Current Issue

• • 2019, Vol. 42 No. 2 Published date:28 April 2019 Last issue Next issue

  Papers

  • Policy Estimation Error Analysis for Symmetrical MARL Problem in Communication Resource Scheduling
  • ZHANG Xin-ran, SUN Song-lin
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 1-6. DOI:10.13190/j.jbupt.2018-121
  • Abstract ( 240 )     HTML     　　
  • Considering multi-agent reinforcement learning (MARL) theory in communication resource scheduling scenario, the symmetrical MARL problem was proposed with definitions for three types of symmetry properties and analysis of policy estimation error. The policy estimation error theorem for strong symmetrical MARL was presented. Simulation results based on the admission control problem in wireless system were modeled by MARL, which testify the characteristics of policy estimation error for strong symmetrical MARL problems. It shows that using the MARL sub-problems with low computational complexity to estimate the original MARL problem with high computational complexity only brings small policy estimation error and deterioration of system performance.
  • References | Supplementary Material | Related Articles

  • Signal Strength Localization Algorithm Based on Rank Filter and Fibonacci Tree
  • YU Xiu-wu, XIAO Ren-rong, LIU Yong, GUO Qian, YU Hao
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 7-12. DOI:10.13190/j.jbupt.2018-120
  • Abstract ( 438 )     HTML     　　
  • In order to solve the problem of poor ranging accuracy and robustness of received signal strength indication (RSSI), a signal strength localization algorithm based on rank filter and Fibonacci tree optimization (RF-RSSI-FTO) was proposed. First, the rank filtering method was used to remove the interference of the RSSI value to improve the accuracy and robustness of the ranging. Then, the Fibonacci tree optimization algorithm was introduced to optimize the global and local search of the positioning coordinates to reduce the positioning error. Simulation results show that the RF-RSSI-FTO algorithm can effectively improve ranging accuracy and robustness, enhance the global and local search ability, and improve positioning accuracy.
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  • Private Sets Intersection Protocols Based on Cloud Computing
  • ZHANG Jing, LUO Shou-shan, YANG Yi-xian, XIN Yang
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 13-18. DOI:10.13190/j.jbupt.2018-236
  • Abstract ( 502 )     HTML     　　
  • A secure two-party set computation protocol based on cloud server outsourcing was proposed. The protocol solved the problem of the intersection of two sets and realizes the privacy protection of privacy sets of participants with the combination of the point value calculations of polynomial and Boneh encryption system. During protocol execution, the calculation of each participant was completely independent without any form of data interaction. It allows multiple participants to storage their private data to the cloud server independently without having to upload copies multiple times. The correctness, security and performance of protocol was proved, and the result of experimental analysis show that the calculation cost of the protocol is lower.
  • References | Supplementary Material | Related Articles

  • Vertical Handoff Algorithm for Reducing Congestion in Ad Hoc Heterogeneous Network
  • MA Bin, MAO Bu-xuan, XIE Xian-zhong
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 19-24. DOI:10.13190/j.jbupt.2018-145
  • Abstract ( 513 )     HTML     　　
  • The combination of Ad hoc and heterogeneous network with infrastructure was proposed to alleviate network congestion. When the network was not congested, the vehicle terminal used utility function algorithm to select network between the base stations or the access points in order to complete the vertical handoff quickly. When the network was congested, firstly, the Ad hoc was divided into several clusters by clustering algorithm; then, the transition among vehicle states was carried out; finally, the access algorithm was selected according to the vehicle status. Simulation results show that the proposed algorithm reduces the probability of network congestion and improves the system throughput.
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  • Machine Learning-Based Stochastic Task Offloading Algorithm in Mobile-Edge Computing
  • MENG Hao, HUO Ru, GUO Qian-ying, HUANG Tao, LIU Yun-jie
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 25-30. DOI:10.13190/j.jbupt.2018-078
  • Abstract ( 480 )     HTML     　　
  • For mobile-edge computing (MEC), a machine learning-based stochastic task offloading algorithm was proposed. By dividing the task into offloadable components and unoffloadable components, the improved Q learning and deep learning algorithm were used to generate the optimal offloading strategy of stochastic task, which minimized the weighted sum of energy consumption and time delay of the mobile devices. The simulation results show that the proposed algorithm saves the weighted sum of energy consumption and time delay by 38.1%, compared to the local execution algorithm.
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  • A Low Complexity Detection Algorithm Based on the Weight Factors for Spatial Modulation System
  • DING Qing-feng, DING Xu, LIN Zhi-ming
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 31-35. DOI:10.13190/j.jbupt.2018-102
  • Abstract ( 350 )     HTML     　　
  • Aiming at the high complexity of the maximum likelihood detection algorithm for spatial modulation systems, an improved maximum ratio combing algorithm was proposed. In this algorithm, a weighting factor was defined, whose subscript corresponded to the sequence number of transmitting antenna. Then the values of the weighting factor were sorted in descending order, and the antennas corresponding to the first L values were selected to form the antenna candidate set. Assuming that an antenna in the antenna candidate set was activated, the possible transmit signal was calculated by zero forcing algorithm. Maximum likelihood search was performed for all antennas and corresponding estimation symbols in the antenna candidate set. Simulation results show that the proposed algorithm can significantly reduce the complexity of the algorithm on the premise of ensuring the sub-optimal detection performance.
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  • Imaging Hashing Based on Principal Component Analysis
  • ZHAO Shan, LI Yong-si
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 36-41. DOI:10.13190/j.jbupt.2018-116
  • Abstract ( 516 )     HTML     　　
  • A novel image Hashing based on principal component analysis (PCA) was proposed. PCA was introduced to reduce dimension of samples, and the projection matrix was achieved by choosing several eigenvectors which have higher recognition ability. Based on which, the reduced-sample was mapped with locality preserving projection (LPP). Meanwhile, the projection matrix of principal component analysis was randomly rotated to form a series of transformational matrixes. The matrix stitching was adopted to construct the final code projection matrix. Finally, the original samples were projected into the code projection matrix to get a reduced dimensional sample, and the Hashing code was used to achieve the final binary encoding. Experiments show that the proposed method has better stability, lower memory consumption and higher efficiency compared with other traditional methods.
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  • Hybrid Precoding Method Based on Geometric Mean Decomposition for Millimeter Wave Massive MIMO
  • LI Min-zheng, DING Jian
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 42-49. DOI:10.13190/j.jbupt.2018-209
  • Abstract ( 524 )     HTML     　　
  • In millimeter wave massive multiple input multiple output (MIMO) systems, a hybrid precoding scheme based on geometric mean decomposition (GMD) was presented. In the proposed scheme, the channel was decomposed into multiple equal-gain subchannels by means of GMD to simplify the complexity of encoding and decoding. Based on it, the analytical expression of the objective function of system spectrum efficiencyoptimization was derived. And then the hybrid precoding was designed according to the basic tracking principle and the least square method. Finally, the optimal theoretical value of the system spectrum efficiency was obtained by the proposed algorithm. The numerical simulation results show that the proposed scheme has the advantages on reducing system complexity and improving system spectrum efficiency compared with the design scheme based on orthogonal matching pursuit.
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  • A Dynamic Influence Map Model Based on Distance Adjustment
  • LU Xiao-feng, WANG Xiao-ming, SHA Jing
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 50-56. DOI:10.13190/j.jbupt.2018-202
  • Abstract ( 381 )     HTML     　　
  • The traditional influence map either lacks the representation of dynamic information or is inaccurate in the representation, which will easily lead to the wrong decision of the game artificial intelligence subject. In order to solve the problem that influence map was difficult to describe dynamic information, the propagation mode and attenuation mode of influence map were studied, and a dynamic influence map model based on distance adjustment was proposed. According to the movement trend of the objects affected, the distance to be calculated in the process of impact propagation was adjusted The model can encode dynamic information into the influence map so as to support decision making of the game agent. Experiments show that compared with traditional influence map, this model can effectively improve the accuracy of the dynamic information representation in influence map, thus enhance the performance of the game agent.
  • References | Supplementary Material | Related Articles

  Reports

  • Critical Nodes Evaluation of Opportunistic Networks Based on Topological Condensation Graph
  • SHU Jian, JIANG Wen-liang, LIU Lin-lan
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 57-62. DOI:10.13190/j.jbupt.2018-234
  • Abstract ( 432 )     HTML     　　
  • By evaluating critical nodes of opportunistic networks, it was found the nodes that have the greatest influence on the throughput of network, which can support for network optimization and maintenance. The topological condensation graph was constructed according to the characteristics of frequent topology changes in opportunistic networks, and three evaluation metrics, such as second-order degree, connection strength, and key domain importance, were defined. The Euclidean distance of the metrics was employed to characterize the importance of the nodes. Experiments show that the proposed model is effective and superior compared with the betweenness method, and the model has higher accuracy when the time window is set for 20 minutes.
  • References | Supplementary Material | Related Articles

  • Consistent Blur Blind Restoration Algorithm Based on Prior Optimization
  • LI Zhe, LI Jian-zeng, WANG Zhe
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 63-69. DOI:10.13190/j.jbupt.2018-130
  • Abstract ( 397 )     HTML     　　
  • In order to improve the clarity of the blind restoration of the conformance fuzzy image, a prior fuzzy blind restoration algorithm based on the prior optimization is proposed for the study of the prior constraint problem of the full variational model involved in the restoration process. Firstly, the local weighted total variation model based on half Gauss gradient operator is used to extract the significant edge of the blurred image. The noise and texture interference are removed, and the ability to maintain the favorable information is improved. Then a multi-scale mixed characteristic prior estimation of blur kernel is proposed to enhance the accuracy of blur kernel estimation. Finally, clear restored images are obtained by non-blind deconvolution. The experimental results show that compared with other algorithms, the proposed algorithm improves the average peak signal to noise ratio of the reconstructed image by about 1.7%, and the average structure similarity index increases by about 19.1%. In view of the real blur image, the artifact of restored image is less, the edge texture details are more clear and natural, and the overall visual effect is better.
  • References | Supplementary Material | Related Articles

  • A Finite-Time Back-Stepping Dynamic Surface Control
  • LIU Yi-cheng, JIN Zhou, PU Ming
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 70-76. DOI:10.13190/j.jbupt.2018-109
  • Abstract ( 483 )     HTML     　　
  • A finite time back-stepping dynamic surface control was proposed for n-order nonlinear systems with external disturbances and modeling errors. In the subsystem controller design of the dynamic surface control method, a nonlinear filter with fast finite time convergence was designed to replace the first order linear filter. This method can avoid "explosion of terms", reduce the error accumulation of high order system, and at the same time can avoid the singularity problem that is difficult to solve in high order system of finite time control. In order to solve the problem that the estimation error was not taken into account in the stability analysis of dynamic surface control, the stability of the estimation error was considered, and the steady-state control error was given. Finally, combining with the position control of the four-rotor aircraft, the simulation verifies its engineering practicability and superiority.
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  • An Improved Clustering and Resource Allocation Scheme for Ultra-Dense Networks
  • XU Yan-ping, JIA Wen-jie, LI Xiao-jing, ZHANG Chang-sen, TIAN Xin-ji
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 77-82. DOI:10.13190/j.jbupt.2018-095
  • Abstract ( 413 )     HTML     　　
  • An improved clustering and resource allocation scheme was proposed for ultra-dense network in order to reduce the interference among small cells. Firstly, a loss graph was constructed according to the path loss among the small base stations, and the cluster head was selected based on the loss graph. Small base stations with the smaller sum of path loss were divided into the one cluster in which the number of small base stations was no more than the number of subchannels. Then, orthogonal subchannels were allocated to users in each cluster according to the signal to interference plus noise ratio on each subchannel of each user in the cluster. Finally, power allocation was optimized to improve throughput. Simulation results show that compared with the existed schemes in the same scenario, the small base stations are more evenly distributed in each cluster, so that the system throughput is improved significantly.
  • References | Supplementary Material | Related Articles

  • Voice Activity Detection Method Based on MFPH
  • WU Xin-zhong, XIA Ling-xiang, ZHANG Xu, ZHOU Cheng
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 83-89. DOI:10.13190/j.jbupt.2018-228
  • Abstract ( 555 )     HTML     　　
  • In order to solve the problem that the accuracy of traditional voice activity detection algorithms is low in the low signal-to-noise ratio (SNR) environment,a voice activity detection algorithm based on product of spectral entropy and Mel (MFPH) was proposed. Firstly, the first dimensional parameter MFCC₀ of Mel frequency spectrum coefficient of the speech signal with noisy was extracted, and the product of MFCC₀ and spectral entropy was taken as fusion characteristic parameter of finally distinguishing speech segment from background noise. Then, the threshold value of MFPH characteristic parameters was estimated adaptively based on combination of fuzzy C-means clustering algorithm (FCM) and Bayesian information criterion (BIC). Finally, the double-threshold method was adopted for the voice activity detection. Experiments show that the accuracy of the proposed method is greatly improved in the -5~15 dB low SNR environment compared with traditional methods.
  • References | Supplementary Material | Related Articles

  • Quantum Chaotic Extended Sequence Algorithm for 5G F-OFDM
  • MA Ying-jie, ZHAO Geng, FAN Xiao-hong, ZHANG Xin-ran, GAO Yuan
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 90-94. DOI:10.13190/j.jbupt.2018-058
  • Abstract ( 554 )     HTML     　　
  • High peak to average power ratio (PAPR) is a main problem of the fifth generation of mobile communications system(5G) filtered-orthogonal frequency division multiplexing (F-OFDM) systems. Aiming at the shortcomings of traditional selective mapping algorithm, such as limited number of candidate sequences, the quantum chaotic extended sequence algorithm was proposed to solve the high PAPR problem of 5G F-OFDM systems. The original signal was divided into real part signal and imaginary part signal by segmentation method, which were respectively multiplied the quantum logistic chaotic map. The PAPR was calculated by linear superposition of real sequences and the imaginary part candidate, and the minimum PAPR was selected for transmission. The simulation results show that the proposed algorithm reduces the PAPR of 5G F-OFDM system, increases the number of candidate signals and reduces the computational complexity. The proposed scheme has a broad application prospect in 5G multicarrier modulation technology.
  • References | Supplementary Material | Related Articles

  • Extended Kalman Filter for Mobile Groups Users Localization in Internet of Things
  • LIANG Yu-zhu, SHEN Xue-wei, QIU Lei, CHEN Bai-sheng, WANG Tian
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 95-100. DOI:10.13190/j.jbupt.2018-216
  • Abstract ( 496 )     HTML     　　
  • In order to meet the requirement of high localization accuracy and the high reliable localization in some scenarios, the user nodes to be located were taken as a group to get better localization performance by utilizing the mutual distance information among them. A mobile group localization method was designed based on extended Kalman filter, which can alleviate the influence caused by environmental noisy and unstable wireless signals. Besides, a real system was implemented and experiments were performed on the campus of University. The experimental evaluations prove that the performance of the proposed method can effectively improve the localization accuracy.
  • References | Supplementary Material | Related Articles

  • Hybrid Algorithm Base on Fuzzy-Rough Instance Selection for Credit Scoring
  • LIU Zhan-feng, PAN Su
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 101-107. DOI:10.13190/j.jbupt.2018-178
  • Abstract ( 362 )     HTML     　　
  • For the credit scoring system built on cluster algorithm based hybrid classifier, the unreasonable clusters number or starting center points of each cluster have severely negative influence on the classification accuracy. In order to solve the problem, two new hybrid algorithms based on fuzzy-rough instance selection were proposed respectively, which are only related to intrinsic data structure of datasets and are not affected by other external parameters. The experimental results show that the proposed hybrid algorithms exhibit their own characteristics for datasets with different structures, which deepens the understanding of data sets and improves the accuracy.
  • References | Supplementary Material | Related Articles

  • Edge Computing Offloading with Parked Vehicular Collaboration in Internet of Vehicles
  • WU Zhen-quan, YE Dong-dong, YU Rong, ZHOU Wen-hui, HE Zhao-shui
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 108-113. DOI:10.13190/j.jbupt.2018-132
  • Abstract ( 584 )     HTML     　　
  • To improve the performance of edge computing (EC) servers, an edge computing offloading framework of parked vehicular collaboration was proposed. Under this framework, the service provider uses the idle computing resources of the parked vehicles in the parking lot to expand the computing capacity of the edge server of the network, and the parked vehicles cooperate to perform the computing tasks unloaded by the service provider, thus reducing the overload. To stimulate parked vehicles to participate in computation offloading, an incentive scheme based on contract theory is designed, which can not only maximize the benefits of EC service providers, but also enhance the utilities of the parked vehicles. Experimental simulation results based on a real dataset demonstrate the effectiveness of the proposed incentive scheme.
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  • An Anti-DoS Attack RFID Security Authentication Protocol in the Internet of Vehicles
  • XIAO Jian, LI Wen-jiang, GENG Hong-yang, ZHAI Ying-bo
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 114-119. DOI:10.13190/j.jbupt.2018-156
  • Abstract ( 459 )     HTML     　　
  • In order to overcome the security problem of radio frequency identification technology in the internet of vehicles, a security authentication protocol based on key distribution center was proposed. First the label without the legal key was filtered by the updateable private key stored in the key distribution center, and then the identity of the tag was authenticated through the background server. While solving the security problems, such as counterfeit attacks, replay attacks, and tracking attacks in the traditional protocol, the denial of service (DoS) attacks existing in the internet of vehicles were also solved. Through the BAN logic proof, as well as the comparison of security and performance analysis, it shows that this protocol can provide effective security protection in the internet of vehicles, which greatly reduces the computing burden of the background server facing multiple tags.
  • References | Supplementary Material | Related Articles

  • Cooperative Quantum Agent Evolutionary Algorithm and Its Characteristic Analysis
  • LIU Zhen, GUO Heng-guang, LI Wei
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(2): 120-126. DOI:10.13190/j.jbupt.2018-024
  • Abstract ( 299 )     HTML     　　
  • Aiming at the drawback for the quantum optimization algorithm, a novel cooperative quantum agent optimization algorithm is proposed. The individual in the population can be viewed as the agent using quantum bit code, and the evolutionary process can be divided into three phases. The information and individual can exchange between subpopulation, the individual can also compete with each other and adjust slightly. The evolutionary can carry through in the different niche, so it can enhance the evolutionary granularity. The trait of convergence is analyzed in view of the functional analysis. The fixed point theorem is used to prove the convergence of the algorithm, and the theorem shows that the proposed algorithm can reach the satisfactory solution set. Simulation results of benchmark function demonstrate that the algorithm performs well than other algorithms, and can get better solution.
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