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Über dieses Buch

The two-volume set LNICST 236-237 constitutes the post-conference proceedings of the 12th EAI International Conference on Communications and Networking, ChinaCom 2017, held in Xi’an, China, in September 2017. The total of 112 contributions presented in these volumes are carefully reviewed and selected from 178 submissions. The papers are organized in topical sections on wireless communications and networking, satellite and space communications and networking, big data network track, multimedia communications and smart networking, signal processing and communications, network and information security, advances and trends of V2X networks.

Inhaltsverzeichnis

Frontmatter

Multimedia Communications and Smart Networking

Frontmatter

WSN Routing Algorithm Based on Energy Approximation Strategy

In the routing protocol of wireless sensor networks, the traditional LEACH algorithm is too random, and the cluster head selection of it is not ideal. To solve this problem, it proposes a WSN routing algorithm based on energy approximation strategy. It chooses a series of nodes with high energy and high density to form cluster candidate clusters, and then selects the farthest node as the cluster head from the candidates by using the energy approximation strategy. The algorithm is simple and easy to implement, and the cluster head selection of it is ideal. Using Matlab software for simulation, the results show that it is less energy consuming than the LEACH algorithm, and the lifetime of the whole network is prolonged.

Yuexia Zhang, Hang Chen, Tianrun Gao

SIFT Based Monocular SLAM with GPU Accelerated

With the rapid development of computer vision technology, 3D Reconstruction based on monocular SLAM (Simultaneous Localization and Mapping) has got more and more attention for its simple requirements, low cost, easy to implement, convenient to carry. ORB-SLAM is a kind of monocular SLAM method based on feature point. ORB feature can meet the real-time requirements for SLAM, but it does not have scale invariance. In this paper, we proposed a monocular SIFT-SLAM, in which a SIFT (Scale Invariant Feature Transform) algorithm based on GPU is used to replace the ORB algorithm, to implement 3D Reconstruction. We show the experiment result of SIFT-SLAM in this paper, which gets some improvement.

Tonghui Wang, Guoyun Lv, Shikai Wang, Haili Li, Baicen Lu

Combining Computer Graphics and Feature for 3D Camera Tracking Based on CAD Model

A real-time 3D tracking system based on CAD model is proposed in this paper. The strategy in the tracking process includes both template-based and keypoint-based approaches. Compared with traditional CAD model-based tracking, a more accurate initial camera pose can be provided for the following feature-based operation which can accelerate the convergence of camera pose estimation. Using template-based method reduces the demand for textures of the tracking object to improve the universality of the system. Furthermore, adaptive visual feature extraction within the feature-based tracking is adopted in the experiment, and feature homogenization and other methods is also chosen to enhance the robustness and interference immunity of the system. Finally, the effectiveness and stability of the methods proposed in this paper is verified through the experiment of tracking targets in the image sequence.

Linlin Wang, Guoyun Lv, Ningxin Zhang, Yanggege Yu

Performance Analysis of CBRP, AODV and DSR Routing Protocols in VANETs Based on IDM-IM

Due to multi-lanes, speed limit, buildings around corners and traffic lights, Vehicular Ad Hoc Networks (VANETs) with urban areas especially in intersections have more complicated network topology, resulting in standard flat routing protocols inapplicable in VANETs. Theoretically hierarchy based routing protocol such as CBRP (Clustering Based Routing Protocol) can achieve better performance in VANETs. To the best of our knowledge, there is no literature reporting network performance tests on CBRP in VANETs. Existing Network Simulator (NS) does not contain CBRP, therefore this paper firstly implements CBRP into NS-2.35 and then aims to compare and analyze performance of CBRP against AODV (Ad Hoc On-demand Distance Vector) and DSR (Dynamic Source Routing) in VANETs based on IDM-IM (Intelligent Driver Model with Intersection Management) modeled by VanetMobiSim. Simulation results reveal that CBRP performs well compared to AODV and DSR in terms of delay, packet loss ratio and route costs.

Luqi Wu, Xia Wang

DOA Estimation for Far-Field Sources in Mixed Signals with Gain-Phase Error Array

Most of the super-resolution direction finding algorithms often require the accurate array manifold, but the gain-phase of the channels is often inconsistent in practical applications, which will lead to the estimation performance deterioration. Therefore, a new method for direction of arrival (DOA) estimation of far-field sources in mixed far-field and near-field signals with gain-phase error array is presented. First, fast Fourier transformation (FFT) is performed on the received data, then matrix transformation is used for simplifying the spectrum function, at last, DOA of far-field signals can be acquired by finding the roots of corresponding polynomial. There is no need to calibrate the array, simulations have shown that the proposed algorithm is effective.

Jiaqi Zhen, Yanchao Li

Sparse Reconstruction in Frequency Domain and DOA Estimation for One-Dimensional Wideband Signals

Previous recovery methods in the literature are usually based on grid partition, which will bring about some perturbation to the eventual result. In the paper, a novel idea for one-dimensional wideband signals by sparse reconstruction in frequency domain is put forward. Firstly, Discrete Fourier Transformation (DFT) is performed on the received data. Then the data of the frequency with the most power is expressed by Fourier serious coefficients. On this basis, the optimization functions and corresponding dual problems are solved. After that the support set is calculated, and the primary sources of this frequency and direction of arrival (DOA) can also be acquired. Comparing with the traditional methods, the proposed approach has further improved the estimation accuracy.

Jiaqi Zhen, Yanchao Li

Radar Burst Control Based on Constrained Ordinal Optimization Under Guidance Quality Constraints

Radar burst control has come into use in order to improve the survivability of combat aircraft and ensure operational effectiveness in the increasingly harsh electronic warfare environment. The critical factor in radar burst control is the radar burst timing. In this paper, a novel method is proposed to determine the optimal timing based on constrained ordinal optimization. Taking the combat effectiveness of air-to-air missile as the constraint condition, the constrained ordinal optimization method is applied to the radar burst detection of hybrid control. The optimal burst timing can be selected quickly and efficiently while making the combat effectiveness maximized. Simulation results indicate that the proposed method can significantly improve the searching efficiency of the optimal radar burst timing.

Bo Li, Qingying Li, Daqing Chen

An Overview of CCMANET: Content Centric MANET

Due to CCN has the advantages of content-centric, unstructured, chunk-level and multipath, the Content Centric Mobile Ad-hoc Network (CCMANET) applies the advantages of Content Centric Network (CCN) to Mobile Ad-hoc Network (MANET). The method solves the problems of low efficiency and unstable in transmission, which caused by nodes movement, dynamical changes of topology, limited node capacity, instability of wireless channel. This paper provides an overview of the existing technologies in CCMANET. Firstly, the paper introduces the basic principle and the new features of CCMANET. Secondly, the key techniques, such as caching, routing, mobility management and security are visited. From this, some important remaining challenges are raised.

Yuehua Huo, Weiqiang Fan, Yinlong Liu, Dong Li

A Cooperative Broadcast Algorithm Based on the Successful Broadcasting Ratio and Residual Energy of Neighbor Nodes in Mobile Ad Hoc Networks

In order to suppress the broadcast storm, balance the energy consumption of the nodes and provide certain reliability, we propose a cooperative broadcast algorithm based on the successful broadcasting ratio and residual energy of neighbor nodes (BSRREN). In this algorithm, each node in a network calculates the broadcasting coefficient according to the successful broadcasting ratio and residual energy. Then, the broadcasting coefficient encapsulated in the broadcast packets is exchanged between neighbor nodes. Each node constructs a neighbor information table (NIT) to store the broadcasting coefficient. Each node dynamically selects up to four neighbor nodes which have the highest broadcast coefficients as the forwarding nodes. The addresses of the four forwarding nodes which are designated as the next hop forwarding nodes are encapsulated in the broadcast packet headers. The transmissions of each node are randomly delayed to reduce the probability of channel contention and message collision. The simulation results show the BSRREN algorithm has lower forwarding node ratio and higher network lifetime, which indicates the algorithm can effectively suppress broadcast storm and balance the energy consumption.

Yichen Deng, Yanping Yu, Zhengqing Yan

Signal Processing for Communications

Frontmatter

Joint User Association and ABS for Energy-Efficient eICIC in Heterogeneous Cellular Network

In the work, we design a novel EE-eICIC algorithm to deal with determining the amount of almost blank subframes (ABS) and user should associate with pico or macro from energy efficiency perspective. Using a generalized fractional programming theory and the convex programming, we propose an iterative and relaxed-rounding algorithm to deal with the problem. Numerical experiments show that the proposed EE-eICIC method can obtain superior performance comparing with state-of-the-art algorithms in terms of energy efficiency of system.

Jie Zheng, Ling Gao, Hai Wang, Jinping Niu, Xiaoya Li, Jie Ren

Transmissions and Network Management of Multiple 100 GB/s Based on Stacking Technology

We have previously proposed and implemented a small form factor and low cost 100G optical transmission system using inverse-multiplexing technology and MLD (Multiplex-Lane Distribution) mechanism [1]. Based on this 100G system, we will further implement a transmission and network management system for multiple 100G application via stacking technology. This technology can incrementally realize the standard 100G OTN or 100G Ethernet capacity expansion with a centralized network element management at one node. The stacking system contains both network management port stacking and optical wavelength stacking. Our test results show that we can stack at least four devices with stable performance, which means a maximum transmission capacity of 400G, but with one IP address or one NE (network element) network management. This technology has a significant advantage comparing with a large rack equipment in term of device cost and flexible 100G bandwidth addition, as well as simple management function.

Xin Huang, Kaixiong Zhou, Chaoxiang Shi, Jianxin Chang, Meng Gao

Topology-Transparent Scheduling in Mobile Ad Hoc Networks with Unidirectional Links

In this paper, a novel efficient transmission scheduling algorithm for multihop mobile ad hoc networks (MANETs) with unidirectional links (ULs) is introduced. We propose an algorithm employing topology-transparent scheduling and erasure coding to support throughput guarantee over ULs in multihop MANATs. Our proposed algorithm can work over both unidirectional and bidirectional links, for both unicast and broadcast scenarios. We analytically study the performance of the proposed algorithm and achieve the maximum guaranteed throughput, for both unicast and broadcast scenarios. Simulations show that the proposed algorithm performs better than other topology-transparent algorithms over unidirectional links.

Yiming Liu, Zhi Fu, Mao Yang

Carrier Synchronizator in Nonbinary LDPC Coded Modulation Systems

This paper proposes carrier synchronizator in a nonbinary LDPC and high-order QAM system in order to solve some relevant problems (e.g. Doppler shift, spectrum efficiency etc.) in the satellite communication. The carrier synchronizator is divided into two parts: frequency estimator and phase estimator. The frequency estimator has two steps: single pilot block-based coarse frequency estimation and multiple pilot block-based fine frequency estimation performed by an autocorrelation (AC) operation and a cross-correlation (CC) operation, respectively. Through frequency compensation, the following phase estimator is carried out by the classical maximum likelihood (ML) criterion. Simulation results show that, for a (225, 173) nonbinary LDPC code over GF(16) with a 16-QAM systems, the proposed carrier synchronizator can eliminate large Doppler shift in the presence of random phase offset with low complexity.

Qiang Zhang, Zhong-yang Yu, Baoming Bai

An Assessment Method of Pilot Situation Awareness in Manned/Unmanned-Aerial-Vehicles Team

In manned/unmanned-aerial-vehicles team, the situation awareness level of manned-aerial-vehicle (MAV) pilot affects the pilot’s cognitive state. Evaluating the pilot’s situation awareness level will enhance the cognitive and interactive capabilities of unmanned-aerial-vehicle (UAV) and MAV. This paper proposes an assessment method of pilot’s situation awareness, which is based on attention resource allocation theory and conditional probability cognitive process. Using the presented method, the situation awareness level of pilot could be quantified and evaluated reasonably. Finally the paper simulated the model at different levels of autonomy (LOA) to demonstrate the rationality of the model.

Jun Chen, Qilin Zhang, Xunjie Qiu, Bo Hou

Minimum Interference Beam Selection for Millimeter Wave BeamSpace MIMO System

Millimeter Wave (mmWave) combined with massive multiple-input multiple-output (MIMO) can provide wider bandwidth and higher spectrum efficiency. It has been considered as a key technique for future 5G wireless communications. However, hardware costs and power consumption make traditional MIMO processing impractical in such systems, because a large number of radio frequency (RF) chains are needed. To solve this problem, the beamspace MIMO concept is proposed in mmWave multiuser MIMO (MU-MIMO) systems, which utilizes beam selection algorithm based on the sparsity of beamspace channel to reduce the required RF chains without obvious performance loss. The existing beam selection algorithms mainly select the beam with the strongest gain, but ignore the inter-beam interference and the complexity. Thus, a novel algorithm based on the minimum interference (MI) criterion is proposed. Specifically, the performance of the beams is measured by defining the beamspace signal-to-interference ratio (SIR). When choosing beams, not only the gain of beams but also the interference to other users is considered. The simulation results demonstrate that the proposed algorithm can substantial reduce the complexity while ensuring better system performance.

Dantao Li, Xiaohui Li, Bin Zhou, Yanbin Zhao, Danfeng Meng

An Efficient Algorithm for Constructing Underwater Sensor Barrier

Most existing works on barrier coverage assume that sensors are deployed in a two-dimensional (2D) long thin belt region, where a barrier is a chain of sensors from one end of the region to the other end with overlapping sensing zones of adjacent sensors. However, 2D sensor barrier construction mechanism cannot be directly applied to three-dimensional (3D) sensor barrier construction problem, such as underwater sensor barrier construction, where sensors are finally distributed over a 3D space. In this paper, we investigate how to efficiently construct an underwater sensor barrier with minimum mobile sensors while reducing energy consumption. We first determine the minimum number of sensors needed for an underwater sensor barrier construction. Furthermore, we analyse the relationship between the initial locations of sensors and the optimal location of the underwater sensor barrier, based on which we derive the optimal final locations for all sensors. Finally, we propose an efficient algorithm to move sensors from their initial locations to final locations. Extensive simulations show that, compared with HungarianK approach, the proposed algorithm costs shorter running time and similar maximum movement distance of any one sensor.

Weiqiang Shen, Chuanlin Zhang, Min-Rong Chen, Jinglun Shi, Guo-Qiang Zeng

Distributed Coverage Hole Detection Algorithm Based on Čech Complex

Coverage problem is essential to Wireless Sensor Networks on energy efficient deployment and monitoring. In this paper, we propose a distributed Čech complex algorithm for coverage hole detection in WSNs. Based on our algorithm, each node takes only local information to build Čech sub-complex. Simulations on randomly deployed nodes show that the algorithm achieves a comparable accuracy and a much lower communication cost than a centralized Čech complex construction. Furthermore, it can be combined with distributed Rips complex algorithm to gain an even better performance.

Wang Yuchen, Lu Jialiang, Philippe Martins

An Energy-aware Routing Protocol Based on Network Coding for Wireless Sensor Networks

In this paper, an energy-aware routing protocol based on network coding (NCEAR) is presented for wireless sensor networks which the energy is constrained. First, considering the rate matching problem of data flows, NCEAR adopts the distributed network coding to calculate the transmission cost of nodes, which reduces the energy consumption. In addition, NCEAR is capable of predicting the congestion degree of nodes through the energy consumption speed, thus balancing the network traffic. What’s more, in order to reduce the probability of link failure and the number of routing maintenance, the protocol takes nodes with the minimum residual energy into consideration and sets the minimum threshold. The simulation results show that compared with other protocols, NCEAR can effectively reduce energy consumption of the transmission, balance the network energy and traffic, prolong the network lifetime and improve the throughput.

Panpan Cui, Song Xiao, Lei Li

Detecting Hierarchical and Overlapping Community Structures in Social Networks Using a One-Stage Memetic Algorithm

Detection of hierarchical and overlapping community structures for social networks is crucial in social network analysis. Previous strategies were focused on a two-stage strategy for separately detecting hierarchical and overlapping community structures. This paper develops a one-stage memetic algorithm for concurrently detecting hierarchical and overlapping community structures in social networks, where quality evaluation functions, community capacity, and hierarchical levels are taken into account to increase the solution quality. This algorithm includes a local search scheme to improve the solution searching ability. Through simulation, this algorithm shows pleasing quality.

Chun-Cheng Lin, Der-Jiunn Deng, Jung-Chao Wu, Liang-Yi Lu

Optimal ZF Precoder Under per Antenna Power with Conjugate Beamforming for MU Massive MIMO Systems

In this paper, we deliberate on multiuser massive multiple-input multiple-output (MU-MIMO) system in designing optimal zero forcing (ZF) precoder under per antenna power constraint. MU massive MIMO with non-square matrix is restrained by the large channel matrix dimension, conjugate beamforming maximization approach is developed to align the channel matrix for the optimal ZF precoder. We further introduced complex lattice reduction (CLR) to transform the lattice bases of the channel matrix and shorten the basis vector, thus meliorates the orthogonality of the conjugate beamforming. Simulation results show LR-based optimal ZF precoder outperforms other precoding schemas. The LR-based optimal ZF precoder improved the beamforming for the base station (BS) to focus on the users, thus improving spatial multiplexing gain and diversity order. As BS antennas and users turn large, the sum rate over the subchannels depends on the dominance of users (that is BS antennas to user antennas ratio) for the channel gain. Thus performance of the LR-based precoder schema under per antenna power can help save power in practical massive MIMO implementation.

James Kweku Nkrumah Nyarko, Christian Ango Mbom

Butterfly-Flow-Graph Based MAP Decoding Algorithm for Channel Quality Information in 3GPP-LTE

Channel quality information (CQI) is an essential element of uplink control signaling in Long Term Evolution (LTE) system. According to 3GPP standard, a linear block code based on Reed-Muller (RM) code has been employed for the CQI transmission for error control. In this paper, a low complexity maximum a posteriori probability (MAP) decoding algorithm for CQI decoding is described, which is performed by re-ordering the likelihood values of the received signal and all mapped codewords, and then calculating the probability of 0 and 1 of every transmitted information bit based on a butterfly-flow-graph (BFG). Compared to the standard MAP decoding algorithm, the proposed algorithm can reduce the addition calculation by 35.71% to 72.82% when the number of CQI bit is changing from 4 to 11, and the bit error rate (BER) performance is without degradation.

Qi Li, He Wang, Yunchuan Yang, Bin Yu, Chengjun Sun

Group-Based Layered Scheduling of ADMM Decoding for LDPC Codes

For low-density parity-check (LDPC) codes decoding by alternating direction method of multipliers (ADMM), the layered scheduling sequentially updates the messages of check nodes one by one. Though the layered scheduling can speed up the convergence rates, it may limit the throughput when implementing the ADMM decoder with multi-core systems due to its serial style. To circumvent this problem, a group-based layered scheduling is proposed by updating a group of check node messages at one time. Extensive simulation results for the proposed scheme over two typical LDPC codes with the ADMM penalized decoding algorithm are provided.

Xing-Long Zhang, Meng Niu, Luo-Hui Su, Ke-Pu Song

LUT-Based Efficient Impulse Shaping for Direct Synthesizing Digital Communication Signals at Arbitrary Symbol Rate

In this paper, we present a LUT-based efficient impulse shaping for direct synthesis of digital communication signal at arbitrary symbol rate. Compared with general approaches where sampling clock changes according to the symbol rate thus signal quality degrade as result of a complex analog hardware structure, or involving a fractional interpolation which consumes considerable computational resource, this new approach allows FPGA to synthesis variable high data rata signal with high quality directly at a fixed sampling rate which simplify the hardware structure and saves computational resource consumption. With some little modifications, the presented scheme could be easily adapted to 8PSK, 16QAM and other arbitrary amplitude-phase-modulation constellations. A hardware prototype has been built to verify the presented algorithms. In particular, we have achieved 4.8 Gsps parallel impulse shaping which supports input symbol rate ranging from 100 Ksps to 600 Msps.

Ziyao Liu, Zhijie Wang, Jun Wang, Di Huang, Nangen Zhang

An Adaptive Step-Size Prediction Joint OMP Algorithm for Beam Tracking in Millimeter Wave Systems

For the millimeter wave (mmWave) time-varying system, beamforming poses a formidable challenge for huge power overhead. In this paper, an adaptive step-size prediction joint orthogonal matching pursuit (OMP) algorithm (ASP-OMP), is proposed for beam tracking. With the direction of arrival (DOA) information obtained by OMP algorithm, kalman filter is used to predict the beamforming vector during N time slots to avoid huge sampling loss. In addition, we propose to determine the prediction step-size with outlier identification and eliminate the beam tracking error through data fusion based on Bayesian estimation. The simulation results demonstrate that the proposed algorithm can converge quickly and have a good performance for mmWave beam tracking.

Xu Yang, Xiaohui Li, Bin Zhou, Yanbin Zhao, Ruiyang Yuan

Priority-Based Multi-carrier Access Schemes for Safety Message Transmission in Vehicular Networks

With the explosive growth of vehicles, current vehicular networks, based on CSMA/CA, are unable to guarantee the low latency and high reliability for safety message transmission under heavy traffic condition. In this paper, we propose a Priority-based Multi-carrier Random Access with Carrier Switching (PMRA/CS) scheme, which is designed for OFDMA-based vehicular networks to support massive concurrent access of large number of vehicles. Compared to CSMA/CA, PMRA/CS utilizes a special short detecting frame to resolve the alarm message collision with less cost. Moreover, the scheme provides more opportunities for vehicles to access the channel in one period by allowing the loser of one sub-carrier to switch to another idle one and continue to access contention. Use of vehicle priority assignment makes the proposed strategy more applicable to realistic scenarios. Furthermore, we provide some theoretical analysis of the proposed scheme combined with derived formula derivation. Simulation results are provided to demonstrate the improvements of message sending success rate and average delay reduction of our proposed scheme.

Huichao Wang, Longjiang Li, Fan Wu, Ke Zhang, Supeng Leng

V2V Resource Allocation Schemes for Non-safety Service in Cellular Vehicular Networks

Vehicle-to-vehicle (V2V) communication has been widely considered as a promising approach for delivering messages between vehicles. However, the highly dynamic topology caused by vehicle mobility makes V2V communication unreliable, especially in the case where the SINR at the receiver below a given threshold. To address the problem, we propose a resource allocation scheme for transmission non-safety messages in cellular vehicular networks. In this scheme, the instability of vehicular network topology has been taken into account. Furthermore, to make the SINR at the receiver under given constraints, distance prediction as well as extra resource allocation is adopted in the design of the scheme. Simulation results demonstrate that the proposed scheme greatly improves the wireless resource utilization.

Lei Jiang, Fan Wu, Ke Zhang, Lixiang Ma

Adaptive Slot Assignment for TDMA Based Dynamic Airborne Ad Hoc Networks

The time division multiple access (TDMA) is thought a better choice for mobile ad hoc networks, especially for sparse and dynamic airborne wireless networks, and its efficiency largely depends on the slot scheduling method. Fully taking the dynamic characteristics of the 3-dimensional airborne network into account, we proposed an adaptive slot assignment TDMA (ASA-TDMA) scheme. It allows for changeable traffic load of the nodes due to the network topology dynamics in sparse airborne ad hoc networks. Slot allocation is performed not only when nodes request for time slots to access, but also when real-time load level changes. The sharing algorithm realizes concurrent transmissions to achieve high slot utilization. Furthermore, our scheme can flexibly adjust the schedule strategy to deal with network emergencies such as node failures. Simulations are provided to validate the performance our approach, and the results show its advantages over some known methods.

Yueyan Qian, Mingwu Yao, Liang Zhang

On Low-Pass Phase Noise Mitigation in OFDM System for mmWave Communications

A phase noise (PN) mitigation scheme was proposed for orthogonal frequency division multiplexing (OFDM) in a previous work. The proposed scheme does not require detailed knowledge of PN statistics and can effectively compensate the PN with sufficient number of unknowns. In this paper, we analyze the performance of PN estimation/mitigation using the proposed scheme. It is shown that increasing the number of unknowns reduces the modeling error, yet increases the additive noise. Hence, increasing the number of unknowns increases the computational complexity and can even degrade the estimation performance. It is also shown that the PN spectral shape of the phase-locked-loop (PLL) based oscillator also affects the PN mitigation and that a larger PN may not necessarily degrade the performance of the OFDM system with PN mitigation. Simulations with realistic millimeter-wave (mmWave) PN and channel models are conducted to verify these findings.

Xiaoming Chen, Wei Fan, Anxue Zhang

Network and Information Security

Frontmatter

Secure Algorithm via Hybrid Relaying Scheme and Resource Allocation for OFDM Networks

Due to its high spectrum efficiency, strong ability to resist multipath fading, OFDM networks is widely applied in various wireless communication systems. However, physical layer security is also an important problem in OFDM networks. By using relay nodes, the secrecy outage probability can be reduced since relay nodes could increase freedoms of optimization for the cooperative OFDM networks. By optimizing multiple variables, which includes adaptive hybrid relaying scheme, relay selection, and resource allocation, we propose the secure algorithm which aims at minimizing the secrecy outage probability of multiuser in cooperative OFDM networks. To achieve this goal, we establish an optimization problem including multiple optimization variables. Then, we convert the optimization problem into a graph theory problem. Simulation results show that the secure algorithm can significantly reduce the secrecy outage probability of multiuser in cooperative OFDM networks.

Xianwen Zhou, Pinyi Ren, Qinghe Du

Dynamic Group Behavior Analysis and Its Application in Network Abnormal Behavior Detection

Focus on the difficulty of large-scale network traffic monitoring and analysis, this paper proposed the concepts of Group Behavior Flow model to aggregate traffic packets and perform abnormal behavior detection. Based on the flow model the pivotal traffic metrics can be extracted while the number of flow records are reduced significantly. Secondly, we employ the graph model to capture the traffic feature distribution between different group users. And optical flow analysis methods are proposed to extract the dynamic behavior changing features between different groups and achieve the goal of abnormal behavior detection. The experimental results based on actual traffic traces show that the methods proposed in this paper can capture the traffic features effectually in the current 10 Gbps network environment, and achieve the goal of abnormal behavior detection and abnormal source location, which is very important for traffic management.

Yan Tong, Jian Zhang, Wei Chen, Mingdi Xu, Tao Qin

A Simplifying Logic Approach for Gate Level Information Flow Tracking

With the increase of design scale and complexity, security vulnerabilities residing in hardware designs become hard to detect. Existing functional testing and verification methods cannot guarantee test and verification coverage in design phase. Fortunately, gate level information flow tracking (GLIFT) has been proposed to enforce bit-tight information flow security from the gate level to detect security vulnerabilities and prevent information leakage effectively. However, there is a significant limitation that the inherent high complexity of GLIFT logic causes significant overheads in static verification and physical implementation. In order to address the limitation, we propose a simplified GLIFT method that incorporates more detailed optimization logic routes to reduce its complexity and allow don’t care to simplify original GLIFT logic. Experimental results have demonstrated that the simplified GLIFT method can reduce the design overhand in several gates by sacrificing a fraction of GLIFT precision.

Yu Tai, Wei Hu, Dejun Mu, Baolei Mao, Lantian Guo, Maoyuan Qin

A Cloud-Based Distance Bounding Protocol for RFID Conforming to EPC-C1 G2 Standards

The development and maturation of cloud computing provides a new idea for deploying RFID systems. A Cloud-based RFID system becomes a new promising architecture. It can be offered as a service of cloud computing to individuals and organizations. However, the cloud-based RFID systems are confronted with more special security and privacy threats, especially the untrustworthy cloud provider and insecure backward communications. Unfortunately, most current RFID authentication schemes fail to meet the special security and privacy requirements of cloud-based RFID, i.e. to provide anonymity and confidentiality against the cloud and build secure backend channels. In this paper, we propose a secure distance bounding protocol for a RFID system, which is cloud-based RFID mutual authentication protocol compatible with the mature EPC-C1 G2 standards. It can effectively resist various threats in cloud environment comparing with other cloud-based RFID authentication protocol and reduce the success probability of a Mafia attack and make it lower than the optimal situation $$ (1/2)^{n} $$ in academic circles.

Zhenjiang Dong, Xinluo Wang, Miao Lei, Wei Wang, Hui Li

Research on the Monitoring Method of the Road Communication Network Quality Based on Vehicle Borne Internet of Things

This article proposes a monitoring method of the road communication network quality based on vehicle borne IoT (Internet of Things) by extracting and analyzing the MR (Measurement Report) data from the bus in the vehicle borne IoT to monitor the wireless network quality on key highways and to efficiently and accurately locate and detect the network errors. This method has proven to be accurate and meets the practical demands. It can further enhance the accuracy and timeliness of network evaluation and its impact in tremendous on increasing the stability of the quality of Mobile Telecommunication Networks.

Baihua Ji, Xiao Liu, Tenghui Ke, Rongjie Kuang, Zibin Gao, Daoce Wang

A Negotiation-Based Collision Avoidance Scheme for Autonomous Mobile Robots

Autonomous mobile robots become increasingly more popular in many fields to execute tasks instead of human beings. When multiple autonomous mobile robots coexist in an area and move autonomously, how to avoid collision among them is a critical issue. In this paper, a distributed negotiation-based collision avoidance scheme is proposed. With this scheme, mobile robots negotiate with each other when they are about to collide. Based on the negotiation, the robots make the most appropriate decision to avoid collision, and move forward to their own destinations with the least cost. The effectiveness and the efficiency of the proposed scheme are proved by extensive simulations.

Zhaoxuan Chen, Pin Lv, Siyu Pan, Jia Xu

Intelligent Access Scheme for Internet of Things Supported by 5G Wireless Network

In future Internet of things (IoT) network, some of the prime objectives or demands that need to be addressed are massive data, increased devices, decreased delay and reduced energy cost. To meet these demands, drastic improvements need to be made. This paper integrates 5G network with IoT scenario and presents a massive IoT device access scheme. In our small cell-IoT network, IoT devices share the resource block (RB) with small cell devices in an overlay way. Under this context, we formulate the access problem with the objectives of minimizing network overall energy cost and maximizing the number of accessed IoT devices. By utilizing data mining tool, the massive data generated by the small cell network and IoT devices is highly utilized and IoT devices can access to the available RBs with higher intelligence. In addition, under the support of K-means algorithm, IoT devices are classified into different clusters. We further propose a cluster access method, with which, each cluster is allocated appropriate RB. All the devices within the same cluster share the same RB in a sequence while considering RB’s vacant time. Simulation results show that our solution leads to a satisfactory outcome.

Yingshuan Song, Heli Zhang, Xi Li, Chunsheng Zhu, Hong Ji

Fast Group Paging Algorithm for Large-Scale MTC Systems

Group paging (GP) is an effective way to solve the serious congestion problem. Congestion problem usually is caused by lots of machine-type communication (MTC) devices communicating at the same time. A certain number of MTC devices in each time slot is been activated, and the number of MTC devices can achieve the maximum of resource utilization. First of all, the total number of MTC devices in each time slot should be calculated according to the different new arrivals in each time slot. By making the resources utilization maximum, the optimal number of total MTC devices can be obtained, from which the optimal number of arriving MTC devices in each time slot will be get. To estimate the total number of MTC devices for traffic scattering GP, a Fast Group Paging Algorithm (FGPA) is proposed, which aims to improve the performance of GP under the condition of massive MTC devices. FGPA is an iterative algorithm that converges fast and has low arithmetic complexity. The corresponding simulation results demonstrate that the proposed FGPA requires less number of iterations under the condition of the same estimation results of total number of MTC devices compared with the existing iterative algorithm.

Si Huang, Xiaohui Li, Bin Zhou, Yanbin Zhao, Ruiyang Yuan

A Honeyfarm Data Control Mechanism and Forensic Study

Honeyfarm is a model to deploy honeypots for global network attack monitoring, correlation and forensic analysis. Data control is a fundamental problem in the honeyfarm to protect the Internet from being attacked by compromised honeypots in the honeyfarm, while providing a controlled environment for worm behaviour study. However, this problem is not well addressed in a limited number of existing implementations. This paper presents a honeyfarm system and focuses on the design of a data control mechanism based on Intrusion detection and Data redirection (DOID). Comprehensive experiments including attack event tracing, worm behaviour study and forensic analysis display that DOID is a good tool for attack monitoring and forensic analysis.

Wei Yin, Hongjian Zhou, Chunlei Yang

Environment-Related Information Security Evaluation for Intrusion Detection Systems

The features of actively detection of intrusion detection systems (IDSs) are crucial in cyberspace security evaluation. Most of existing evaluation models are insufficient for selecting proper IDS in varying situations since these methods only base on detection rate and false alarm ratio. The paper proposes an environment-related information security evaluation model for IDSs, and applies the model in a practical IDS evaluation process. Compared to existing ones, the proposed model considers two more factors: background traffic and workload, and thus can achieve a more objective and comprehensive evaluation result for IDSs.

Ran Cheng, Yueming Lu, Jiefu Gan

A Novel Accurate Source Number Estimation Method Based on GBSA-MDL Algorithm

Several classical source number estimation methods have been proposed in the past based on information theoretic criteria such as minimum description length (MDL). However, in most known real applications there is a scenario in which the number of sensors goes to infinity at the same speed as the number of snapshots (general asymptotic case) which yields to a blind performance for the classical MDL and results in an inaccurate source number estimation. Accordingly, in this work, the Galaxy Based Search Algorithm (GBSA) is modified and applied with the MDL criteria in order to optimize and correct the detection of source number under such sample-starving case. Simulation results show that the proposed GBSA-MDL based method gives reliable results compared to several used source number estimation methods.

Taha Bouras, Di He, Fei Wen, Peilin Liu, Wenxian Yu

Communication QoS, Reliability and Modeling

Frontmatter

A Green Load Balancing Algorithm for Dynamic Spatial-Temporal Traffic Distribution in HetNets

With the increasing users demands, the data traffic in the network reveal different characteristics in both spatial and temporal dimensions, bringing severe load imbalance problem. This may impact resource utilization, users experience and system energy efficiency, and then need further investigation. In this paper, we propose a distributed load-balancing algorithm considering this spatial-temporal variation in a two-tier heterogeneous network. Instead of illuminating the spatial-temporal influence, we make use of this characteristic while designing the algorithm, and accordingly switch ON/OFF small cell base stations (SBSs) for improving the energy efficiency. A load factor described with load variance is derived, based on which the problem is formulated as a non-linear integer programming that seeks to minimize a load function. Then a suboptimal solution is obtained by an effective heuristic algorithm. Simulation results show that our proposed algorithm balances the traffic load better and significantly reduces the total energy consumption, compared with conventional load-balancing scheme.

Jichen Jiang, Xi Li, Hong Ji

Research on the Construction of Radio Environment Map (REM) Based on Spatial Interpolation

For the further performance improvement of Cognitive Radio systems, providing accurate or comprehensive information support to Cognitive Radio devices or networks, there is a use of “Radio Environment Map (REM)”, which presents multi-dimensional information of radio environments and scenarios. With the study of Spatial Interpolation, a method of constructing REM is proposed, and the performance of each algorithm is compared. Experiments show that the RMSM algorithm has advantages like high efficiency and low error, which can be used for the construction of REM.

Ran Zi, Jun Chang, Rong Zong, Ruonan Wang, Guiwen Liao

Resource Allocation in OFDM-Based Cognitive Radios Under Proportional Rate Constraint

The objective of this paper is to optimize the power allocation to maximize the total rate of secondary users (SUs) under the SU total transmit power constraint and primary user (PU) interference temperature constraint, a proportional rate constraint is also used to assure that each SU can achieve fairness. The power allocation problem is not a convex optimization problem, which can be converted to a convex optimization problem without introducing auxiliary variables. To reduce the burden of information exchange and computational complexity, PU interference temperature constraint can be decoupled to an average interference constraint. The Lagrangian duality method is used to solve the optimal transmission power. Numerical results show that the proposed algorithm not only improves the rate fairness of each SU, but also guarantees the quality of service (QoS) of PU.

Hongzhi Wang, Yongfei Yan, Mingyue Zhou

Capacity Analysis of Secondary User System in Cognitive MIMO Networks Based on NOMA

Nowadays, 5G puts forward a number of candidate multiple access technologies, among which the non-orthogonal multiple access (NOMA) is attracting more and more attention. Combining cognitive MIMO with NOMA is of great significance to improve the capacity for future mobile communication. Cognitive system includes two kinds of users, which are secondary users (SUs) and primary users (PUs), and the underlay spectrum sharing paradigm needs to consider the interference of the SUs system to the PUs system is below the predetermined threshold. And therefore, in order to reduce interference and improve capacity, we precode firstly at the transmitter. Then SUs were clustered according to the merits of the channel quality and performed power allocation for each cluster. During this process, the mean of the channel matrixs’ trace is used as the dynamic reception weight to enhance the system capacity. Meanwhile, taking the SUs’ quality of service (QoS) and the requirement of successive interference cancelation (SIC) into account. The objective function is NP-hard problem, we need to transform it into system capacity for sub-cluster, and finally using Lagrange function, nonconvex KKT conditions and mathematical induction (MI) to solve the optimal power allocation coefficient, which is between zero and one. The simulation shows that this proposed scheme can improve the capacity obviously compared with the average power allocation.

Han Liao

A Novel Energy Aware Coded Opportunistic Routing for Social Cognitive Radio Networks

As a huge numbers of heterogeneous devices will be connected in social cognitive radio networks (SCRNs), it needs more frequency spectrum. Moreover, dynamic spectrum availability and heterogeneous devices make it more difficult for routing design in SCRNs. Opportunistic routing (OR) can leverage the broadcast nature of wireless channels, and then can enhance network performance. In this work, we propose an energy aware coded OR (ECOR) in SCRNs, which jointly considers energy efficiency and social feature for designing coded OR. In the proposed OR, we exploit a new scheme for candidate selection and use network coding in data transmission between selected nodes in SCRNs. In addition, we propose a game-theoretic approach to decide forwarding candidate set which is based on auction mechanism. The simulation results demonstrate that the ECOR performs better compared with existing routing in SCRNs in terms of hop count and packet delivery ratio.

Shoubai Xiao, Renhao Lu, Xiaoxiong Zhong

Research on Anti PUE Attack Based on CAF Spectrum and Repeated-Game

High imitation of primary user (PU) signal, primary user emulation (PUE) signal is difficulty for discrimination. First, a method based on cross ambiguity function (CAF) is proposed for determining PUE signal. For PUE signal different from PU signal in spatial but same in frequency in one sensing slot, the algorithm with two dimension search is reduced to one dimension search, having no inter-modulation signal influence. Moreover, for defending PUE attack (PUEA), a repeated game between malicious user (MU) and secondary user (SU) is formulated. By introducing credit discipline mechanism, the optimal strategies for both players are investigated. The stability of the strategies is analyzed with replicated dynamic equation, which indicates that the strategies are the final choice no matter what initial strategies they choose. Simulation results demonstrate that the method is effective for discriminating and defending PUEA in terms of lower computation, higher detection probability and greater payoff.

Hong Chang, Yong Li

Multi-modal Transmission Strategies with Obstacle Avoidance for Healthcare Applications

This paper presents a novel energy-efficient MAC Protocol designed for Body Sensor networks (BSN) focusing towards pervasive healthcare applications. BSN nodes are usually attached to the human body to track vital health signs such as body temperature, activity or heart-rate. Unlike traditional wireless sensor networks, the nodes in BSN are not deployed in an adhoc manner. The network connectivity is usually centrally managed and all communications are single-hop. The BSN has to be dependable in order to ensure the availability and reliability of the data received. Hence, it is necessary to reduce energy consumption in order to prolong the operation of the network without frequent outage. It is common to duty cycle the sensor nodes to preserve the battery utilization. However, the communication between the sensing node and receiving node can be interfered by human movement that can lead to energy wastage. In this paper, A Multi-Modal Opportunistic Transmission with Energy Saving (M-MOTES) is proposed. M-MOTES uses the opportunistic transmission approach and the human kinematics to duty-cycling the node. Extensive experiments performed on real hardware show that M-MOTES can reduce the battery power consumption without affecting the packet reliability.

Tiong Hoo Lim

A BP Neural Network Based Self-tuning for QoS Support in AVB Switched Ethernet

To support QoS of time-sensitive services in Ethernet, IEEE has proposed a set of standards for transporting and forwarding real-time content over Ethernet known as Audio Video Bridging (AVB) with bandwidth reservation and priority isolation. AVB traffic is granted highest priority to ensure its transmission while low-priority traffic follows Strict Priority (SP). However, due to restrictions of SP algorithm, low-priority traffic may suffer a problem of starvation. To solve the problem, we propose a BP neural network based self-tuning controller (BPSC) over a probability selector to manage the transmission of best effort (BE) traffic in AVB switched Ethernet. This paper introduces the model of BPSC, followed by an simulation to demonstrate that BPSC could operate effectively and dynamically. The result shows that BPSC not only has the ability to manage the transmission precisely, but also shows both effectiveness and robustness.

Dong Chen, Ang Gao

Optimal Power Splitting in a Full-Duplex Wireless Powered Network with a Bidirectional Relay

This paper studies the optimal power splitting strategy in a full-duplex wireless powered communication network (WPCN). This wireless powered network contains three nodes, which are the access point (AP), the relay node (R) and the user. We divide the communication process into two phases that each one has the same duration time. The AP transmits the energy to the relay node and the user, and the user transmits the information to the relay node and the AP simultaneously in the first phase. In the second phase, R relays the energy to the user and simultaneously decodes the information and forwards the information signal to the AP. We study how R splits its harvested energy into two parts separately for energy harvesting (EH) and information forwarding, respectively, to maximize the achievable information rate from the user to the AP, when a direct link between AP and the user exists or does not. We get the mathematical results of optimal power splitting factor in two models. Numerical results show that the variation trend of the maximum achievable rate with the distance between the AP and R, and the rate with direct link is not always larger than the rate without direct link.

Yingting Liu, Hongwu Yang, Chunman Yan, Li Cong

Advances and Trends of V2X Networks

Frontmatter

Design and Implementation of an Intelligent Shipborne Terminal System

To solve the problem that network services provided by ships can’t distinguish different users and the Quality of Service (QoS) is poor, an intelligent shipborne terminal system which combines advanced positioning technology and wireless communication technology is designed in this paper. The overall design of the system including hardware design and software design is proposed. The test results show that the system can distinguish between different users’ Wi-Fi connection, intelligentize the management of system users, realizes the function of GPS positioning navigation and has a rich local resource storage, which all proved its good application value.

Wenqiu Chen, Rongbin Yao, Jincai Ye, Xin Tang, Xiaohuan Li

A Positioning Method Based on RSSI and Power Spectrum Waveform Distinction

In this paper, we propose a positioning method based on the dual-complex fingerprint, which consists of the Received Signal Strength Indication (RSSI) and the Power Spectrum Waveform (PSW), including three stages. First, generate fingerprint library by data collected offline. For each reference point, RSSI and PSW are both stored in the library. Then make pre-positioning by RSSI fingerprint and the location of reference points. These points will be selected twice to remove the single points away from the others. Final positions are estimated by taking PSW Distinction (PSWD) and RSSI into consideration. In addition, we introduce an idea of evaluating PSWD by the Kullback-Leibler Distance (KLD). The MATLAB simulation results show that, comparing to other algorithms such as KNN and WKNN, the proposed method leads to lower number of observable misestimated points, and approximately 5% improvement in cumulative distribution function (CDF) of position error within 1.3 m.

Yuyang Lin, Zunwen He, Jiang Yu, Yan Zhang

A Network Coding Collaborative Download Scheme for Platoon-Based VANETs

Platoon-based Vehicular Ad-hoc Networks (VANETs) can significantly improve the road capacity and facilitate the potential cooperative communication applications. However, the communication links between platoon-based vehicles and the roadside unit (RSU) are unstable, which decrease the throughput and increase the delay, and cause the infotainment resources cannot be downloaded quickly. In this paper, we propose a collaborative download strategy in platoon-based VANETs to solve the problems. On the basis of RSUs support simultaneous communication with multiple vehicles, when a demand vehicle need to download multimedia files, we use the collaborative download request management mechanism to request other vehicles in the same RSU coverage area to participate in the collaborative download process. Besides, to decrease the download time, we divide the required multimedia files into multiple data packets. After the RSUs encode the data packets via linear network coding, the cooperative vehicles forward the received encoded packets to the demand vehicle. We also research the impact of speed and file size on the performance of cooperative download strategy. The simulation results show that the proposed cooperative download strategy can effectively increase throughput and reduce the downloading completion time when download multimedia files, especially when the size of multimedia files is large and the speed of platoon-based vehicles is fast.

Jincai Ye, Xuewen Huang, Xiaohuan Li, Guan Wang, Rongbin Yao, Xin Tang

Analysis of Conditional Connectivity Based on Two Lanes for VANETs

Conditional connectivity is important for the design of the upper layer communication protocol and the network deployment in different scenarios. This paper analyzes the performance of conditional connectivity with the network topology change by establishing the model of inter-vehicle communication. The paper aims at the two-lane highway scenario for vehicular ad hoc networks (VANETs), considering the factors of communication range, vehicle flow characteristics and moving speed. The main conditional connectivity performance index is the conditional connectivity probability. Based on the simulation, the correctness of the theoretical analysis is verified. We also make an explanation of the simulation results.

Bin Pan, Hao Wu

Optimized Workload Allocation in Vehicular Edge Computing: A Sequential Game Approach

With the development of Vehicle-to-Everything (V2X) communication technologies, Vehicular Edge Computing (VEC) is utilized to speed up the running of vehicular computation workload by deploying VEC servers in close proximity to vehicular terminals. Due to resource limitation of VEC servers, VEC servers are unable to perform a large number of vehicular computation workloads. To improve the performance of VEC servers, we propose a new workload allocation framework where vehicular terminals are divided into Resource Provision Terminals (RPTs) and Resource Demand Terminals (RDTs). In this framework, we design an optimized workload allocation strategy through a sequential Stackelberg game. With the sequential Stackelberg game, a VEC server, RDTs, and RPTs achieve an efficient coordination of the workload allocation. The sequential Stackelberg game is proven to reach two sequential Nash Equilibriums. The simulation results validate the efficiency of the optimized workload allocation strategy.

Dongdong Ye, Maoqiang Wu, Jiawen Kang, Rong Yu

Navigation Route Based Stable Clustering for Vehicular Ad Hoc Networks

Due to high mobility of vehicles, stability has been always one of the major concerns of vehicle clustering algorithms. In this paper, we propose a novel clustering algorithm based on the information of route planned by vehicular navigation systems. Including route information into cluster mechanism is not trivial due to two issues: (i) stability is a property of time rather than position, (ii) route diversity may cause high re-clustering overhead at road intersections. To address the first issue, we propose a function to quantitatively calculate the overlapping time among vehicles based on route information, with which a novel clusterhead selection metric is designed. To address the second issue, we design a mechanism of future-clusterhead, which can help avoid message exchanges at intersections. The simulation results show that, compared with similar works, our algorithm can cluster vehicles with higher stability and at the same time lower communication cost.

Zhiwei Yang, Weigang Wu, Yishun Chen, Xiaola Lin, Xiang Chen

A Social-Aware Routing Protocol for Two Different Scenarios in Vehicular Ad-Hoc Network

Vehicular Ad-hoc Network (VANET) has recently attracted wide public attention. A key challenge is to design suitable routing protocols for VANET. In order to get high packet delivery ratio and low end-to-end delay, this paper proposes a social-aware routing protocol based on the “store-carry-forward” strategy, called Tie and Duration Based Routing Protocol (TDRP). To select the best relay node, TDRP takes two social metrics into consideration: community and centrality. We adopt a distributed K-Clique community detection to divide vehicles into different communities, and calculate global and local centralities of vehicles by making full use of strong and weak ties, as well as the duration of historical connections. The ONE simulator is used to evaluate the performance of TDRP and Bubble Rap, a typical social-aware routing protocol. Experimental results show that TDRP outperforms Bubble Rap in both city and highway scenarios in terms of packet delivery ratio and end-to-end delay.

Zhixiao Zhu, Binjie Hu, Haina Song, Xiaotao Liu

Backmatter

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