Please wait a minute...

Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

Current Issue

  • Review

    • Intelligent-Concise Radio Access Networks in 6G: Architecture, Techniques and Insight
    • PENG Mu-gen, SUN Yao-hua, WANG Wen-bo
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 1-10. DOI:10.13190/j.jbupt.2020-079
    • Abstract ( 1323 )     HTML       
    • Mobile communication systems evolve every ten years, and to meet the performance requirements of high bit rate, low latency, and massive connections for the intelligent people-machine-things communications, the intelligent-endogenesis 6th generation of mobile communications system (6G) is urgent to be evolved. In order to fulfill the functions of intelligent-endogenesis, an extreme-intelligent and extreme-concise system architecture of radio access networks is proposed. The corresponding fundamental theories and key techniques are outlined, and the future particular services and applications in 6G are discussed as well.
    • References | Supplementary Material | Related Articles

    Papers

    • Exploring the Life Modeling Methods for Electrochemical Migration Failure of Printed Circuit Board under Dust Particles
    • ZHOU Yi-lin, YANG Lu, LU Wen-rui
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 11-18,31. DOI:10.13190/j.jbupt.2019-170
    • Abstract ( 599 )     HTML       
    • Facing the complex conditions that the discrete dust particles interact with the temperature, the humidity, and the electric field intensity, it is difficult to effectively establish the life model of electrochemical migration (ECM) of printed circuit board (PCB) based on failure physics. Through the temperature humidity bias tests, the ECM process under different dust density is simulated. The effect of particle distribution density on time to failure (TTF) of PCB is analyzed. The TTF data of PCB under different particle distribution density, temperature, relative humidity and electric field intensity are obtained by an orthogonal experiment. Based on the data driven method, the ECM life modeling of PCB under dust particle pollution is discussed. The life prediction effects of polynomial regression, gradient boosting regression tree and random forest in machine learning for high and low dust distribution density are compared. The effectiveness of machine learning to establish ECM life model of PCB under dust particle contamination is discussed.
    • References | Supplementary Material | Related Articles
    • Resource Allocation Algorithm for Simultaneous Wireless Information and Power Transfer in Multi-Carrier Cognitive Radio
    • GUO Shao-xiong, LIU Yu-tao, Lü Yu-jing, ZHANG Zhong-zhao
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 19-23. DOI:10.13190/j.jbupt.2019-118
    • Abstract ( 598 )     HTML       
    • Cognitive radio can improve spectrum utilization through sensing spectrum, but it may generate circuit energy consumption, which decreases transmission energy.In order to guarantee transmission performance, a multi-carrier is proposed to realize simultaneous wireless information and power transfer whose optimal performance can be achieved through communication resource allocations.Cognitive radio uses some subcarriers to transmit information and collect the primary user radio frequency energy on the remaining subcarriers to supplement the perceived energy consumption.A joint optimization algorithm of subcarrier set and subcarrier power is proposed, which can maximize system performance subject the constraints of energy, interference and total power.Simulations show that energy harvesting may occupy transmission resources, a reasonable allocation of subcarriers is required to achieve a tradefoff between rate and energy.The proposed algorithm effectively improves system throughput by collecting energy to supplement sensing energy consumption.
    • References | Supplementary Material | Related Articles
    • UAV-Assisted Time Division Power Allocation Strategy Based on RF Energy Harvesting
    • LIU Zhi-chao, ZHAO Yi-sheng, GAO Jin-cheng, CHEN Zhong-hui
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 24-31. DOI:10.13190/j.jbupt.2019-175
    • Abstract ( 525 )     HTML       
    • Aiming at the difference of users in different time periods for the femto base station (FBS),the power allocation problem of maximizing the total downlink information is investigated.The different time periods include busy time and spare time.There are more users in the busy time and less users in the spare time.By deploying a pico base station carried by unmanned aerial vehicle (PBS-UAV),it provides services for users of multiple FBSs in spare time.Both the FBS and PBS-UAV have energy harvesting function.During the busy time,the FBS and PBS-UAV simultaneously harvest energy from the macro base station,and FBSs transmit data to users.During the spare time,multiple FBSs are replaced by the PBS-UAV to communicate with users in downlink.The power allocation problem is modeled as an optimization problem.The objective is to maximize the amount of downlink information of FBSs and PBS-UAV while satisfying the constraints of FBS and PBS-UAV energy consumption and transmission power.Because the formulated optimization problem is a convex optimization problem,the optimal solution is obtained by using an augmented Lagrange multiplier method.Simulations show that compared with the equal power method and partial fixed power method with PBS-UAV,the proposed method has an increase in terms of total information to different degrees.
    • References | Supplementary Material | Related Articles
    • Offloading Decision and Resource Optimization for Cache-Assisted Edge Computing
    • XUE Jian-bin, DING Xue-qian, LIU Xing-xing
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 32-37. DOI:10.13190/j.jbupt.2019-189
    • Abstract ( 641 )     HTML       
    • An offloading decision and resource optimization scheme for cache-assisted edge computing is proposed to further reduce the energy consumption of terminal devices in the mobile egde computing(MEC)system.Firstly,the optimization problem is established to minimize the worst-case energy consumption of user during the task execution,and the mixed integer programming problem is transformed into a non-convex quadratic constrained quadratic programming(QCQP)model.Semidefinite-relaxation and randomization probability mapping are used to obtain the pre-selected offloading set assisted by caching;Secondly, the Lagrangian dual decomposition method and the bisection method are utilized to acquire the optimal transmission power and edge computing resource under constraints.By comparing the energy consumption of the set of devices,an ideal set of offloading decision and resource allocation scheme are got.Experiment shows that the proposed scheme can effectively reduce the energy consumption and improve the service performance of the edge computing system.
    • References | Supplementary Material | Related Articles
    • Identification Method of Valve Leakage Ultrasonic Signal Based on Improved CNN
    • NING Fang-li, HAN Peng-cheng, DUAN Shuang, LI Hang, WEI Juan
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 38-44. DOI:10.13190/j.jbupt.2019-127
    • Abstract ( 553 )     HTML       
    • In order to detect valve leakage in gas pipelines, an improved AlexNet network architecture is studied, an ultrasonic signal recognition method for valve leakage based on an improved convolutional neural network (CNN) is proposed. Due to short-term and narrow-band line spectrum features of the leakage signals, the "square" convolution kernel, commonly used in image recognition, is changed to "flat" based on the perspective of image neighborhood information density. At the same time, the AlexNet layers are optimized, the number of convolution kernel and neurons in the fully connected layers are re-determined, and the small-scale convolution kernel is selected to increase the network capacity and model complexity while reducing the number of parameters to prevent model overfitting. The two-class and multi-class models with different leakages are established respectively, and the data set is collected through experiments to generate corresponding time-frequency diagram samples as well, including leakage signals at different valve openings and pipeline pressures and background acoustic signals. It is shown that the improved CNN classifier achieves higher recognition performance on the test set than the traditional CNN classifier.
    • References | Supplementary Material | Related Articles
    • Spectral Efficiency Analysis of Massive MIMO Systems over Spatial Correlation Channel
    • DING Qing-feng, LIAN Yi-chong, DENG Yu-qian
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 45-50,98. DOI:10.13190/j.jbupt.2019-177
    • Abstract ( 664 )     HTML       
    • Aiming at multi-user massive multi-input multi-output systems with jammer under spatial correlation channel, where the system spectral efficiency performance of the base station with low-resolution analog-to-digital converters (ADCs) is studied. Establishing spatial correlation channel by combining exponential Toeplitz correlation models, utilizing the additive quantization noise model and the maximum ratio combination algorithm, a closed expression of the spectral efficiency is derived. The system spectral efficiency under ideal/non-ideal channel state information is analyzed thereafter. Simulation shows that the spectral efficiency will have a saturation effect as the transmit power of the user and the resolution of the ADC increase; when the transmit power of the user is less than the transmit power of the jammer, the influence of the jammer on the system is dominant; when the transmit power of the user is greater than the transmit power of the jammer, it can effectively suppress the influence of the jammer on the system.
    • References | Supplementary Material | Related Articles
    • Packet Error Probability Analysis of Multiuser MIMO-WET System with Short-Packet Transmission
    • ZHAO Wei, LUO Ya-fei, BAO Hui, WANG Bin
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 51-58. DOI:10.13190/j.jbupt.2019-187
    • Abstract ( 500 )     HTML       
    • Aiming at the characteristics of ultra-reliable low-latency communication transceiver equipment with limited energy and ultra-reliability requirements, the multi-antenna technology is applied to the short-packet transmission system of wireless energy harvesting and the packet error probability (PEP) performance of multiuser multi-antenna-wireless energy transmission (MIMO-WET) system with short-packet transmission is studied accordingly. Firstly, an approximate closed-form expression of the packet error probability is obtained by utilizing the cumulative distribution function of the signal-to-noise ratio for each user and the Gaussian function approximation method.Then the number of channel uses in the wireless energy transmission phase and the power allocation factors in the wireless information transmission (WIT) phase are jointly optimized for minimizing the sum-PEP of all users.Simulations validate the correctness of the closed expression of the packet error probability.It is shown that there are optimum numbers of channels uses for WET and WIT for given packet length of information transmission and the number of antennas.
    • References | Supplementary Material | Related Articles
    • A Multiuser Interference Cancellation Algorithm in Time Reversal Division Multiple Access System
    • ZHU Jiang, LIANG Jing-wen, Lü Zhi-qiang
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 59-65. DOI:10.13190/j.jbupt.2019-191
    • Abstract ( 401 )     HTML       
    • Aiming at solving the problem of multi-user interference caused by channel correlation in time reversal division multiple access system,eliminating inter-use interference and reducing computational complexity,a low complexity approximation algorithm of matrix decomposition of tridiagonal matrices based on minimum mean square error is proposed.Firstly, the tridiagonal matrix that include the main diagonal line in the detection matrix(Gram-N) is extracted,and the tridiagonal matrix into two double diagonal lines matrices is divided.Then,by using the inverse rule of double diagonal lines matrix, the inverse of these two double diagonal lines matrices is obtained, the inverse of the tridiagonal lines matrix is applied in the algorithm.Finally,according to the Neumann series approximation,the goal of approximating Gram-N's inverse is realized by using the inverse of tridiagonal matrix.Simulations show that the proposed algorithm has obvious performance advantages in terms of bit error rate,spectral efficiency,and complexity.The algorithm can obtain a near-optimal performance gain when the complexity is low.
    • References | Supplementary Material | Related Articles
    • Doppler Shift Estimation and Compensation under Satellite Networking System
    • ZHU Jun, LI Qiu-jin, LI Kai, WANG Hua-jun
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 66-71. DOI:10.13190/j.jbupt.2019-178
    • Abstract ( 935 )     HTML       
    • Aiming at problems such as lack of satellite networking capabilities in current satellite mobile communication systems, a Doppler frequency shift estimation and compensation algorithm based on virtual satellite cell networking is proposed on the basis of non-terrestrial networks. By introducing a centralized control unit, the user equipment can quickly select the satellite with the smallest Doppler frequency shift, and at the same time, the Doppler shift value is compensated, updated and re-compensated according to the transmission delay and the satellite ephemeris. Simulations show that, compared with the traditional algorithm, this algorithm effectively reduces the Doppler frequency shift, and improves the quality of satellite communication links and access success rate.
    • References | Supplementary Material | Related Articles
    • Energy-Efficient Routing with Delay Soft-Constraint in Sparse Mobile Networks
    • XU Meng-meng, ZHU Hai, CUI Ya-jie, XU Heng-zhou
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 72-76. DOI:10.13190/j.jbupt.2019-121
    • Abstract ( 489 )     HTML       
    • In order to achieve the energy-efficient data transmission in sparse mobile wireless networks, a routing algorithm with delay soft-constraint is proposed. A sequence of network topologies in a number of time-slots is modeled as a virtual spatial-temporal graph, which includes both the connectivity information in each time-slot and the link change information due to mobility. A new routing problem in the spatial-temporal graph is defined to find an energy-efficient spatial-temporal path under a given delay soft-constraint. Also, an energy-efficient routing algorithm is developed, which could meets the soft-constraint of the transmission delay. Simulations validate that the proposed algorithm achieves the tradeoff between energy consumption and transmission delay.
    • References | Supplementary Material | Related Articles

    Reports

    • Research Review of Green Vehicle Routing Problem
    • KONG Ji-li, CHEN Can
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 77-82. DOI:10.13190/j.jbupt.2019-196
    • Abstract ( 762 )     HTML       
    • To raise the awareness of environmental protection, arouse the great attention of enterprises and respond to the strong push of the government, the development situation of green vehicle routing problem in recent years is analyzed. The origin of the green vehicle routing problem is described focused on the research of hot topics of green vehicle routing problem in the form of teamwork. Minimizing fuel consumption, considering the pollution path, and combining with new energy vehicles are the three main stages of green vehicle routing problem. The article points out the shortcomings of current research on green vehicle routing problem and directions of possible future research.
    • References | Supplementary Material | Related Articles
    • Contract-Based Cache Renting Mechanism in UAV-Assisted 5G Networks
    • WANG Min, ZHANG Bi-ling
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 83-91. DOI:10.13190/j.jbupt.2019-133
    • Abstract ( 564 )     HTML       
    • To alleviate the load of the backhaul link, a mobile network operator (MNO) temporarily deploys cache-enabled unmanned aerial vehicles(UAVs) as aerial base stations to offload the traffic from a macro base station (MBS). While several content providers (CPs) desire to rent the cache space at both the MBS and UAVs to proactively place their popular videos so that their subscribers can receive low-latency services. However, the willingness for cache renting is privately for each (CP), resulting in asymmetric information between the MNO and CPs. To overcome this problem, the contract theory is exploited to formulate the cache renting problem and to maximize the utility of MNO. The feasible conditions for the contract are derived, and the target optimization problem is relaxed to the convex programming problem. Finally, the KKT condition is utilized to solve the optimal contract for the cache renting. Experiments validate the effectiveness of the proposed cache renting mechanism in UAV-assisted the 5th generation of mobile communications system(5G) networks, and the influence of UAVs' flight altitude on system performance is discussed.
    • References | Supplementary Material | Related Articles
    • U-Net Based Intracranial Hemorrhage Recognition
    • ZHANG Tian-qi, KANG Bo, MENG Xiang-fei, LIU Yi-lin, ZHOU Ying
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 92-98. DOI:10.13190/j.jbupt.2019-146
    • Abstract ( 732 )     HTML       
    • Aiming at analysis and recognition of cerebral hemorrhage from craniocerebral computed tomography (CT) images, a method combining neural network model U-Net with contour recognition is proposed to extract brain parenchymal regions. The image texture features of hemorrhagic area are firstly extracted by adaptive threshold segmentation algorithm, the precise location of hemorrhagic area is thereafter obtained through filtering the irrelevant physiological tissues such as soft tissue, brain tissue and cerebrospinal fluid. Finally, a three-dimensional structure of the hemorrhagic area is reconstructed based on interpolation to evaluate the amount of hemorrhage. A validation test with 500 patients from medical institution in Tianjin shows that the algorithm achieves a target recognition accuracy of 97.4% and could provide reference for the diagnosis of cerebral hemorrhage.
    • References | Supplementary Material | Related Articles
    • Uncoded Space-Time Labeling Diversity Based on MBM
    • JIN Ning, SONG Wei-jing, JIN Xiao-ping, CHEN Dong-xiao, WANG Jia-tian
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 99-104. DOI:10.13190/j.jbupt.2019-195
    • Abstract ( 485 )     HTML       
    • Aiming at the problem that the envelope of the uncoded space-time labeling diversity (USTLD) system based on quadrature amplitude modulation (QAM) constellation is not constant and the spectrum efficiency is low, the design method of mappers for phase shift keying (PSK) constellation and the USTLD system based on media based modulation (MBM) is proposed respectively. A bound of the average bit error probability of the proposed system is derived. Due to the high detection complexity of the USTLD-MBM system, a low complexity detection algorithm for the system is given. Simulations show that the error performance of the USTLD-MBM system is better than that of the USTLD system under the same spectral efficiency. In the USTLD-MBM system, the bit error performance (BER) of the sphere decoding algorithm is almost identical to the maximum likelihood (ML) algorithm, and the complexity is reduced by about 50%.
    • References | Supplementary Material | Related Articles
    • Secrecy Outage Probability Analysis of Underlay Cognitive Cooperative Relay Network with Energy Harvesting
    • LUO Yi, WANG Yu-ting, SHI Rong-hua, YAN Meng-chun, ZENG Hao
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 105-111,124. DOI:10.13190/j.jbupt.2019-179
    • Abstract ( 499 )     HTML       
    • Aiming at the problems of low spectrum utilization, short lifetime and the physical layer security caused by the openness of the wireless channel of energy-constrained cooperative relay network, a new two hop cognitive cooperative relay network with distributed relay nodes is constructed by combining power beacon assisted RF energy collection technology, cognitive radio technology and cooperative relay network. Then, a single eavesdropping node is introduced to eavesdrop the second hop transmission, and the optimal relay selection and the sub optimal relay selection are proposed in combination with the active and passive eavesdropping modes respectively, and the closed-form secrecy outage probability expressions of secondary network under two relay selection modes is deduced. It is shown in simulations that the secrecy outage performance of secondary network is significantly affected by the number of primary receiver nodes and relays, the location of relays and the eavesdropping node, the ratio of energy harvesting, the efficiency of energy conversion, and the thresholds of channel capacity and secrecy capacity. The secrecy outage performance of the secondary network under the optimal relay selection scheme is obviously better than that of the suboptimal relay selection scheme. The secrecy outage probability of secondary network is reduced and tends to be saturated by increasing interference constraint or power beacon signals' power.
    • References | Supplementary Material | Related Articles
    • Three-Dimensional Knee Joint Registration Based on Principal Component Analysis and Iterative Closest Point
    • WANG Xiao-yu, CHEN Lin
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 112-117. DOI:10.13190/j.jbupt.2019-165
    • Abstract ( 498 )     HTML       
    • In view of inconsistency between knee joint and prosthesis in spatial coordinate system, a three-stage registration method based on principal component analysis (PCA) and iterative closest point (ICP) algorithm is proposed, which adopts PCA and ICP twice. Firstly, the point cloud data of knee joint and joint prosthesis is registered by PCA. then ICP algorithm is used to adjust the initial registration results. Finally, ICP registration is carried out again for the adjusted point cloud data, so as to adjust its spatial coordinate axis to be consistent. Experiments show that compared with other algorithms, the three-stage registration method can keep high registration accuracy and shorten the registration time.
    • References | Supplementary Material | Related Articles
    • A Fast Clustering Algorithm for Massive Data
    • HE Qian, LI Shuang-fu, HUANG Huan, XU Hong
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 118-124. DOI:10.13190/j.jbupt.2019-078
    • Abstract ( 791 )     HTML       
    • To meet the requirements of massive data processing, a grid-based K-means fast clustering algorithm (SPGK) is proposed. Selection for optimal clustering initial point and the number of clusters algorithm is presented. The grids of different clusters are meshed to obtain the centroid of each grid. These centroid points are used as sample points for K-means clustering, thereby reducing the number of Euclidean distance calculations of K-means. SPGK realizes parallel computation based on Spark platform, which further improves the running efficiency of the algorithm. SPGK not only obtains good clustering effect but also greatly reduces the number of Euclidean distance calculations, which is suitable for fast clustering of mass data. With 10 millions of data, the experiments show that SPGK is superior to the existing K-means++ and recursive partition based K-means clustering algorithms obviously.
    • References | Supplementary Material | Related Articles
    • Research on Compressed Sensing Security Theory
    • TANG Yong-li, ZHAO Ming-jie, LI Li-xiang
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 125-130. DOI:10.13190/j.jbupt.2019-129
    • Abstract ( 540 )     HTML       
    • The rapid development of Internet induces huge requirement on transmission, which calls for much more efficient techniques to compress information. Compressive sensing method can sample sparse signals with much less samples than Nyquist's sampling law with payload of recovery quality and computation complexity. Compressive sensing can not only compress data, but also encrypt them, and thus can be applied to encrypt the information and network. The article reviews the compressive sensing-based encryption methods, which combines other technologies (such as chaotic system, scrambling and diffusion). After analyzing the performance comparison of existing methods, the compressive sensing-based schemes is verified to achieve a great security capability to resist brute-force attack, statistical attack, known plaintext attack and other attacks.
    • References | Supplementary Material | Related Articles
    • Clustering Routing Protocol for WSNs Based on Neural Network Optimization by Improved Firefly Algorithm
    • DAI Jian-yong, DENG Xian-hong, WANG Bin, WANG Heng-hao
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 131-137. DOI:10.13190/j.jbupt.2019-161
    • Abstract ( 595 )     HTML       
    • Aiming at solving the problem of uneven energy consumption in wireless sensor networks (WSNs),an uneven clustering routing protocol based on the improved firefly algorithm optimized back propagation(BP) neural network (IFABPUC) is proposed. To balance the intra-cluster load and reduce the inter-cluster communication distances,a weighting factor which takes into account four more evaluation indexes than the conventional firefly algorithm is embedded in the improved firefly algorithm. To achieve the best clustering, BP neural network is combined to optimize the way to path selection and cluster head election. Simulations show that IFABPUC can effectively extend the lifecycle of networks,save energy and balance energy consumption.
    • References | Supplementary Material | Related Articles
    • An Optimization Scheme with Weighted Sum-Rate Maximization for Multi-User Wireless Powered Communication Networks
    • LI Fang-wei, WU Yue
    • Journal of Beijing University of Posts and Telecommunications. 2020, 43(3): 138-144. DOI:10.13190/j.jbupt.2019-185
    • Abstract ( 550 )     HTML       
    • A jointly optimize time and power allocation in uplink and downlink scheme combined with time reversal technique is proposed to solve the cross-link interference problem in multi-user wireless powered communication networks and maximize the uplink weighted sum-rate.Using the unique time-space focusing of time reversal to suppress the cross-link interference firstly,an optimization model is then established,thus the non-convex weighted sum-rate problem transformed into weighted minimum mean square error problem is solved.The optimal solution of power and time can be obtained separately by grading optimize variables sequentially.Simulations show that the system average sum-rate significantly improved after introducing the time reversal technique to suppress the cross-link interference.
    • References | Supplementary Material | Related Articles