Current Issue

• • 2020, Vol. 43 No. 1 Published date:28 February 2020 Last issue Next issue

  Papers

  • Channel Correlation Based LOS/NLOS Identification for 3D Massive MIMO Systems
  • LI Jun-yao, CHANG Yong-yu, ZENG Tian-yi
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 1-7. DOI:10.13190/j.jbupt.2019-052
  • Abstract ( 880 )     HTML     　　
  • To improve the performance of some wireless technologies, which are susceptible to line of sight (LOS) and non line of sight (NLOS), LOS/NLOS identification in 3D massive multi-input multi-output (MIMO) system is studied. Based on channel correlation, an improved identification algorithm, TSFCI-1, is proposed, which uses actual channel information instead of the normally assumed ideal accurate channel. The process includes:defining measurement based on time-space-frequency properties of LOS/NLOS; in view of the unsteady spatial channel correlation for 3D massive MIMO systems, finding the expectation of measurement on the spatial interval; using channel information to construct the statistical identification model. Considering the influence of antenna dual-polarization, TSFCI-2 with better evaluation index is proposed. It is shown that the identification error of TSFCI-1 and TSFCI-2 is as low as 1.92% and 1.72%, with over 6% better than a previous study. Besides, the effects of signal to noise ratio and the taps number on TSFCI-2 with the best performance is discussed.
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  • Mobile Phone Energy Saving Based on Link Prediction
  • XU Jiu-yun, SUN Zhong-shun, ZHANG Ru-ru
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 8-13,27. DOI:10.13190/j.jbupt.2019-061
  • Abstract ( 506 )     HTML     　　
  • The technology of mobile cloud computing is benefit for deploying various mobile applications. However, there is an energy consumption problem to access cloud resources via mobile phone, which needs to establish connections many times under unstable communication conditions. To solve this problem, a link prediction method based on maximum user interaction behavior was proposed. Firstly, based on data prediction model, an interaction degree method based on improved interaction relationship is used to predict the data accessed by users. Then, combined with the friend link method of social network based on user behavior, the prediction data is analyzed and filtered, and the pre-storage mechanism is used to pre-store the above prediction data. Experiments show that the expected energy saving of mobile phones can be achieved without involving users' private information and improving the hit rate of users' next visit.
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  • Road Network Vulnerability Identification Considering the Impact of Road Sections and Intersections Congestion
  • LI Yong-cheng, LIU Shu-mei, YU Yao, LI Shuang
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 14-20. DOI:10.13190/j.jbupt.2019-088
  • Abstract ( 503 )     HTML     　　
  • Accurately assessing the vulnerability of road networks is the basis of road planning. The congestion effects of road sections and intersections are considered. The concept of bottleneck lines is introduced to identify the vulnerable line, it is difficult to withstand emergencies due to small road capacity. A road network vulnerability analysis method based on spectral analysis is proposed thereafter, using the minimum segmentation theory of the spectral partitioning to locate the bottleneck line. In addition, in order to solve the problem of large-area cut-off segmentation, a road network improvement measure based on connectivity contribution is proposed, providing improvement suggestions for road network protection. Simulations show that the proposed method is more accurate in locating the bottleneck line compared to comparison scheme, and the network improvement measure can effectively avoid the segmentation phenomenon of the road network.
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  • NLOS Ranging Error Compensation Algorithm Based on Fuzzy Association Channel Identification
  • LI Xiao-hui, DU Yang-fan, SHI Xiao-zhu, YANG Xu
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 21-27. DOI:10.13190/j.jbupt.2019-084
  • Abstract ( 572 )     HTML     　　
  • Aiming at the problem of ranging errors in non line of sight (NLOS) ranging, an NLOS ranging error compensation algorithm is proposed based on fuzzy association channel identification. The algorithm constructs fuzzy membership matrix of channel feature parameters based on the prior channel feature parameter distribution information, and uses gray correlation analysis method to calculate the normalized weight matrix, so that to obtain the fuzzy comprehensive evaluation matrix to identify the channel environment. On this basis, the Huber residual cost function is constructed according to the channel identification result, and the original ranging result is iteratively reconstructed by Huber linear regression method, which is filtered as the measured value of Kalman filter. Simulation show that the proposed algorithm can improve the ranging accuracy under NLOS effectively, and the range accuracy of this algorithm can reach centimeter level when signal-to-noise ratio is -2 dB.
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  • Reinforcement Learning Based Energy Dispatch Strategy and Control Optimization of Microgrid
  • LIU Jin-hua, KE Zhong-ming, ZHOU Wen-hui
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 28-34. DOI:10.13190/j.jbupt.2019-040
  • Abstract ( 1398 )     HTML     　　
  • Aiming at the economic benefit problem, charging efficiency optimization problem, system load fluctuation problem and carbon emissions problem of energy scheduling in microgrid, application of reinforcement learning to energy scheduling in microgrid is presented. By establishing a complete microgrid model and using reinforcement learning to obtain the optimal strategy in the continuous iterative process, economic benefits tended to be maximized, charging power is relatively stable, load fluctuation of the system is reduced, and carbon emissions is tended minimized. These four joint optimization objectives are reached. Simulations show that the control strategy used in this system can not only maximize the convergence of economic benefits and minimize carbon emissions, but also make the charging power relatively stable, and reduce the load of microgrid. The stability of this system will be improved greatly.
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  • Structure Design of SC-LDPC Code over Additive White Gaussian Noise Channel
  • ZHANG Ya-kun, ZHANG Ya-mei, ZHOU Lin, HE Yu-cheng
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 35-39. DOI:10.13190/j.jbupt.2019-087
  • Abstract ( 597 )     HTML     　　
  • In order to optimize the performance of spatially coupled low density parity check (SC-LDPC) codes over the additive white gaussian noise channel, a novel spatial coupling structure was proposed by changing the edge spreading rules, the edges of the variable nodes were connected to the check nodes of the previous position. Basis matrix, rate, degree distribution and computational complexity were analyzed and the results show that the rate of the novel structure is promoted with the degree distribution of check nodes become larger. Finally, the performance of the proposed novel structure is verified by BP decoding.
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  • BP Neural Network Based CSI Device-Free Target Classification Method
  • JIANG Fang, ZHANG Nan-fei, HU Yan-jun, WANG Yi
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 40-45. DOI:10.13190/j.jbupt.2019-035
  • Abstract ( 539 )     HTML     　　
  • Aim at the imbalance between accuracy and expense, the heavy workload of manually extracting features in current device-free target classification systems, a channel state information (CSI) device-free target classification method based on error back propagation (BP) neural network is proposed. By extracting the CSI of the WiFi signal as the base signal and combining the neural network method with the characteristic of autonomous learning data features, the BP neural network training model is designed, which reduces the overhead caused by the manual extraction feature. Taking the height classification as an example, an experiment is carried out, and it is shown that the proposed method can distinguish four different height segments, and the average classification accuracy can reach more than 90%.
  • References | Supplementary Material | Related Articles

  • Automatic Identification and Cracking Method for Vulnerable Hash Functions of Embedded Firmwares
  • ZHANG Guo-dong, YING Huan, YANG Shou-guo, SHI Zhi-qiang, LI Ji-yuan
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 46-53. DOI:10.13190/j.jbupt.2019-085
  • Abstract ( 514 )     HTML     　　
  • There exist some problems for the existing firmware vulnerable Hash functions mining technology, for the reason that the identification error rate is high, the positioning is not accurate, the cracking is difficult and so on. To solve these problems, a method that uses vulnerable Hash functions identification and positioning technique based on machine learning model and a structured matching method is proposed. Meantime, constraint solution of Z3 satisfiability modulo theories (Z3 SMT) based on VEX intermediate representation (VEX IR) and symbol execution techniques for an automatic identification and cracking method or vulnerable Hash functions of embedded firmwares are proposed. A complete automated analysis process is constructed for the vulnerable Hash functions in the firmware binaries from being identified and positioned to being cracked. Experiments show that the method can identify and position the vulnerable Hash functions in the binary files which compiled by multiple architectures and compiler optimization options with the accuracy rate as high as 98%, vulnerable Hash functions with a structure similar to the BKDRHash Hash function structure can be accurately positioned and quickly cracked out of many collision values.
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  • Markov Chain Based Artificial Bee Colony Algorithm
  • GUO Jia, MA Chao-bin, MIAO Meng-meng, ZHANG Shao-bo
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 54-60. DOI:10.13190/j.jbupt.2019-063
  • Abstract ( 567 )     HTML     　　
  • To overcome the shortcomings of existing local search ability and to easily obtain the local optimal solution of artificial bee colony algorithm (ABC), a new modified artificial bee colony algorithm (MABC) is proposed using the development trend of known solution space predicted by Markov Chain. The running process of the algorithm is provided through a pseudo code. The performances of the ABC and MABC are analyzed from two aspects:convergence performance and algorithm complexity. Using 10 typical functions as test cases, Experiments are carried out in four aspects:result precision, convergence speed, segmentation parameters and running time. It is shown that the MABC algorithm is superior to the ABC algorithm in terms of accuracy and convergence speed.
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  • Signal Combining and Self-Interference Cancellation Scheme Based on Linear Neural Network in a Full-Duplex Receiver Cooperative Jamming System
  • LEI Wei-jia, LI Huan
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 61-67. DOI:10.13190/j.jbupt.2019-067
  • Abstract ( 503 )     HTML     　　
  • Aiming at the problem of self-interference cancellation when the full-duplex mode is adopted by the legitimate receiver, a scheme is presented for signal combining and self-interference cancellation based on neural networks at the full-duplex legitimate receiver in a single-input multi-output system. The legitimate receiver, while receiving signals, sends artificial noise to interfere with the eavesdropper. Two neural networks are designed, one combining the signals received by multiple antennas, and the other reconstructing self-interference for the self-interference cancellation of the received signals. The bit error rates of the legitimate receiver and the eavesdropper and the achievable secrecy rate are simulated. The simulation results show that the signal combination and self-interference cancellation scheme is feasible and effective. They also show that a considerable secrecy rate can be achieved when the transmitting antennas and receiving antennas at the legitimate receiver are properly allocated.
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  • Log Template Extraction Algorithm Based on Normalized Feature Discrimination
  • SHUANG Kai, LI Yi-wen, Lü Zhi-heng, HAN Jing, LIU Jian-wei
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 68-73. DOI:10.13190/j.jbupt.2019-033
  • Abstract ( 705 )     HTML     　　
  • A log template extraction algorithm based on normalized feature discrimination is proposed, aiming at the problem that the number of clusters needs to be provided as a priori information in traditional log template extraction. First, log data is initially compressed to reduce data redundancy. Then, a log clustering process is implemented, and the normalized feature is used to discriminate whether the clustering result meets requirement:if so, the clustering process is successfully completed; if not, the number of log clusters is adjusted by using binary search and redo clustering. Finally, the log template is extracted via clustering results. In addition, an evaluation metric that measures the effectiveness of template extraction is designed. Experiments on real data indicated that the algorithm can achieve more stable and accurate template extraction performance than the benchmark method, and it had good generalization performance.
  • References | Supplementary Material | Related Articles

  • Trusted Routing and Forwarding Mechanism Based on Dirichlet Distribution
  • DU Cong, ZHANG Zhe, LI Wen-jing, GUO Shao-yong, MENG Luo-ming
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 74-79. DOI:10.13190/j.jbupt.2019-089
  • Abstract ( 448 )     HTML     　　
  • The opportunistic mobile social network is vulnerable to the interruption of normal communication due to the interference of bad nodes. Existing research methods generally have the problem of neglecting the difference of bad behavior. The article proposes a trusted routing and forwarding mechanism based on Dirichlet distribution. Firstly, the message passing process is used to judge the credibility of the node, and then the routing and forwarding mechanism for dealing with interference is proposed. Experiment shows that the mechanism can accurately evaluate nodes under the condition of poor node interference, and the transmission success rate is 5%~10% higher than the traditional method while keeping the transmission cost low.
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  • Proactive Caching Scheme with Local Content Popularity Prediction
  • REN Jia-zhi, TIAN Hui, NIE Gao-feng
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 80-91. DOI:10.13190/j.jbupt.2019-054
  • Abstract ( 775 )     HTML     　　
  • Considering the problem that most works on content placement so far consider global popularity, neglecting the demand difference between base stations (BSs), a content placement scheme based on similarity between small base stations (SBSs) and local content popularity prediction considering popularities' geographical diversity are proposed. Firstly, SBSs that possess similar historical content requests is identified by similarity measurements. Then the probabilities of future requests are predicted for each similar SBS group utilizing linear regression method. Based on this local popularity, the sub-optimal content placement decision is made according to stochastic geometry and convex optimization. Thereafter, real data sets to verify our prediction algorithm and investigate system performance are used. It is shown that the proposed scheme outperforms the comparison schemes in terms of hit ratio.
  • References | Supplementary Material | Related Articles

  • Quantum Simulation Model of Entangled Microwave Signals
  • LI Xiang, WU De-wei, ZHU Hao-nan, MIAO Qiang, WEI Tian-li
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 92-96. DOI:10.13190/j.jbupt.2019-065
  • Abstract ( 518 )     HTML     　　
  • In order to facilitate the design of component parameters based on actual generating circuits of entangled microwave signals and improve the entanglement degree of entangled microwave signals, a quantum simulation model of entangled microwave signals is proposed. Firstly, according to the quantization of electromagnetic field, the electric-field intensity of entangled microwave signals is represented by the observable physical quantity-quadrature components. Then, the relation among the electric-field intensity and the input angular frequency, the squeezed parameter and the noise fluctuation is obtained. Subsequently, the random numbers with Gaussian distribution are used as the input of vacuum state or squeezed state to analyze the changing of the exacting quadrature components with time. It is shown that the quantum simulation model of entangled microwave signals can reflect the positive and negative correlation characteristics of quadrature components. The correlation degree is proportional to the squeezed parameter.
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  Reports

  • A Heavy Hitter Detection Mechanism in Software Defined Networks
  • XING Chang-you, LI Dong-yang, XIE Sheng-xu, ZHANG Guo-min, WEI Wei
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 97-103. DOI:10.13190/j.jbupt.2019-076
  • Abstract ( 631 )     HTML     　　
  • SampleFlow, a heavy hitter detection mechanism in software defined networks, is proposed to solve the problems of low detection accuracy and high measurement cost. By combining the technical advantage of sFlow and OpenFlow, SampleFlow firstly detects a set of suspicious heavy hitters by using the coarse-grained sFlow sampling method, and then installs measurement flow entries on specific OpenFlow switches to perform a fine-grained measurement on these suspicious heavy hitters, so as to determine the true heavy hitters. Besides, SampleFlow also uses a sampling position optimization method to decrease the sampling redundancy. Experiment results show that SampleFlow can decrease the measurement cost, and increase the heavy hitter detection accuracy effectively.
  • References | Supplementary Material | Related Articles

  • Analysis and Improvement of Privacy Protection Scheme in VANET
  • LI Tao, ZHANG Jing, YANG Hao
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 104-110. DOI:10.13190/j.jbupt.2019-017
  • Abstract ( 531 )     HTML     　　
  • Through analysis a privacy protection scheme in vehicle Ad hoc network (VANET), it is revealed that the scheme cannot resist the collusion attack. Based on the scheme, a novel privacy protection scheme is proposed. It is proved that the proposed scheme solves privacy protection, anonymity, collusion attack, replay attack, etc. Compared with current privacy protection schemes in VANET, the novel scheme is more security.
  • References | Supplementary Material | Related Articles

  • Study on PDMA Based Visible Light Communication Systems
  • SHEN Xiao-huan, LIN Bang-jiang, TANG Xuan, XU Jun-xiang
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 111-115. DOI:10.13190/j.jbupt.2019-018
  • Abstract ( 587 )     HTML     　　
  • A visible light communications (VLC) system based on non-orthogonal multiple access technology-pattern division multiple access (PDMA), is proposed. PDMA technology can simultaneously optimizes the transmitter and receiver of a multi-user VLC system to achieve non-orthogonal transmission. To achieve the resources reuse at the transmitter under the conditions of frequency domain at the same time, it is necessary to use the joint coding of power, space and channel coding of the multiusers. The multiuser detection at the receiver is, based on message passing algorithm, to optimize the performances of VLC. PDMA can support 150% overload gain of the number of users compared with orthogonal frequency division multiplexing access. Simulation verification of the VLC system is carried out and shows that the transmission distance can achieve 120 cm for the bit error rate of 10^-3 with limited bandwidth of LEDs.
  • References | Supplementary Material | Related Articles

  • DOA Estimation Algorithm for Sparse Representation Under Non-Stationary Noise
  • WEI Juan, CAO Kai-jun, NING Fang-li
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 116-121. DOI:10.13190/j.jbupt.2019-049
  • Abstract ( 490 )     HTML     　　
  • In order to improve the direction of arrival (DOA) estimation accuracy of the far-field non-coherent narrow-band signal in non-stationary noise environment, an improved DOA estimation algorithm based on sparse reconstruction is proposed. Firstly, the class differential covariance algorithm is used to construct the difference matrix to suppress the influence of non-stationary noise. Then the sparse representation model and the weight function is constructed based on the basic principle of estimation of signal parameters via rotational invariance technique algorithm. Finally, the DOA estimation is realized by solving the model with weighted l₁ norm. Simulation shows that, compared with the traditional covariance difference algorithm, the noise covariance matrix estimation algorithm, the rank trace minimization algorithm, the sparse reconstruction algorithm, the proposed algorithm can not only suppress the influence of non-stationary noise effectively, but also has strong robustness and high estimation accuracy under low signal noise ratio and low snapshot number.
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  • Social Network User Identity Association and Its Analysis
  • SUN Bo, ZHANG Wei, SI Cheng-xiang
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 122-128. DOI:10.13190/j.jbupt.2019-020
  • Abstract ( 960 )     HTML     　　
  • The same user registers accounts on different social platforms, which makes user data scattered across multiple platforms, and these data are incomplete, unreliable and low utilization. By using these cross-platform data to discover the real identity of the same user corresponding to different accounts, cross-platform user identity association plays an important role in building detailed user profiles, recommendation systems, cross-social network link prediction and other cross-platform applications. Starting from the research status of identity association technology at home and abroad, the framework of user identity association and analysis is introduced, and the standards of identity data acquisition and social network data sets are collated. Subsequently, the technology of user identity association in recent years is analyzed and the evaluation index of identity association is summarized, and the social network data mining and analysis based on identity association is expounded. Finally, the research difficulties and hotspots of identity association are discussed and prospected.
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  • Color Pencil Drawing Based on Convolutional Neural Network
  • WANG Xiao-yu, HU Xin-hao, HAN Chang-lin
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 129-134. DOI:10.13190/j.jbupt.2019-030
  • Abstract ( 530 )     HTML     　　
  • In order to optimize the single generation result of traditional color pencil drawing algorithms, a convolution neural network (CNN) based color pencil drawing generation method is presented. Fractional differentiation is employed to obtain original image contour information, CNN can obtain pencil drawing style, and histogram matching can obtain similar tones. Meanwhile, L-BFGS algorithm is used to synthesize pencil drawing image. This can generate color pencil drawing images of different styles. Experiments show that the images generated can retain more original image detail information, and feature with more flexible and diverse styles.
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  • Research on Location Privacy Protection Scheme Based on Similar Trajectory Replacement
  • SONG Cheng, ZHANG Ya-dong, PENG Wei-ping, WANG Lei, LIU Zhi-zhong
  • Journal of Beijing University of Posts and Telecommunications. 2020, 43(1): 135-142. DOI:10.13190/j.jbupt.2019-031
  • Abstract ( 500 )     HTML     　　
  • Aiming at the problem of privacy leakage of mobile terminal users in location based service, a location privacy protection scheme is proposed based on similar trajectory replacement query. In this scheme, identities of the requesting user and all the candidates are annonymized. By adopting the similar trajectory function to calculate the trajectory similarities between all the candidates and the requesting user at certain time intervals, the optimal candidate with highest similarity is selected to represent requesting user in requesting LBS. So the identities of the requesting user. The privacy of queries and the trajectories is protected. Security analyses prove that the scheme satisfies such security features as anonymity, unforgeability, and resisting continuous query service tracking attack. Simulation shows that the proposed scheme effectively improves the trajectory similarity of the optimal candidate and the efficiency of the best candidate selection.
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