paper analyzes all the links of substation construction, and puts forward the secondary information standardization platform of intelligent substation based on configuration file, which will sort out every key link in the construction process, and focus on the ICD file detection, SCD file version control and other key technologies. The platform improved the standardization of intelligent substation construction. Finally this paper verified the effectiveness of the platform through the engineering example.

Xiaoguang Hao, Qingquan Liu, Yongyi Fang, Peng Luo

Depth Extraction Based on Motion Cue and Defocusing Cue

With the development and popularity of stereo images or videos, the requirement of stereo resource is gradually upgrading. As an economical method to solve the problem of stereo resource scarcity, 2D-to-3D video conversion techniques are paid more and more attentions. How to obtain high quality depth information is the key of 2D-to-3D video conversion. Depth information is usually hidden in several interframe cues or pictorial cues. In this paper, motion cue and defocusing cue are analyzed in detail. In order to compensate the limitations of the two cues, the fusion strategy is presented here. The experimental results show that piecewise linear combination of the two cues can improve the quality of depth map.

Huadong Sun, Xuesong Jin

A Regional Decomposition Based Search Algorithm for UAVs Team

Currently, search in an irregular region is a challenged issue for multi-unmanned aerial vehicles (UAVs) mission. This paper presents a convex decomposition based search algorithm for UAVs team, which incorporates a regional decomposition into the path planning algorithm. In particular, the targeted region is considered as a polygon, which is seamlessly divided into a serial of sub-regions by a well-designed concave polygon convex decomposition algorithm. The simulation results show that, the proposed algorithm can reduce the search time obviously for most scenes.

Xiaoli Liao, Zhentao Liu, Shoufeng Chen, Zhihua Yang

Binocular Calibration of Infrared Cameras

Infrared binocular stereo vision is one of the focuses in the field of computer vision. A design scheme of infrared camera calibration target is proposed in this paper. The infrared calibration target is designed as a checkerboard layout by sticking square metal sheets on a wooden calibration board. The target can be used to calibrate infrared cameras at normal temperature successfully. The experiments show that the calibration accuracy reaches sub-pixel level, and it can solve the problem of complicated calibration process and low precision of infrared cameras.

Jinjing Miao, Ying Tong, Zeng Liu, Kaikai Li, Hengxin Liu, Yajing Wang, Tingting Li, Guanyu Meng

Study of Feature Extraction Algorithms for Epileptic Seizure Prediction Based on SVM

Epilepsy is a common brain disease state, which threatens the safety of patients. So the effective prediction of epilepsy has great significance. To predict the epileptic seizure, energy feature of electroencephalogram (EEG) is extracted by wavelet transformation and power spectral. Then, support vector machine (SVM) is applied to separate the feature data. The research result shows that the energy of frequency band 0.5–8 Hz would rise 2000 s before seizure onset by analyzing inter-ictal and pre-ictal EEG’s wavelet energy. We used relative wavelet energy and SVM to analyze and test 8 patients’ EEG data, and it shows that the algorithm can predict some patients’ seizure onset except a few of patients’ bad behavior. We replace the wavelet with spectral power and use it to extract feature. The predict accuracy is improved by using spectral power and SVM. Comparing to the relative wavelet energy, the result of 6 patients’ test data improved by spectral power.

Guangteng Wu, Zhuoming Li, Yu Zhang, Xuyang Dong, Liang Ye

Toward’s Arabic Multi-modal Sentiment Analysis

In everyday life, people use internet to express and share opinions, facts, and sentiments about products and services. In addition, social media applications such as Facebook, Twitter, WhatsApp, Snapchat etc., have become important information sharing platforms. Apart from these, a collection of product reviews, facts, poll information, etc., is a need for every company or organization ranging from start-ups to big firms and governments. Clearly, it is very challenging to analyse such big data to improve products, services, and satisfy customer requirements. Therefore, it is necessary to automate the evaluation process using advanced sentiment analysis techniques. Most of previous works focused on uni-modal sentiment analysis mainly textual model. In this paper, a novel Arabic multimodal dataset is presented and validated using state-of-the-art support vector machine (SVM) based classification method.

Abdulrahman S. Alqarafi, Ahsan Adeel, Mandar Gogate, Kia Dashitpour, Amir Hussain, Tariq Durrani

Study on Electromagnetic Simulation Methodology for Sea Clutter Based on FDTD Model

By simulating the electromagnetic field over the sea-surface with a high level of precision, the characteristics of sea clutter echo could be effectively analyzed, which could lead to better maritime remote sensing systems. To fulfill this goal, the electromagnetic simulation method of dynamic sea-surface is studied: Firstly, the ocean wave spectrum model is used to reconstruct the 3D coarse sea-surface; then the metrics of electromagnetic parameters are loaded to initiate the Maxwell equations; after that, the equations are differenced to facilitate FDTD method; then the electromagnetic field distribution is achieved by solving the equations, which gives the physically precise parameters of the sea clutter and targets. The simulation experiments showed the effectiveness of this method.

Enxiao Liu, Liang Cao, Lei Yang

A Multilayer Perceptron Neural Network-Based Spectrum Prediction Approach with Gray Decision

In cognitive radio networks (CRNs), spectrum prediction for inferring spectrum availability can help unlicensed users to discover spectrum holes earlier and to improve spectrum utilization more efficiently. Multilayer perceptron (MLP) neural network-based spectrum prediction model can identify the traffic characteristics of the spectrum only using the history data of the spectrum status. We investigate the statistic characteristics of the MLP neural network’s outputs, propose the gray decision to improve the performance of the MLP-base spectrum predictor. We prove that the performance of MLP-base predictor with gray decision will be improved significantly when the spectrum status change frequently.

Jincheng Ge, Yuhua Xu, Dianxiong Liu, Lijun Kong, Xueqiang Chen

Research of H.264/AVC Intra Prediction Mode Fast Decision

Intra prediction is a characteristic in H.264/AVC. The fast decision mode is a significant factor for video coding efficiency in current video coding standard. In this paper, a quickly choose prediction mode method to improve coding efficiency is proposed. According to the characteristics of picture texture, we divide a block with intra 16 × 16 into four sub blocks with intra 8 × 8 using the method. The four sub blocks are transformed into frequency domain. We choose the appropriate intra prediction mode according to the number of zero. The intra 4 × 4 sub blocks mode decision can be obtained by taking advantage of direction relationship. The experimental results show that the algorithm which proposed in this paper can save coding time 30–50% while 0.04 dB reduction of PSNR.

Daxing Qian, Xiangkun Li

Research on Modulation Recognition Algorithm of Secondary Modulation Signal in Satellite Communication

In this paper, we propose a direct modulation recognition algorithm based on decision theory for secondary modulation in satellite communication. The proposed algorithm introduces the instantaneous feature of different signal modulation types in both signal time and frequency domain, which can achieve efficient secondary modulation signal recognition. Recognition procedure and tree classifier design for the proposed algorithm are also discussed in detail. Simulations results show that the proposed algorithm can achieve high recognition probability with relatively low SNR without priori information.

Chuntao Liu, Wei Zhang, Dahai Chen

Outlier Filtering Algorithm for Indoor Pedestrian Walking Direction Estimation

This paper introduces an outlier filtering algorithm to improve the indoor pedestrian walking direction estimation accuracy performance. Our previous proposed RMPCA approach combines rotation matrix (RM) and Principal Component Analysis (PCA) to extract pedestrian walking direction using a smartphone in the trouser pocket. Performance of the RMPCA approach may deteriorate if an irregular leg locomotion occurs or device slides in the pocket. If this situation occurs, it may be detected by the proposed outlier filtering algorithm. Then, walking direction of the current step may be obtained by averaging the walking direction estimations of the adjacent normal walking steps. Experiments show that the proposed outlier filtering algorithm may avoid large estimation errors and improve accuracy performance of RMPCA approach.

Jiaqi Lv, Zhenyu Na, Xin Liu, Tingting Yao, Zhian Deng

Machine Learning and Its Applications in Wireless Communications

Machine Learning (ML) can improve system performance in many fields such as data dining, object tracking, spectrum sensing and indoor positioning. A review on ML was presented in this paper. Firstly, we looked back to the development, definition and classification of ML; secondly, we summarized the basic principle, mathematical formulation and application methods of two classic algorithms named error back-propagation (BP) and clustering; then, we focused on advanced and typical applications of ML in communication systems like cognitive radio networks (CRNs) and positioning system; finally, we concluded that the system performance could be improved by ML technique.

Jiaqi Lv, Zhenyu Na, Xin Liu, Zhian Deng

Sensor Networks


The Two-Way Trusted Authentication Mechanism of the Internet of Things for the Community Pension

With the development of Internet of things, especially the development of wearable devices, the elderly home care services can be realized. The wearable devices can get the real-time position of the aged and effective monitor the elderly physiological health data, and the aged can use the wearable devices communicate with each other. But the existing security mechanisms of the Internet of Things for the community pension cannot protect the key data. To solve the above problem, the paper presents the two-way trusted authentication mechanism for the Internet of Things for the community pension, it can not only achieve the identity authentication which balances efficiency and safety but also realizes the trusted mutual authentication and data transmission, and the mechanism has a higher security. Compared with traditional authentication scheme, the scheme presented in the paper interacts more simply, the proposed scheme is well suitable for using in computationally limited devices for identification such as terminal equipment of Internet of things.

Caiqiu Zhou, Yuwang Yang, Yongjian Wang

Thunder Interference Rejection Method for Frequency Monitor System in HFSWR

High frequency surface wave radar (HFSWR) works in shortwave bands with complex electromagnetic environment, which contains not only a lot of radio communications, but also atmospheric noise, thunder interference and personal interference. Thunder interference of near area has a great influence on frequency monitor system (FMS) in HFSWR and may even lead to target detection failure or formation track failure. The paper researches on thunder interference rejection method and gives a double threshold method in time-frequency domain to detect thunder interference then remove legitimately. The results of experiments by the presented method show that the effect of thunder interference rejection is significant and the method can greatly improve the accuracy of frequency selecting.

Hongzhi Li, Changjun Yu, Bin Zhao

A Localized Critical-Node Detection Algorithm Based on Partial Routing Information in Swarming FANET

In the swarming unmanned aerial vehicles (UAVs) system integrated flying ad-hoc network (FANET), efficient and reliable critical nodes (the nodes whose removal will disconnect the network) detection is an important issue at present. In this paper, we proposed a localized critical nodes detection algorithm based on partial routing information (CNDPR), in which the to-be-detected target nodes require to communicate only with its 1-hop neighbors. The demonstration and simulation results indicate CNDPR has lower transmission overhead and time delay than several other typical algorithms, with a competitive accuracy.

Haojie Jin, Zhihua Yang, Min Su, Xiaohan Qi

Research on the Deployment Algorithm of Distributed Detection Network

In the complex electromagnetic environment, there are large numbers of radio communication nodes and terminals. Research on how to improve the area cover rate has become a research hot-spot in the field. This paper proposes a distributed detection network deployment algorithm to improve the cover rate of the key area and reduces the number of detection nodes. Firstly, a few detection nodes, sufficient to meet the communication connectivity requirement, are pre-delivered and deployed. Secondly, the algorithm locates the key nodes and estimates the key area through self-organizing network and reconnaissance results. Thirdly, the algorithm integrates the detection nodes into the objective function and particle renewal equation of the particle swarm optimization to redeploy the detection nodes. According to simulation results, the proposed algorithm has higher cover rate than other optimization algorithms.

Yu Zhou, Hongjun Wang, Shizhong Li

A Time-Evolving Topology Based Obstacle Avoidance Algorithm for Multi-UAV Formation

During avoidance of obstacles, an Unmanned Aerial Vehicle (UAV) team confronts with varying communication distances and intermittent visibilities among the member nodes, leading to a time-evolving communication topology. In this paper, therefore, we present a time-evolving based avoiding algorithm for a teamed Unmanned Aerial Vehicle (UAV) system in a two-dimension environment with dynamic obstacles. In one snapshot of the time-varying topology, especially, each member node computes out a convex polygon-based hull of the next-step positions set by making distributed consensus with neighbor nodes. With a centralized approach, the team determines the largest convex region by using these obtained convex hulls within a two-dimension geometric space, where each robot will locally compute the optimal parameters for its next proper position within the resulted convex region. From the simulation results, for a dynamic clutter environment, the proposed approach presents obviously less communication overheads, less time cost and scalable with the formation size.

Zhentao Liu, Zhihua Yang, Haifeng Yu

Opportunistic Routing Algorithm Based on Estimator Learning Automata

The mobile ad hoc network has proven its efficient performance for supporting multimedia and real-time applications in wireless network. The opportunistic routing is a kind of promising protocol for utilizing the characteristics of broadcast of MANET. In traditional opportunistic routing algorithm, the periodic update of link qualities has been employed in adjusting the network congestion condition. In this paper, we proposed Dynamic Cooperative Routing using Estimator Algorithm (DCREA). We use estimator learning automata to implement this algorithm so that it can accommodate dynamic network changes. The algorithm has been simulated on OMNET++ platform, and the result has shown that the DCREA outperforms traditional algorithm.

Zhuoran Han, Shenghong Li

A Reinforcement Learning-Based Routing Protocol in VANETs

Vehicular ad hoc networks serves as an important enabling technology for assistant driving and intelligent transportation, it has aroused wide concern since it was proposed. However, due to the dynamic topology and poor link quality of wireless channel in VANETs caused by vehicle movement and obstacles, establishing a reliable multi-hop communication in VANETs is rather challenging. In this paper, we proposed a position-based reinforcement learning routing protocol. The protocol uses Q-learning to evaluate the quality of the neighbor nodes, and thus selects the next-hop node according to the quality of the neighbor nodes and the position of the destination node to maintain the stability and reliability of the links and routing. Through extensive simulation, the effectiveness of the proposed protocol is shown.

Yanglong Sun, Yiming Lin, Yuliang Tang

A Genetic Fuzzy Tree Based Moving Strategy for a Group of Nodes in Heterogeneous WSN

This paper introduces a novel moving strategy for a group of nodes in heterogeneous wireless sensor networks to improve the performance of target tracking. It employs a two-layer fuzzy tree system (FTS) constructed by two fuzzy inference systems (FISs) to decide which group of nodes move and how they move. The first FIS gives a score to each node and selects the group of moving nodes. The second FIS then controls the moving distance of the moving nodes. The Pittsburgh genetic algorithm is used to optimize the whole rule base and data base of the FTS. Simulation results show that the tracking accuracy can be improved after moving of the selected nodes.

Xiaofeng Yu, Xiaoxu Liu, Jie Ren, Jing Liang

High-Frequency Spectrum Analysis and Channel Availability Decision on Sea Surface Environment

This paper measured entire spectrum in the HF environment of two places by an electromagnetic spectrum monitor system. Based on the above measured data, the HF spectrum characteristics of 2–30 MHz band were analyzed: power spectral density (PSD), Time-frequency distribution, The probability distribution of 3D map, etc. The paper analyzed high frequency bands occupancy one the sea with setting different latitude, season and time as control groups. Hence, we confirm the source of interference noise is broadcasting, and the silent frequency band is obtained. Further analyze has proven it has short-time stationary property. At last, the paper defines the channel availability function for evaluating availability of the channel.

Hongbo Li, Shuo Liu, Gaopeng Li, Jian Zhao, Yang Bai

Multi-path Selection Based on Attractor Selection in Heterogeneous Networks

In order to solve the problem of wireless resource scarcity, a novel heterogeneous network of power line carrier and wireless network (IPWN) is proposed. IPWN employs extended attractor selection algorithm (EASA) to select the optimal path from multi-path candidates. EASA is based on the attractor selection algorithm (ASA), which can select the optimal path adaptively and dynamically. Moreover, the delay threshold of the EASA is calculated to reduce the delay and the number of connections. Simulation results show that the IPWN based on EASA with delay threshold is superior to the network employed greedy algorithm. At the same time, IPWN is robust and stable.

Huan Wu, Xiangming Wen, Zhaoming Lu

Localization Scheme with MAP Pre-filter in Wireless Sensor Network Combating Intensive Measurement Noise

Increasing advances in building reliable and efficient wireless sensor network (WSN) provide a promising prospect in the applications of monitoring and localization. However, due to the intensive measurement noise, observations from sensors can be severely deteriorated, rendering most existing localization schemes unattractive. In this paper, we propose a new localization scheme, which can obtain more reliable observations from the deteriorated ones, and improve the localization performance. That is, we design a maximum a posterior (MAP) pre-filter, which can filter out the measurement noise, and derive the more reliable filtered observations. Then such filtered observations will be adopted in the sequential two-phase Bayesian process, which combines the priori estimative results and the current filtered observations to derive the current estimative localization. Numerical simulations validate the new localization scheme, which can indeed obtain a better performance than traditional schemes.

Zhuangkun Wei, Yongjun Zhang, Bin Li, Chenglin Zhao

Energy Efficiency Optimization with CoMP in Homogeneous Network of TD-LTE-A System

Coordinated Multiple Point (CoMP) Transmission/Reception could increase the transmission date rate of cell edge users and extend the cell coverage. Meanwhile, to meet the requirement of green communications, the researchers have studied how to improve the energy efficiency. In this paper, the energy consumption of eNodeB in CoMP is analyzed and the energy efficiency is optimized. Then, the joint optimization of resource allocation, beamforming and power allocation is performed to maximize the energy efficiency in CoMP homogeneous networks. The relationship between system energy efficiency and system spectrum efficiency is also discussed in this paper.

Liqiang Wang, Qi Zhang, Nannan Fu, Jiajun Zhang

Deployment of 3D Wireless Sensors Within Forest Based on Genetic Algorithm

This paper introduces a non-uniform wireless sensor network (WSN) deployment strategy based on genetic algorithms in forest environment. A new fitness function is proposed which emphasizes on WSN’s convergence and connectivity. According to the fitness function, The deployment strategy selects the best topology in mounts of random network development samples. Then, Minimum spanning tree is employed to optimize connectivity and fix the WSN’s partially damaged problem. Simulation shows that the deployment strategy suits for forests with complex terrain and communication obstacles.

Weiwei Cui, Liang Zeng, Qi Li, Yang Zhang, Jing Liang

Target Recognition Based on 3-D Sparse Underwater Sonar Sensor Network

Underwater target recognition is becoming a hot topic nowadays. In this paper, we propose a maximum likelihood automatic target recognition (ML-ATR) algorithm for both non-fluctuating and fluctuating targets. Theoretical analysis illustrates that our underwater ML-ATR method can tremendously reduce the number of physical sensors while maintain in a good performance. Simulations further validate these theoretical results.

Hao Liang, Qilian Liang

Research on the Temperature Sensor Based on the Selective-Filling Birefringent Photonic Crystal Fiber

In this paper, a new type of photonic crystal fiber with birefringence effect is designed based on the selective-filling of high refractive index liquid. By finite element method, the modal effective index of the fundamental modes, phase birefringence and group birefringence of the birefringent photonic crystal fiber were calculated. With increasing temperature, the effective refractive index decreases,and phase birefringence and group birefringence shift to the shorter wavelength. Further, the Sagnac transmission spectra of the birefringent fiber at different temperature were calculated. Finally, a temperature sensor with sensitivity of −5.05 nm/°C is completed.

Jingping Yang, Tingting Han

Positioning and Tracking


Joint Range and DOA Estimation for Near-Field Signals with a Few Snapshots

2-D MUSIC method has been presented to jointly estimate range and DOA of narrowband near field signals. However, this approach is impractical on enormous application situations such as underwater source detection. Sparsity-based IAA are able to work well with few snapshots (even one). Two-dimensional version of IAA is proposed to estimate 2-D range and bearing information of narrowband near-field sources with few snapshots. In the case that snapshots are abundant, both 2-D MUSIC and 2-D IAA do well in estimating range and DOA. However, when it comes to a few snapshots, 2-D IAA performs much better than 2-D MUSIC. Computer simulation results by MATLAB validate the efficacy of 2-D IAA algorithm with few snapshots.

Bo Wang, Zhimin Yao, Deliang Liu, Yunfei Shi

Position Estimation Based on RSS and DOA Path Loss Model

In complex indoor environment, wireless positioning is mainly affected by non-line-of-sight (NLOS) and multipath problem. In our previous work, we use the ray-tracing model to establish a model of time-of-arrival (TOA) and direction-of-arrival (DOA) based on virtual station (VS) to solve this problem. The advantage of this model is converting NLOS problem into line-of-sight (LOS) problem with VS. It also develops a two-step weighted least squares (TSWLS) positioning estimator using the hybrid TOA and DOA values and have high accuracy. However, it did not take into account the loss of the signal during the propagation process. Based on previous models, developing a Gauss-Markov theorem positioning estimator using the hybrid DOA and Received Signal Strength (RSS) values, taking into account the loss of signal in the propagation process because of transmission, reflection and diffraction, and achieved higher accuracy.

Yunfei Shi, Yongsheng Hao, Deliang Liu, Bo Wang

Dynamic Spectrum Access with Uncertain Wireless Environment: A Probabilistic Based Update Approach

This paper investigates the problem of dynamic spectrum access with taking the uncertainty of the wireless environment into consideration. The existing previous works assumed that the wireless environment is static, i.e., the channel states remain unchanged during the transmission period. In this paper, we assume that the channel states vary from slot to slot. We formulate the channel selection problem as a non-cooperative game and then prove it is an exact potential game, which has at least one pure strategy Nash equilibrium. In addition, we propose a probabilistic based update algorithm, in which users update the channel selection probabilities according to their rewards with a certain probability. Simulations demonstrate that the proposed algorithm achieves satisfactory performance.

Yongjun Zhang, Xiaonan Li, Chaoqiong Fan, Bin Li, Chenglin Zhao

A Sliding Approach of 2-D DOA Estimation for Single Vector Hydrophone

The article focuses on the problem of 2-D (two-dimensional) DOA (Direction of Arrival) estimation of a single source in the scenario of far-field using a single vector hydrophone which comprises three orthogonal velocity-sensors plus one spatially co-located pressure sensor. In this proposed approach, a temporal invariance is formed via two time-delayed data sets collected from a vector hydrophone, and the ESPRIT (Estimation of Signal Parameters via Rotational Invariance Techniques) is utilized to estimate the DOA. A sliding method is proposed to process data collected by a single vector hydrophone in a period of time so that the motion trajectory of the target can be determined. Both the theoretical analysis and the results of computer simulation demonstrate that the algorithm is an effective 2-D DOA estimation approach.

Lang Ge, Ke Xu, Jianwei Wan, Yong Chen

A Sliding Window Fusion Location Algorithm Based on WI-FI/PDR

In order to improve the accuracy of indoor localization, this paper presents a fusion positioning algorithm using the sliding window method based on Wi-Fi and PDR. The algorithm can not only provide the user’s initial position accurately, but also correct the position error of the indoor turning points, so it can correct the cumulative error generated by PDR and improve the positioning accuracy. The experiment results show that the average localization error of the proposed algorithm is lower than Wi-Fi fingerprinting approach and PDR approach. At the same time, the error of turning point has been greatly corrected.

Ning-Xin Zhou, Xin-Yue Fan, Peng-Cheng Xia, Fei Zhou

DOA Estimation with Array Antenna Under the Circumstance of Multiple Errors

Direction of arrival (DOA) estimation is an important research direction of the array signal processing in many fields, such as radar, communications, sonar etc. which has very broad application prospects. However, in the processing of spatial spectrum estimation, the array errors including mutual errors and amplitude and phase errors are hard to be ignored, which may cause discrepancies between array manifold and hypothetical model, thus DOA algorithm performance model based on the ideal model decreases, which will affect the actual application of DOA algorithm. Therefore, it is significant to strengthen the stability of spatial spectrum estimation in actual application. They will be discussed in this paper including method of correcting errors under the circumstance that multiple errors exist at the same time. It is mainly about the common inconsistencies errors of amplitude and phase and array elements mutual coupling error, which are combined with MUSIC algorithm of subspace class used in uniform linear arrays (ULAs).

Nanchi Su, Qing Guo, Xiuhong Wang

Analysis on Positioning Accuracy Based on Joint TDOA and FDOA for Single Satellite Passive Location

Single satellite passive location has many advantages and practical applications, but it also has limitations such as the positioning is not accurate and the sample points of track are relatively sparse. Knowing the shortcomings of such single satellite positioning measurements, this paper gives the simulation of a three-point passive location method based on joint Time Difference of Arrival (TDOA) and Frequency Difference of Arrival (FDOA) and analyzes the Geometric Dilution of Precision (GDOP) performances based on positioning error. The simulation results show that this method is able to calculate the position of radiation source with TDOA and FDOA measured at three points. GDOP performances show the relative velocity and position between radiation source and satellite can affect positioning accuracy in the range of TDOA and FDOA estimation error.

Zhenyong Wang, Ming Ma, Dezhi Li, Gongliang Liu, Haibo Lv, Qirui Zhang

An Error Evaluating Factor of Multi-mode GNSS Positioning with Auxiliary Information

To solve the problem of positioning errors and the discontinuity of positioning caused by signal blockage or noise jamming in GNSS system, this paper firstly studies least squares positioning algorithm. Then the research focuses on the positioning principle and the mathematical model of positioning accuracy in different models, namely multi-mode satellite observation fusion positioning, clock bias auxiliary positioning, height auxiliary positioning, clock bias and height auxiliary positioning and the paper proposes an error evaluating factor ERF to assess the precision of positioning. Finally, the comparative trial verifies the effectiveness of positioning algorithm and the matchup of the ERF and the positioning error. The results show that in the case of accurate auxiliary information, the accuracy of positioning with auxiliary information is mainly related to the number of satellites and the geometric distribution of satellites.

Hang Yin, Ming Li, Jiaqi Li

An Epipolar Geometry-Based Approach for Vision-Based Indoor Localization

Indoor positioning is getting more and more attention and research. We propose an epipolar geometry-based method for vision-based indoor localization using images. It needs an image collected in the positon that is aiming to localize. It uses SURF to pick up the feature points and filtrate them to remain good ones and get rid of bad ones. The good feature points are used to match the feature points in the database. (The feature points are selected by the images whose positions are already known). We use the matched feature points to calculate the essential matrix that include the translation information and rotary information. Then we can complete the localization by the relationship between the query image and the images in the database. What’s more we use the feature points to replace the images to build the database aiming to reduce the space and speed up the localization.

Yinan Liu, Lin Ma, Xuedong Wang, Weixiao Meng

Selection of Sensors Number Based on Localization Accuracy in Wireless Sensor Networks

In the application of wireless sensor network (WSN), it is of great significance to minimize the number of sensors without deteriorating the localization accuracy. In this article, the number of sensors is identified by the localization accuracy of a single or multiple objects. Bayesian compressed sensing (BCS) is employed as the localization method, which is motivated by the advantage of BCS such as better performance of reconstruction in noisy case. Based on the spatial sparsity of objects to be located in a WSN (comparing with the number of sensors), the localization problem can be converted into recovering a spare index vector using Bayesian estimation. The proposed method can achieve the localization performance without the prior information of objects number. Besides, the minimal level of the sensor number is obtained which can satisfy the location accuracy. The simulation results show that the number of the sensors can be quantified according to localization accuracy in different size of regions and different number of objects.

Shuai Shao, Chenglin Zhao, Yongjun Zhang

A New Shadow Tracking Method to Locate the Moving Target in SAR Imagery Based on KCF

Shadow detection and tracking (SDT) is the effective method to locate moving targets, which always be shifted or smeared outside the scene, in different images sequence by Synthetic Aperture Radar (SAR). In this process, the detection of shadow is obtained on the first frame image, and the Kernelized Correlation Filter is used to track target among the following SAR images, using the changes between the image sequence. By the experiments and performance analysis, the validity of the proposed algorithm can be demonstrated.

Zhenhua Xu, Yun Zhang, Hongbo Li, Huilin Mu, Yuan Zhuang

Research on Micro-Doppler Feature of Spatial Target

Inverse Synthetic aperture radar (ISAR) is widely used to observe the space moving target, on which the motion of spin, vibration and rotation will introduce the micro-Doppler (m-D) effect, and results in the smear imaging. When the space target has a micro-Doppler effect, it will produce frequency modulation for the radar echo and cause serious interference. In this paper, the micro-spin model is constructed, and the echo of micro-spin scattering is processed respectively by the time-frequency analysis. A new method of eliminating the micro-Doppler effect is proposed to improve the ISAR imaging. By the experiments and performance analysis, the validity of the proposed algorithm is demonstrated.

Ji Zhenyuan, Hu Encheng, Zhang Yun, Jin Hongyan

Long-Term Target Tracking for UAV Based on Correlation Filter

During UAV target tracking, there still exist some issues such as severe deformation, scale variance, occlusion and even fast motion. In this paper, we propose a more stable, real-time and long-term target tracking algorithm based on correlation filter for these problems. Our proposed tracker mainly included the movement and scale transformation module, which can achieves the precise area of target by combining different scale transformation based on multiple position points. In addition, we exploit the keypoint-based method to solve the redetection issue caused by target disappearance in the UAV long-term tracking process, which ensure stability of the entire system. In this paper, we verify our algorithm on the representative UAV data set called UAV123. The experimental results show that our tracker performs superiorly against several traditional methods at speed of 26 frames per second during tracking.

Qiao Xiao, Qinyu Zhang, Boqian Wu, Xiao Han, Xi Wu

A Resource Allocation Scheme with Excellent Energy Efficiency Based on the Channel Matrix Sparse

This paper introduces a C-RAN scenario which is overlapping covered with the macrocell, residential microcells, office microcells under different activeness. Due to the large scare-fading in the urban environment, the signal to interference and noise ratio (SINR) between some offices and the family micro base stations are too small to care. Therefore, some interference between micro base stations and user are not considerable. In order to improve the energy efficiency in the CoMP process, this paper presents selective beamforming with channel matrix sparse algorithm. This algorithm greatly reduces the complexity of matrix inversion calculation during beamforming and improves the energy efficiency of the system. Simulation results show that the proposed algorithm can effectively reduce the energy consumption of the baseband and improve the energy efficiency of the system.

Ximu Zhang, Xiaofeng Liu, Haitao Wang, Zhihui Liu, Min Jia

Joint DOA and Polarization Estimation Based on Multi-polarization Sensitive Array

A joint direction-of-arrival (DOA) and polarization estimation method based on multi-polarization sensitive circle array and joint spectrum in polarization and spatial domains has been investigated. Multi-polarization sensitive array is composed of several elements with different polarizations, which can avoid signal energy loss caused by the polarization mismatch or shelter and can estimate DOA and polarization parameters of incident signal with arbitrary polarization effectively. In addition, this structure can be better applied to conformal antenna. The joint spectrum in polarization and spatial domains is defined by using MUSIC (multiple signal classification) method. The estimation accuracy and resolving power under different SNR (signal-to-noise ratio) and snapshots are investigated to measure the performance of the method based on this structure. The simulation shows good performance for DOA and polarization estimation of single signal, and the polarization discrimination can improve the resolution when two signals arrival in closely direction.

Jian Yang, Tao Chen, Lin Shi, Chen Zhang

MCMC Based Generative Adversarial Networks for Handwritten Numeral Augmentation

In this paper, we propose a novel data augmentation framework for handwritten numerals by incorporating the probabilistic learning and the generative adversarial learning. First, we simply transform numeral images from spatial space into vector space. The Gaussian based Markov probabilistic model is then developed for simulating synthetic numeral vectors given limited handwritten samples. Next, the simulated data are used to pre-train the generative adversarial networks (GANs), which initializes their parameters to fit the general distribution of numeral features. Finally, we adopt the real handwritten numerals to fine-tune the GANs, which greatly increases the authenticity of generated numeral samples. In this case, the outputs of the GANs can be employed to augment original numeral datasets for training the follow-up inference models. Considering that all simulation and augmentation are operated in 1-D vector space, the proposed augmentation framework is more computationally efficient than those based on 2-D images. Extensive experimental results demonstrate that our proposed augmentation framework achieves improved recognition accuracy.

He Zhang, Chunbo Luo, Xingrui Yu, Peng Ren

A Modified Particle Filter for Cooperative Positioning

This paper proposes a modified hybrid cooperative particle filter (MHC-PF) for cooperative positioning in Global Positioning System (GPS)-challenged scenarios, utilizing information from both satellites and terrestrial neighboring GPS receivers. In GPS-challenged scenarios, determination of receivers’ positions is still a challenging task due to radio blockage. In this situation, cooperative positioning can be utilized to improve the ability to estimate position. The proposed MHC-PF involves introducing a modified factor to the likelihood function, and then selecting a value of the modified factor that results in a minimum estimation error through Monte-Carlo strategy in a pre-processing stage. The proposed method is verified by a realistic indoor scenario to demonstrate the accuracy and availability. Simulation results indicate that the proposed MHC-PF provides approximately 2-m horizontal position root mean squared error (RMSE) and significant improvements over the existing method.

Shiwei Tian, Guangxia Li, Zhi Xiong, Weiheng Dai, Rong Xu

Robust Visual Tracking with Incremental Subspace Learning Sparse Model

Sparse representation based trackers have achieved impressive tracking performance in recent years, the utilization of trivial templates could help to improve the trackers’ performance when partial occlusion occurs. In this paper, we propose a novel incremental subspace learning sparse model for robust visual tracking. The proposed model collaboratively exploits the advantages of both sparse representation and the incremental subspace learning by modeling reconstruction errors caused by sparse representation and the eigen subspace representation simultaneously. We also propose a customized APG method for solving the optimization solution. In addition, a robust observation likelihood metric is proposed. Both qualitative and quantitative evaluations over challenging sequences demonstrate that our tracker performs favorably against several state-of-the-art trackers. Furthermore, we indicate the drawbacks of our tracker and analyze the underlying problem.

Hongqing Wang, Tingfa Xu

A Fast Estimation Method for 3-D Acoustic Source Localization

This paper discusses a type of 3-dimentional rapid sound source location method, which can be widely used in underwater or air environment, such as oil and gas exploration, fish characteristics research, remote conferencing and other fields. Delay-and-sum and Fast Direction of Arrival algorithm are discussed for narrowband signal processing. Sound source positioning only need to calculate and display the power intensity of each different angle of incidence, without the need to extract the specific incident signal, so we can directly apply FDOA algorithm. Since the center frequency of the sound signal is much lower than that of radio waves, laser and other signal carriers, the boundary conditions of the narrowband signal are often not satisfied in the actual workplace. Meanwhile, the system only needs the data characteristics of a certain frequency band in most applications. Therefore, this paper studies a fast beamforming and display method for specifying the frequency band and wave velocity, and verifies the validity of the relevant method with the delay-and-sum beamformer.

Jin Chen, Kaikai Li

Multipath-Aided Probabilistic Multi-Hypothesis Tracker for the SFN-Based Passive Radar

Passive radar (PR) system can provide many benefits and advantages in urban area surveillance. Many PRs have been deployed in the single frequency network (SFN). For multitarget tracking in these scenarios, one of the key issue is the measurement-to-target-and-illuminator association. Moreover, since in the urban scenario, the multipath effect is another difficulty should be handled. An new algorithm is proposed by extending the Probabilistic Multi-Hypothesis Tracker (PMHT) to handle the triple uncertainties of association among measurements, illuminators, propagation paths and target states efficiently. The numerical simulation in an urban Long-Term Evolution (LTE)-based PR scenario to track two small unmanned aerial vehicles (UAVs) illustrates the improved performance of the proposed algorithm over the existed algorithms.

Xu Tang, Mingyan Li, Qi Wu, Dayu Huang

Phantom Track Identification for Radar Network Based on Multi-feature Fusion

To combat against surveillance radar network, the electronic countermeasure scheme of phantom track is employed by the cooperation of multiple electronic combat air vehicles. A modified method is presented to enhance the phantom tracks identification performance for radar network in this paper. The temporal-spatial information fusion trick is applied based on Dempster-Shafer evidence theory. The features of range-angle measure errors and power amplifier distortion are analyzed to identify the phantom track. Simulation results prove that the proposed method is feasible and capable of identifying the phantom track accurately.

Yuan Zhao, Ahmed Abdalla Ali, Bin Tang

Speeded Up Visual Tracker with Adaptive Template Updating Method

Tracking an object with limited prior information regarding to its appearance is a challenging problem that attracts much attention. In this paper, we propose a speeded up visual tracker that is not only capable of long-term tracking but also of online tasks. The tracker treats object tracking as a binary classification problem between the object and background information. Usually, little information is available for training in real cases, which makes trackers with pre-defined distance metric to drift. To solve this problem, the proposed tracker adopts distance metric learning to update classifier after every frame for a more robust tracking result. We use dense SIFT feature to describe an object appearance and randomized principle component analysis (RPCA) to reduce the original feature space dimensionality. Additionally, a new partially-updated template library is proposed for a more robust tracking. The experiment results show that the proposed tracker performs preferable comparing to state-of-art trackers.

Shuqiao Sun, Wenjing Kang, Gongliang Liu

Finding Expert Role in Social-Support Online Community

Understanding experts’ roles and behaviors in social networking sites are helpful in designing and implementation of social network systems. Social element of an expert’s role is an important aspect to be investigated that has been overlooked until recently. In this paper, to investigates the social element of experts in social support online community, we proposed a graph based feature selection approach to identify current experts in online communities. The experimental results show the effectiveness of the proposed technique in evaluating user’s expertise in online communities. The proposed technique is simple to implement in comparison to computationally expensive algorithms.

Isma Hamid, Yu Wu, Qamar Nawaz, Muhammad Rauf

Modeling and Analysis of Microchannel Plate for a Highly Dynamic Star Sensor

A microchannel plate (MCP) model of a highly dynamic star sensor is presented in the current paper. The model is developed based on the working principle of the MCP, and it includes the geometrical and compositional parameters of the MCP. An analytical investigation and numerical calculation of the centroiding error are carried out. The simulation results show that the centroiding error is increased with the decrease of the MCP voltage, increase of the channel diameter and the nonuniformity of the channel sampling, and the effect and available method to decrease the centroiding error is increasing the open area ratio of the MCP.

Yan Jin, Yali Wang, Chunbo Jiao

WLAN Indoor Positioning Based on D-LDA Feature Extraction Algorithm

This paper introduces the Direct Linear Discriminant Analysis (D-LDA) algorithm for feature extraction to reduce noise and redundant location information of the access points (APs) signals in wireless LAN (WLAN) indoor positioning system. Feature database is obtained by deploying D-LDA algorithm to extract the low-dimensional and discriminative positioning features from the original WLAN signal database. The dimensionality of the extracted features may be chosen by setting appropriate retained eigenvalues ratio of between-class scatter matrix. Based on the generated feature database, three typical localization algorithms including weighted k-nearest neighbor (WKNN), nearest-neighbor (NN) and maximum likelihood (ML) are carried for real-time positioning and the results are compared. D-LDA feature extraction algorithm obtains the higher accuracy than traditional localization algorithms while reducing the storage and computation cost significantly.

Jianguo Yu, Zhian Deng, Xin Liu, Juan Chen, Zhenyu Na


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