Communications and Networking

JTIDS is the active service Data-Link of the USA and is playing an important role in modern warfare. However, the low throughput of 115 kbps becomes its bottle neck. In this paper, a throughput enhanced JTIDS waveform with max throughput of 1.1 Mbps is proposed. Multi-rate LDPC and GMSK are adopted to achieve the throughput. To prove its advantages, the performance of different waveforms is compared by simulation. The results show that the throughput enhanced JTIDS waveform is excellent.

In this paper, the theories, features, and design methods to the aperture-coupled-patch frequency selective surfaces (FSSs) were discussed. A novel wide bandwidth FSSs and a kind of multi-bands FSSs with reduced geometry were designed in this paper due to the theory we introduced. Based on the FSSs proposed in this paper, a 24-GHz flat lens antenna was designed as an application example to certify the theory. A prototype of lens antenna was fabricated and measured, and measurement results well agree with the calculated ones.

A novel polarization insensitive metasurface for backscattering Radar Cross Section (RCS) reduction is designed and studied. The proposed metasurface consist of carefully arranged unit cells, which enables estimated uniform diffusion of incoming electromagnetic (EM) energy. A theoretical model based on reflect array theory is introduced to demonstrate the operating principle of the metasurface. An over 20 dB RCS reduction characteristics is observed in the vicinity of 9.5 GHz, indicating our metasurface will provide potential applications for future stealth technologies.

In this paper, we focus on the problem of joint direction-of-departure (DOD) and two-dimensional (2D) direction-of-arrival (DOA) estimation in massive multiple-input multiple-output (MIMO) systems. A novel method for angle estimation is proposed with automatic pairing. The method transforms the element space into the beamspace by employing the property of conjugate centrosymmetric array, such that the angle estimation operates only on the real-valued computation. Then, we utilize the real-valued rotational invariance relationships in beamspace to estimate DOD and 2D DOA in a fresh fashion. Numerical results show that the proposed algorithm provides reduced computational complexity without the loss of estimation accuracy owing to real-valued processing, automatic pairing and computation dimension reduction in massive MIMO systems.

The Internet of things (IoT) technology plays an important role in shipping, vessel tracking, marine engineering and other fields. The space-based Internet of things (S-IoT) is an extension of the IoT in the space field. It is the integration of satellite communications and emerging IoT technology, which will greatly promote the development of the earth integrated network. In this paper, a new non-orthogonal multi-carrier modulation scheme is designed for the machine-to-machine (M2M) communication system to make it applied to space-based networking. This scheme can effectively improve the transmission rate and reduce the sensitivity to frequency offset, so it is suitable for a wide range of data communication environment. The simulation results indicate that the scheme proposed can effectively restrain inter-carrier interference (ICI) caused by non-orthogonal subcarriers, and realize the high speed data transmission rate, which provides a new way for information collection and ship monitoring.

Satellite navigation spoofing technology induces the victim receivers to capture and track the forged navigation signal, so that the receivers work out the spoofed position and time. This paper presents a novel GPS spoofing method based on modifying navigation message, modify the handover word, spoof the calculated pseudo ranges and the satellite positions, then spoof the positioning result of receiver. The influence of the spoofing method on GPS receiver have been simulated, the results show that the proposed method has the approximate linear relationship with the eastern and northern spoofed distance, but has nonlinear relationship with the up spoofed distance. It has great significance to airspace supervision and defense.

Direct sequence spread spectrum (DSSS) system needs some anti-jam algorithms for communication when strong interference exists. Both Normalized least mean square (NLMS) algorithm in time domain and anti-jam algorithm based on FFT in frequency domain are widely used for the excellent performance and small hardware costs. This paper implemented the two algorithms on FPGA and researched their system performances and hardware costs, finally some useful guides for later system design were given.

The potential performance gains promised by massive multi-input and multi-output (MIMO) rely heavily on the access to accurate channel state information (CSI), which are difficult to obtain in practice when channel coherence time is short and the number of mobile users is huge. Therefore, a critical question is how to make the system perform well with imperfect CSI. Rateless codes with adaptive code-rates can free the system from the accurate CSI requirements and guarantee it to approach the maximum achievable rate (MAR) as well as improve the achieved-rate over that based on the fixed-rate codes. In this paper, a recently proposed family of rateless codes, called spinal codes, will be involved in massive MIMO transmission scheme, which in general approaches to the MAR with sufficiently large encoding block-size. In addition, multi-level puncturing and dynamic block-size allocation (MPDBA) techniques are proposed, where the block-sizes are determined by user MAR to curb the average retransmission delay for successfully decoding the messages, which further enhancing the system retransmission efficiency. Multi-level puncturing, which is MAR dependent, limits the gap between the system MAR and the related achieved-rate. Theoretical analysis are provided to demonstrate that spinal codes with MPDBA can guarantee the system retransmission efficiency as well as achieved-rate. Numerical simulation results are presented to demonstrate these benefits.

In this paper, we investigate the topology design to balance the network cost and connectivity, which are two important metrics to guide the design of network topology in ad hoc networks. To this end, we focus on how to construct the network topology, which has the minimum network cost subject to a connectivity constraint. A new topology metric for each link, called connectivity-cost-ratio, is defined as the ratio of the connectivity contribution to the link cost. Then, a heuristic algorithm, low-cost topology design with connectivity constraint (LCTDCC), is proposed to switch off the links, which have small value of connectivity-cost-ratio, i.e., large cost but small contributions on connectivity. Some cost functions are also devised for various network applications. Simulation results validate the efficiency of our proposed algorithm.

To improve the spectrum efficiency and alleviate scarcity, ultra-narrow band (UNB) technique is proposed with high bandwidth efficiency and low bit error rate (BER). In this paper, the waveform design schemes, which are sine amplitude modulation (AM-sine), dual-frequency amplitude modulation (DFAM) and constant modulus dual-frequency (CMDF) modulation for wireless communication networks employing UNB technique, are proposed. We investigate the Euclidean distance of binary modulated signals for UNB communication under the bandwidth restriction compared to very-minimum waveform difference keying (VWDK). We derive the simplicity to optimize our proposed schemes by introducing sine-like signal. By applying the concavity optimization theory, we get more smooth phase waveform than VWDK. We formulate the optimization problem to minimize the average BER subject to these conditions, one is the Euclidean distance between modulated signals and carrier signal, the other one is the signal energy. Simulation results are provided to show the superiority of our proposed schemes as compared to VWDK.

Device-to-Device (D2D) Communication enables User Equipment (UE) to establish direct link between each other to transmit data, which can improve both the efficiency of spectrum and throughput, has become a key technology in the Fifth Generation (5G) system. However, there still exist many challenges to ensure the D2D communication and the 5G standard hasn’t been released. In order to promote the development of D2D technology and provide a simulation tool for the research of 5G D2D communication, in this work, we present the design of system-level simulation platform for 5G D2D communication according to the guidelines of METIS Project. We introduce several key technologies in the simulation platform, including resource allocation, interference computation, power control, etc. Finally, we give the simulation results and summarize that our 5G D2D communication system-level simulation platform is able to offer rich interface for testing and evaluation of related technologies.

A new joint algorithm is proposed to resolve the contradiction between algorithm complexity and performance in multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system. Using the hierarchical structure of the MIMO-OFDM systems, channel estimation and signal detection are alternately performed iteratively. Firstly, to reduce the complexity of channel estimation algorithm, an improved minimum mean squared error (MMSE) channel estimation algorithm is proposed. Then, zero force-successive interference cancellation (ZF-SIC) and MMSE-SIC are used in the joint algorithm as signal detection algorithms. Simulation results show that the new algorithm can obtain good BER performance under single path QPSK and single path 16 QAM simulation conditions. Compared with the existing joint algorithms, the new algorithm can make full use of system’s space resources and ensure the requirements of algorithm complexity and system performance.

Ultra-wideband (UWB) localization technique has been considered as a promising candidate for short-range positioning applications because of its advantages in terms of accuracy and penetrability. In this paper, backpropagation (BP) neural network is employed to improve the positioning accuracy of indoor environments. Theoretical analysis and simulation results show that the BP-based method outperforms other existing popular positioning algorithms with limited penalty in computational complexity. Therefore, it can be regarded as an alternative scheme for scenarios with the requirement of high position accuracy.

Transmitted reference (TR) system has become an attractive non-coherent ultra-wideband (UWB) communications due to its simple structure, no need for channel estimation, low synchronization requirements, and robustness. In this paper, time-hopping (TH) technology is introduced to the TR-UWB system, in which each frame within the transmitted signal for one symbol is divided into several non-overlapping time slots (or chips). In order to guarantee reliable communications and mitigate multi-access interference (MAI), it is necessary to employ TH sequence with good performance. Therefore, as two categories of classical TH sequences, m and Gold sequences are used to realize multiple access communications. Theoretical analysis and simulation results indicate that the bit error rate (BER) performance of the Gold sequence is better than the m sequence. For the same TH sequence, the BER performance degrades with the increase of number of users. Furthermore, the BER performance can be improved by increasing the number of elements of a TH sequence, at the cost of information transmission rate.

In the ultra-wideband (UWB) communication system, Gaussian monocycle is the most frequently used due to its simplicity. However, in a Gaussian monocycle, the most of signal energy is concentrated in low frequency band, in which direct current components exist. Therefore, it cannot fully meet the U.S. Federal Communication Commission (FCC) on radiation template requirements. Meanwhile, in order to avoid the interference with other wireless systems, good pulse design is particularly important. Accordingly, several pulses were proposed, such as Scholtz’s pulse, Hermite pulse, and spectrum shifted Gaussian waveforms (SSGW) pulse. However, it was shown that coefficient adjustment of SSGW pulse requires too many computations or iterations. In this paper, in order to overcome this drawback, random selection (RS) and Least Square Error (LSE) algorithms are introduced to the SSGW pulse design. Correspondingly, an improved SSGW waveform design is presented. Our analysis and results show that the improved approach has significant flexibility in designing and therefore it can meet the requirements of FCC spectrum mask better.

SCMA is a novel, promising non-orthogonal multiple-access technique which adopts iterative detecting algorithms with affordable complexity. Current multiuser detection algorithms are mostly based on factor graph, which usually has a small number of variable nodes and function nodes and makes the girth of the factor graph small. Because the performance of an iterative detection algorithm based on factor graph is closely related to the minimum cycle length (girth) of the graph, we propose a novel uplink SCMA scheme where independent factor graphs corresponding to different SCMA blocks are connected together by using interleaving technique. Numerical results show the proposed scheme has a substantial gain over current detection algorithm over AWGN channels. Meanwhile, the diversity effect introduced by channel coefficients in different resource elements is also considered. The diversity effect combined with interleaving is analyzed. Simulation results demonstrate interleaving can affect BER performance under some circumstances related to channel coefficients diversity.

Generalized spatial modulation (GSM) activates more transmit antennas than spatial modulation to increase the spectral efficiency. Although the maximum likelihood (ML) detector is able to achieve the optimal performance, its exhaustive search leads to intractable computational complexity. In this paper, we design a detection scheme based on Integer-Forcing (IF) algorithm, which utilize IF receiver to decode the transmitted symbols for all possible antenna combinations, and then compare the Euclidean distances between the detected symbols and the received signals. Finally, the symbol vector with minimum Euclidean distance and the corresponding antenna combination are detected as the decided symbols and transmit antenna combination. Simulation results shows that the designed detection scheme achieves obviously better performance than the ZF and the MMSE detection with relatively lower complexity.

The Link-16 tactical data link is a wireless data broadcasting network using fixed TDMA protocol. However, the fixed TDMA protocol cant adjust the time slot adaptively according to users demand, resulting in waste of network resources. In this paper, two dynamic TDMA protocols for tactical data link is studied, which are designed to meet the transmission requirements of some network nodes to send large quantities of messages abruptly. In the reservation-based dynamic TDMA protocol, dynamic reserved time slots are allocated by the master node according to the real-time level requirements and the time-out degree of the messages. In the contention-based dynamic TDMA protocol, other nodes can compete with the time slot when there is no data transmission requirement in itself fixed time slot. The two dynamic TDMA protocols improves the utilization rate of time slots and increase the throughput of the network. The simulations results show that two dynamic TDMA protocols are able to achieve much higher throughput, lower average delay than the fixed TDMA protocol.

This paper describes an interesting method to address the problem of pilot contamination, which adopts the staggered frame structure. The core idea is that different users in the same cell send pilot symbols in different time intervals, and users who send pilot sequences simultaneously in different cells use orthogonal pilot sequences. Furthermore, two channel estimation methods were utilized, which respectively are the Orthogonal Projection Least Square (OPLS) method and the Subtract Interference Least Square (SILS) method. Both two methods don’t directly estimate the whole channel parameters. Alternatively, they estimate the sectional channel response that is orthogonal to the other users’ channel response. The OPLS method is implemented by orthogonal projection operation, whose complexity is higher. So we proposed the SILS method, which combines signal detection to reduce the computational complexity. The simulation results show the staggered frame structure and the channel estimation methods can solve the pilot contamination effectively.

In this paper, we propose an improved time-domain combined anti-jamming structure applied ahead of DOA estimation in DSSS communication system. It makes full use of the weak correlation of DSSS signals on the premise of the accurate use of the DOA estimation algorithm. Compared with the traditional anti-jamming method used in beam space, it influences much less useful signals’ peak after anti-jamming and it has better resolution. In addition, this method can suppress the interference that has the same arrival direction of the useful signals.

Currently, user-centric ultra-dense network (UUDN) is recognized as a promising candidate to deal with the challenge of very high area throughput density. However, the limited wireless backhaul capability restricts the performance of UUDN and needs further study. In this paper, we propose a score and location-aware distributed (SLD) wireless backhaul routing algorithm to transmit users’ data flexibly and efficiently. We consider channel state information, interference between access points (APs) and load of APs in the algorithm. The joint optimization of load of APs and throughput in backhaul links is formulated as a weighted rate maximization problem and resolved by iterative algorithm. The proposed wireless backhaul routing algorithm balances backhaul tasks on APs in UUDN and has high success rate in finding backhaul paths. Simulation results show the effectiveness of the proposed algorithm.

In this paper, we consider a three-node relay network with energy harvesting (EH). Assuming the EH source equipped the energy queue, and the EH relay has energy and data queues, unlike the conventional half duplex relay, the relay experience link selection at each slot. We design a optimization approach aiming at maximizing the long-term averaged transmission rate under the energy queue and data queue length constraints. Considering the link selection and power allocation, we propose a Lyapunov optimization algorithm to solve the energy causality, then obtain the asymptotically optimality. Without requiring any knowledge of the statistics of energy arrivals and channel states, simulations show our proposed algorithm outperform the greedy algorithm and conventional relay algorithm.

This paper presents an efficient parallel symbol timing architecture for high data rate communications receivers. The presented architecture relies on a modified version of the classic Gardner loop, and it features a “multi-channel pipeline” interpolator that enables the symbol rate to be several times higher than the clock rate of the FPGA, hence maximize the achievable throughput. The presented timing recovery scheme is demonstrated on a Xilinx XC7VX690T FPGA at 150 MHz clock rate together with an ADC at 4.8 GHz sampling rate, for an QPSK data-stream at 600 Msps symbol rate. Also, it is observed the presented scheme occupies only 2% of the logic, storage and computational resources in the targeted FPGA. With minor modifications, our algorithm may be adapted for other Amplitude-Phase modulation constellations such as 8PSK, 16PSK or QAM.

Due to the wide deployment of wireless local area networks (WLANs) and the easy acquirement of received signal strength (RSS), indoor localization based on RSS has attracted considerable attention in both academia and industry. In this paper, we extract the scatter factor from RSS and then propose a novel indoor localization scheme based on location fingerprinting and curve fitting techniques. The scheme is set up in two phases. In the offline phase, we create a fingerprint and apply the curve fitting technique to construct fitted RSS-distance functions in LOS (Line Of Sight) and NLOS (None Line Of Sight) condition, respectively. In online positioning phase, the proposed optimized fingerprinting-based localization algorithm (OFPL) uses trilateration technique to assist the fingerprinting localization in choosing the proper location of the receiver. Through conducting field and extensive experiments, we can draw the conclusion that our proposed algorithm can obtain some improvement in localization accuracy compared with the classical fingerprinting-based localization.

Millimeter wave (mmWave) backhaul networks are emerging as a promising candidate for the 5G mobile network. By exploiting highly directional antennas, the concurrent transmission technology which can greatly improve the network throughput is enabled in the mmWave backhaul communication. However, the existing concurrent transmission scheduling scheme ignores fairness, leading to the situation that some links in good state are always dispatched while some in poor state suffering starvation. In this paper we propose a Fairness-aware Global Scheduling (FAGS) algorithm in which a utility function and a scheduling threshold are designed to maximize the system throughput with the fairness requirements satisfied. And to quantify the impact of the scheduling algorithm on fairness a Jain Index is proposed. Simulations conducted in the 60 GHz band demonstrate the superior performance of our algorithm compared with other existing schemes.

In this letter, we study optimal power allocation for a Non-Orthogonal Multiple Access (NOMA) communication system, where the transmitter transmits superimposed information symbols to two users over fading channel with energy harvesting technology. Our objective is to maximize the long-term time-averaged transmission rate subject to the power constraint of the transmitter. By exploiting Lyapunov optimization scheme, we equivalently transform the non-convex optimization problem into a single time slot optimal problem and solve it by alternative optimization scheme with the help of convex optimization. At the end, simulation results have shown that the proposed optimal scheme outperforms other two compared algorithms and can achieve Lyapunov stability.

Software Defined Network (SDN) provides a solution to design 5G network architectures. The existing 5G network architectures based on SDN have various problems, such as the difficulty in implementing and deploying, the poor scalability, etc. In this paper, we propose SEA (SDN-Based Evolution Architecture for 5G Network). SEA reforms the LTE/EPC system and retains the main service logic of LTE, so that it has excellent service performance. Besides, SEA uses the GTP-enabled SDN switch, which has only 4 MB code, to forward traffic, making it easier to deploy on a large scale. Finally, we implement the SEA demo and LTE contrast systems. Experiments show that the SEA demo and LTE system take the same time to build the bearing. Meanwhile, both of them can respond to the data request of the user equipment (UE) within 30–60 ms. In addition, SEA can recover data path within 6 ms.

Link margin (LM) analysis has a critical importance on designing and using aeronautical communication (AC) systems. Antenna gains are vital to analyze LM, while gains of airborne antenna are affected by position or attitude of aircrafts. To study the relationship between LM and position or attitude of aircrafts, a method of LM analysis is presented based on coordinate transformation. The coordinate is used to be calculated for elevation and azimuth angles, which are associated with antenna gains. The method is validated in typical scenarios, and the result indicates that the LM calculating model is accuracy and practicable.

The down link communication environment of high-speed railway (HSR) is modeled by multi-user Gaussian Z interference channel (GZIC) model in the paper. The sum-capacity and the optimum transmission solution of multi-user GZIC are obtained in the strong interference regime. Based on the optimum solutions in all interference regimes, the multi-dimensional communication scheme is proposed and applied to HSR. Finally, three numerical simulations are done to show that the coverage of base station and the rate of user can increase and the frequency of handover can decrease using multi-dimensional communication scheme.

The multipath bias is a non-ignorable factor that limits the BeiDou navigation satellite system (BDS) to improve positioning accuracy. Due to the relatively stationary geometry, the geostationary earth orbit (GEO) satellites not only have poor orbit accuracy, but also the multipath bias is difficult to eliminate by the existing approaches. In this paper, a new multipath error mitigation algorithm based on the wavelet and 2-fold cross validation methods are proposed, which can adaptive select the optimal decomposition level. The comparison of the proposed technique with the existing technique has been carried out with the simulated data series. In addition, a real date experiment shows that 17% to 57% improvement can be achieved in standard deviation compared with the raw multipath error.

Global navigation satellite systems (GNSS) can implement high-precision navigation and positioning, requiring rapid and accurate signal acquisition under very weak signal conditions. Double block zero padding (DBZP) is an efficient algorithm for unaided weak signal acquisition. Considering the acquisition problem of weak direct sequence spread spectrum continuous phase modulation signal, the subblock combining and zero padding method is studied in detail. To solve the weakness of fixed number of subblock and fixed number of signal samples in each subblock given frequency resolution and Doppler searching range in DBZP, a multi block overlapping zero padding (MBOZP) algorithm is proposed, which combines with the ideas of data subblock overlapping. This algorithm optimizes the combination of data subblock by introducing the data subblock overlapping, which can increase the length of coherent accumulation and improve the performance of acquisition under the determined frequency resolution and Doppler searching range. Compared with the traditional DBZP, the simulation results show that MBOZP can obtain higher acquisition probability at small frequency offset.

Since the code length of a polar code is an exponent of 2 if the Arikan’s kernel is employed, it is hard to construct code that with flexible code length. In this paper, a partially repeated scheme for polar codes is proposed for constructing length flexible codes. And the Gaussian Approximation method is used to analyze the block error rate performance of the code. The simulation results verified the analysis.

In this paper, the performance bound has been analyzed on Hamming-Weight-Analysis (HWA) algorithm. We first introduce the description of the linear block code and the theoretical analysis of the HWA algorithm. According to the theoretical analysis, we build simulation model and analyze the performance of HWA algorithm. HWA algorithm has a good recognition performance under the condition of low code rate and high BER. Finally, the performance bound of HWA algorithm is given based on the simulation results. The results in this paper have been validated through simulation on MATLAB.

Space borne GNSS receivers may not have enough tracked GNSS space vehicles due to the geometry caused by high altitude and limited receiver sensitivity. In many cases, such as real-time orbit determination for communication satellites, it is necessary to refine the position and velocity outputs of a space borne GNSS receiver for improved accuracy and robustness before actually using them. Toward this problem, an efficient algorithm jointly using weighted Runge-Kutta integration and cubic Hermite polynomial interpolation is proposed in this work. Simulations are conducted based on the GNSS data of GRACE-B satellite and LING QIAO satellite, the result of which show the proposed algorithm can effectively eliminate outliers and significantly reduce the root mean square error of GNSS position and velocity outputs.

It is difficult to ensure secure transmissions in wireless networks because of the openness of radio signal. In this paper, a fountain-coding aided symmetrical encryption scheme is proposed to deal with this problem. In the proposed scheme, all source packets are first encrypted with a secret key. Then, all encrypted source packets are encoded with fountain code and next transmitted on wireless channels. Finally, the secret key is encrypted with all the fountain-coded packets the legitimate receiver has received for sharing the secret key between the legitimate users. Due to the independent fading characteristic between the legitimate channel and the wiretap channel, if the eavesdropper fails to correctly receive some fountain-coded packets the legitimate receiver receives, the wireless transmission can be secured under appropriate conditions. Compared with the counterparts, the proposed scheme achieves lower intercept probability of the eavesdropper with little receiver feedback burden under appropriate conditions.

Aiming at the problem of communication blackout in the near-space aviation, a new anti-blackout communication method is proposed based on carrier aggregation of OFDMA and frequency diversity. The plasma sheath covered by the aerocraft is treated as a wireless fading channel. The same message is modulated onto every subcarrier of OFDMA in different frequency band. Then frequency diversity reception is used to improve the robustness of the data link. The analysis and simulation results show that the method could significantly improve the bit error performance of the communication link through the plasma sheath. This research provides an effective and simple way for anti-blackout communications.

In order to detect and track a moving target using an IR-UWB radar in indoor environment, the signal processing system using filters is normally used. Basically, filters cut the clutters off from the received signal based on the pre-defined characteristics of the target or clutters. Therefore, if the target and clutters are clearly distinguished, filters can be useful. However, the positioning range of the radar can be severely limited when the target signal is not distinguished because of the effect of signal attenuation caused by the path loss. This paper presents a radar signal processing method using codebook-based background training model. While the filter based signal processing system predicts the errors, proposed method measures and stores the informations of background components in the radar signal. In this way, the proposed system can distinguish the target and background more accurately. Experimental results in this paper shows that the proposed system is more robust to signal attenuation.

In image acquisition and communication systems on small or micro platforms, such as small satellite or unmanned aerial vehicle platforms, the imaging system can generate huge amount of image data while communication system can only deliver a very small part of them due to the limited communication bandwidth. In this paper, a novel bandwidth adaptive image communication strategy via similarity based auto-selection is designed to select a certain number of most informative images acquired by the imaging system for transmission, where the number of selected images is adaptive to the communication bandwidth. Specifically, the image that is more distinguishing to previously transmitted images measured by the similarity, instead of the instantly acquired image, is selected. Experimental results on simulated image sequence has demonstrated the effectiveness of the proposed bandwidth adaptive image communication algorithm.

In this paper, a novel multistage guided filter based hyperspectral (HS) pansharpening algorithm is presented. The intensity component (INT) from interpolated HS image is generated using adaptive IHS method and the optimization equation is solved to get weight vector at first. Then, the paper proposes a multistage guided filter strategy to extract the spatial detail by using panchromatic image and INT image as a guidance image respectively, which is different from the traditional methods. In this way, the detail information can be obtained in a consistent manner. The obtained spatial details information is finally added into the interpolated HS image to generate fused HS image. Experimental results based on different remote sensing images indicate that the presented approach improves performance in the spatial and spectral aspects.

Mobile visual search attracts an increasing attention in multimedia communication recent years which demands higher performance with less delay. An efficient moving object tracking algorithm based on the correlation filter framework is proposed in this paper aiming at accrute real-time mobile visual search in multimedia surveillance. We employ complementary features including HOG and color attributes for the target appearance representation, and the optimization to solve for both the kernelized correlation filter and the adaptive target response jointly is adopted to counter fast motion, motion blur and occlusion. Besides, a separate scale pyramid filter is applied for accurate scale estimation while being computationally efficient. Moreover, a compressed support vector machine (CSVM) serving as a modifier is employed with a compressed sensing matrix to further boost performance. Finally, extensive experimental results on large-scale benchmark datasets validate that the proposed algorithm outperforms state-of-the-art methods in terms of efficiency, accuracy, and robustness.

In this paper, a multi-objective optimization design methodology of low Earth orbit (LEO) satellite broadband network is proposed. Firstly, the quality of service (QoS) metrics and network stability factor (NFS) are established for the LEO satellite network. Then, a multi-objective optimization model for LEO satellite network design is constructed based on the constraints of permanent Inter-satellite Link (ISL) and QoS metrics. In addition, a constrained multi-objective optimization algorithm is designed by integrating NSGA-II with constraints handling. Finally, the simulated results validate the effectiveness of the proposed method and show that this approach provides a new idea for the optimization deployment of the network architecture.

Most of the existing routing protocols designed for LEO satellite networks assume that links are bi-directional symmetric links, which is in contradiction with appearance of Uni-directional link. Those protocols may decrease their performance or at worst cannot establish any path under Uni-directional links existence. In this paper, we will present an efficient routing protocol for LEO satellite networks with Uni-directional links. However, using Uni-directional link introduces new problems such as detection of link disconnection. In order to solve these problems, we employ the group strategy and parallel computing. Simulation results show that more packets could be delivered than Datagram Routing Algorithm (DRA) with pruning Uni-directional links. It is also shown that average end-to-end delay can be decreased in some extent by using group strategy and parallel computing.

With the rapid growth of novel 360-degree video streaming applications, there has been a strong demand of quality-of-experience (QoE) measurement. For the novel experience provided by the 360-degree video, there still lack of corresponding research and usable evaluation model. In this paper, the user’s QoE during the stalling event for the 360-degree streaming video viewed on the Virtual Reality (VR) Head-Mounted Display (HMD) is obtained for the first time by an elaborately designed subjective experiment. The impact of stalling event on the QoE of 360-degree video streaming is then investigated. We find that there is a significant difference between the QoE during the stalling for the 360-degree video streaming and the traditional video streaming, which indicates that the existing QoE evaluation models are no longer suitable for evaluating the QoE of 360-degree video streaming. This preliminary finding appeals for more researches on modeling the specific QoE of 360-degree video streaming.

As a part of the 10 key enabling technologies for 5G, SDN and NFV bring great influence and inspiration to satellite network architecture. SDN/NFV-enabled satellite network building method in transparent satellite system has been researched; however less attention has been paid to the regenerative process satellite system. In addition, satellite system is a typical restricted system, the theoretical research results and successful technology solutions of the ground network are difficult to be applied directly to the satellite system. In this paper, we study how to build a software defined satellite network based on regenerative process satellite system, how to support the software definition of satellite nodes, and put forward a realizable and efficient approach for building software defined satellite network, on this basis, the application scenario of the software definition satellite network is prospected.

Content caching on the edge of dense networks is an emerging and critical technology to support the thirst for content of mobile users. However, the user mobility imposes additional difficulties on caching design because a moving user may not be able to obtain a whole file from a single small base station (SBS). In this paper, we consider the content caching problem in a dense small cell networks. We proposed a proactive mobility-aware (PMA) caching strategy combined with users mobility prediction. In this strategy, we first predict future locations of mobile users, then optimally cache content at SBSs where mobile users are most likely to access in the future. We evaluate efficacy through simulation and compare our strategy against a commonly used cache strategy. Simulation results of our caching strategy show a considerable improvement on the users cache hit ratio.

Geometric Dilution of Precision (GDOP) represents the magnification positioning error in satellite navigation, smaller GDOP represents high positioning accuracy. The analytic results of relevant methods to derive the minimum of GDOP by geocentric coordinate system cannot be achieved in reality, because it does not think fully about the satellite visibility constrains. This article employs the elevation angle to express the satellite visibility, and on basis of the local Cartesian coordinates coordinate system, the essay derives the minimum of GDOP with constraint of four satellites visible. Based on the information track of Beidou satellite navigation system, the minimum of GDOP is verified by using the STK simulation software.

SDN (Software-Defined Networking) provides a new approach to improve network security. In this paper, we design and implement a security service of transmission channels in SDN, which will efficiently lower the percentage of information leakage on the data plane of SDN networks. The core of the service is forwarding strategies based on multi-connection and time-slot scheduling, which functions on SDN controllers. According to the time-slot strategy, every data flow is transmitted on one path in a network at a certain moment, then in next time-slot it will be transmitted on another path, and so on. The multi-connection strategy allows to transmit data through multiple links at a same time. There is a client-side subsystem deployed in user terminals to process the data to send or receive. The processing of data including splitting and encrypting in application layer, coordinating with the forwarding strategies, reduces probability of the whole data flow being intercepted.

Quasi-cyclic (QC) LDPC codes whose parity-check matrices have diagonal structure play an important role in channel coding of 5G communications. In this paper, we study an algebraic-based method for constructing QC LDPC codes with diagonal structure of parity-check matrices. We first analyze the cycle structure of this class of QC LDPC codes and then divide the diagonal parity-check matrix into two parts, i.e., the diagonal matrix and the non-diagonal matrix. By employing the masking technique, we design the non-diagonal matrix based on prime field and QC LDPC codes with diagonal structure of parity-check matrices are proposed. Numerical results show that the constructed QC LDPC codes perform much better than the WiMAX-LDPC codes.

The impact of redundant paths on the performance of onboard multistage switches is investigated systematically for the first time. A calculation model based on Markov chain for throughput performance of Clos-network switch with finite buffers is proposed and proven to have considerable accuracy. Simulations under various parameters are performed to evaluate the impact of redundant paths on the re-sequencing delay, end-to-end delay, as well as the throughput performances. The conclusions drawn in this study can serve as a theoretical guide in the design of onboard multistage switch fabrics.

With the fast development of mobile Internet and wireless communication technology, especially 4G communication technology widely used, people increasingly rely on a large number of mobile applications (Apps). In this paper, we propose a machine learning method to accomplish the task of mobile App user and server interaction prediction based on mobile Internet traffic. As in the real traffic flow data, which is collected by network traffic monitors from the public network of ISPs, only the connection information between users and servers is recorded, i.e. we only have positive examples and a large set of unlabeled examples. We design a PU learning (Learning from Positive and Unlabeled examples) based method to predict the interaction between mobile users and servers. We use the real traffic flow data from the most popular mobile App in China, i.e. Tencent QQ, as the experimental dataset. Experimental results illustrate that our proposed method is effective.

Mobile data traffic is important for the remote device control in Internet of Things (IoT). Due to heterogeneous usage and subscribed data caps, mobile traffic sharing is attractive for the users. This paper mainly studies how the users share the leftover traffic efficiently. In particular, it presents a framework that allows the users to share their traffic based on WiFi. The framework can collect all the users’ bids, and then the sellers allocate their traffic according to the buyers’ bids. In such scenario, the competition between the buyers exists, so how to bid efficiently is critical for the buyers. This paper models the problem as the non-cooperative game. According to the number of sellers, it considers two different cases. The existence of the Nash Equilibrium in both cases is mathematically proved.

This paper presents an energy efficient aware continuous cell zooming algorithm based on green random cellular heterogeneous networks (HetNet). Firstly, we derive a two-tier Poisson Voronoi Tessellation (PVT) random heterogeneous network model in which the macro base stations (MBS), small-cells base stations (SBS), macro users (MU) and small-cell users (SU) locations are drawn randomly from independent homogeneous Poisson point processes (HPPPs). Secondly, by updating the SUs’ locations in SBSs periodically, the radius of the cells can be adjusted adaptively to achieve cell zooming. The performance of this work is examined under different user densities and ratios compared with reference algorithm. Numerical evaluations show that our proposed algorithm can significantly decrease system energy consumption and improve energy efficient.

Multi-user multiple-input multiple-output (MU-MIMO) has been adopted as a key enabling technique to achieve the capacity demand in 4G wireless networks. However, there are still some problems existing in the frequency division duplex (FDD) MU-MIMO system, such as the channel quality indicator (CQI) mismatch problem, large uplink feedback, low pairing probability of MU communication. In this paper, we exploit a MU-MIMO scheme in FDD assisted by device-to-device (D2D) technique to enhance the conventional LTE network. The proposed scheme could not only solve the above problems in conventional MU-MIMO systems, but also achieve significant performance improvement than conventional MU-MIMO schemes. Since the user pairing process is done at the user side, the feedback of the proposed scheme is reduced dramatically compared with the conventional scheme. Simulation results show that the proposed D2D assisted MU-MIMO scheme has clear superiority in terms of throughput over conventional MU-MIMO scheme in LTE networks. Because with D2D assisted MU-MIMO, the proposed scheme tackles the CQI mismatch problem and increases the multi-user pairing probability to enhance the overall throughput.

Efficient resource management to improve the throughput in large-scale cluster has become a research focus with the rapid development of applications of Big Data. YARN (Yet Another Resource Negotiator), as the new generation of resource management system in Hadoop, is more efficient in resource utilization and capable of handling more kinds of workload than previous systems. Due to the fact that a task usually occupies more resources than it actually uses during some stage of its life cycle, a relevant amount of resource is idle and can not be allocated to satisfy the requirements of pending tasks. In order to address the deficiencies of resource allocation in YARN, this paper presents a high concurrent elastic resource allocation strategy named Ballon, which can dynamically adjust the configured resource of a node depending on the actual resource utilization of the node. Moreover, Ballon classifies resource requests of applications into different types. Consequently the elastic resources can be allocated to proper request. Our experiments demonstrate that Ballon cluster can reduce the average execution time of application by at least 10% in most MapReduce application and can increase the resource utilization of cluster.

As protocols play respective roles to fulfill different communication services, it is important to identify protocols before analyzing and managing the system. In the past decade, there have been a lot of researches on protocol identification using machine learning methods, which achieve promising results. However, the features of protocol used for identification mainly rely on engineering skill and domain expertise, which may not be available for the complicated wireless communication systems, such as encryption-based systems. In this paper, we propose an unsupervised-based learning method to make the feature extraction more intelligently and automatically. We first review the limitation of the traditional identification methods, especially the part of feature extraction. After that, an unsupervised deep learning based method, autoencoder, is proposed for automatically extracting the features of the original protocol data. Then, we construct the identification model based on the extracted features and a Support Vector Machine based classifier. Finally, experimental results show the effectiveness of the proposed method.

To ensure the safety of data transmission in SDN network, a practical approach is to forward data by time division in multiple reachable paths. Considering multiple data transmission processes between the sender and the receiver based on the mechanism above, the overlap of the paths is inevitable, which may make the utilization rate of some switches or critical paths too high and other switches are relatively idle, then the transmission efficiency would be too low. This paper put forward a path selection algorithm based on graph-cut to solve the problem. Also, taking switch weight under consideration. In addition, effectiveness is taken into account. Considering to the large scale of actual networks and uneven occupancy rate of switches, this algorithm reflects its advantage.

Due to dense and random deployment of dense heterogeneous cellular networks (HetNets), the systems are more susceptible to channel estimation errors, which effect secure and reliable transmission. To solve this problem, we propose a secure and reliable transmission scheme for dense HetNets based on secure Energy Efficiency (EE) Optimization. Firstly, the system model with channel estimation error is established. Then, transmission threshold selection algorithm is designed to maximize secure EE, and emission control is achieved by comparing the receiving signal-to-interference-plus-noise ratio (SINR) with the transmission threshold. Finally, secure EE constrained by the connection and secrecy probabilities is derived. Numerical results verify that the transmission scheme can increase secure EE by at least 50%.