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Journal of Beijing University of Posts and Telecommunications

  • EI核心期刊

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  • Papers

    • NDN Routing Strategy Based on SDN Centralized Topology Update
    • YIN Bi-bai, LIU Jiang, ZHANG Ran, HUANG Tao, LIU Yun-jie
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 1-8. DOI:10.13190/j.jbupt.2018-027
    • Abstract ( 466 )     HTML       
    • Named data networking (NDN) routing strategy based on software defined network (SDN) centralized topology update separates the two key functions of routing. The topology update function is centralized in the SDN controller, while the route calculation function is distributed in the NDN content nodes. In addition, in this strategy, load-weighted preprocessing of the network topology can be performed under the premise of considering the state of the network. Simulation results show that in the NDN routing strategy based on the SDN centralized topology update, the delay of the first packet of the content request data stream is reduced by an average of 90%, the load of the SDN controller is reduced by an average of 10% to 30%, and the entire network realizes an effective load balancing.
    • References | Supplementary Material | Related Articles
    • A Physical Layer Secure Communication Mechanism Based on Multidimensional Constellation
    • LIU Zhe, ZHANG Qiao-yu, CHENG Ming-zhi
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 9-15. DOI:10.13190/j.jbupt.2018-030
    • Abstract ( 402 )     HTML       
    • An orthogonal frequency division multiplexing (OFDM) multi-carrier physical layer secure communication mechanism based on multi-dimensional constellation was presented, which can effectively prevent the modulation information of wireless communication from being eavesdropped, therefore, the security communication is guaranteed. Based on multi-dimensional constellation, the system symbol error rate performance and spectrum utilization are derived and simulated. Simulations show that the multi-carrier polarization state-amplitude-phase modulation scheme can effectively prevent the eavesdropper from obtaining the modulation information, and its symbol error rate and spectral efficiency are significantly better than the traditional OFDM-QAM modulation.
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    • A Dynamic Adjustment Strategy of Materialized Views Based on Query Clustering
    • FENG Xia, ZHANG Jiang, ZUO Hai-chao
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 16-22. DOI:10.13190/j.jbupt.2017-234
    • Abstract ( 382 )     HTML       
    • In order to improve performance of query response of data warehouse, and avoid the frequent "jitter" phenomenon for materialized views set caused by immediate adjustment algorithm, a dynamic adjustment strategy of materialized views based on query clustering is presented. Firstly, attribute similarity can be calculated based on method of mining association rules, then queries similarity can be calculated and candidate views set can be generated by clustering the queries set during a statistical time, and then the benefits of candidate views can be calculated according to benefit model. Finally, the latest materialized views can be selected using dynamic management algorithm of materialized views. Based on the experimental results with data of air ticket settlement recorded by airlines. Whether in single-machine environment or distributed environment, compared to other benchmark algorithms, the overall performance of query response of data warehouse has been improved greatly, especially for high frequency queries.
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    • Multiband Microstrip Antenna Design Using Parasitic Coupling Elements
    • HAN Yu-nan, YUAN Si-yu, SUN Xiao-yu, WEN Zheng-lin, ZHOU Jun
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 23-28. DOI:10.13190/j.jbupt.2018-025
    • Abstract ( 656 )     HTML       
    • By adding two different shape parasitic coupling elements at the radiating edge of a feeding transfer metal patch, a single feed point, good conformal shape, compact multiband microstrip antenna was developed. The proposed microstrip antenna is consisting of a ground plane, a feeding transfer metal patch, a meander-line patch parasitic coupling element and a T-shaped patch parasitic coupling element. The resonant frequency and bandwidth of the antenna are determined by the structure of the meander-line patch parasitic coupling element,the T-shaped patch parasitic coupling element, and the mutual coupling between the two parasitic elements and the feeding transfer element. The proposed antenna achieves multiband resonant frequencies that can be tuned independently by adjusting individual structure parameters. The associations between the antenna resonant frequencies and the structure parameters are simulated by electromagnetic simulation software, and it is shown that the antenna can typically work in 0.972~0.988 GHz,2.178~2.27 GHz and 3.293~3.356 GHz. The measurement results fit very well with the simulation, which validates the multiband microstrip antenna design method using parasitic elements excited by single feed point.
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    • Incremental Fuzzy C-Ordered Means Clustering
    • LIU Yong-li, GUO Cheng-yi, WANG Heng-da, CHAO Hao
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 29-36. DOI:10.13190/j.jbupt.2018-026
    • Abstract ( 394 )     HTML       
    • Because traditional clustering algorithms are difficult to deal with large-scale data and sensitive to noise data, based on the Fuzzy C-ordered-means clustering (FCOM) algorithm, we propose a single-pass fuzzy C-ordered clustering algorithm, named SPFCOM, and an online fuzzy C-ordered clustering algorithm, named OFCOM, by combining single-pass and online incremental architectures respectively. These two algorithms weight the FCOM algorithm, and incrementally process the large-scale data chunk by chunk. Experimental results show that, compared with other similar prominent algorithms, the SPFCOM and OFCOM algorithms can achieve higher accuracy and better robustness.
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    • Dynamic Reconfigurable Implementation of SAD Algorithm in HEVC Motion Estimation
    • JIANG Lin, WU Xin, CUI Ji-xing, XIE Xiao-yan, SHAN Rui
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 37-43. DOI:10.13190/j.jbupt.2017-227
    • Abstract ( 505 )     HTML       
    • The asymmetric partitioning mode introduced in the high efficiency video coding (HEVC) standard results in a double increase of the sum of absolute difference (SAD) operation amount in the motion estimation algorithm. In order to improve the efficiency of motion estimation algorithm, it is convenient for users to choose independently, a reconfigurable array structure is designed which supports both the opening and closing of an asymmetric partitioning mode and the free switching between execution modes. In order to satisfy the user's requirement for coding speed, and maximize the use of the resources of the reconfigurable array processor, 16×8, 16×4, and 16×2 processing elements are loaded in an array structure of 16×16 processing elements. The instruction is used to dynamically reconfigure the array size, and different instructions are sent to corresponding processing elements for corresponding configuration by means of the instruction issuance manner. The experimental results show that the proposed reconfigurable implementation approach reduces the processing time by about 35% and the throughput is improved by about 0.4 times compared with the streamlining under the condition that the hardware resource occupancy closely. The implementation has high execution efficiency, and can switch between execution mode and array size, and has better flexibility.
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    • Task Offloading Decision Algorithm of Real-Time Application for Internet of Vehicles
    • PENG Wei-ping, SU Zhe, SONG Cheng, JIA Zong-pu
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 44-50. DOI:10.13190/j.jbupt.2017-256
    • Abstract ( 517 )     HTML       
    • In order to solve the problem of the timeliness of nodes processing tasks in the internet of vehicles, a new task offloading decision-making scheme is proposed based on the optimal node selection and task offloading theory. First of all, the task offloading model is built and a directional node distribution model is constructed. Furthermore, the node is pre-selected by using the optimal node selection algorithm. Finally, the task offloading decision is achieved by once or second task offloading pre-judgment mechanism. Compared with the traditional task offloading decision-making, the proposed solution takes less time, and the task Real-time is more higher. Simulation results verify the effectiveness of the proposed method.
    • References | Supplementary Material | Related Articles
    • Interference Suppression Based Adaptive Resource Allocation Algorithm in MBSFN
    • CHEN Lei
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 51-55. DOI:10.13190/j.jbupt.2018-038
    • Abstract ( 430 )     HTML       
    • The traditional resource allocation algorithms mainly aim at reducing the required resource units, without considering the interference suppression of multicast/broadcast single frequency network (MBSFN). Therefore, an interference suppression based adaptive resource allocation algorithm in MBSFN (IS-ARAAM) is proposed. The topology relationship between MBSFNs is modeled and the transmit power of base station is also taken into consideration when calculating the reuse distance. Then IS-ARAAM is obtained according to the reuse distance. Simulations demonstrate IS-ARAAM is more effective to improve the rate and coverage of network comparing to traditional algorithms. Meanwhile, IS-ARAAM also provides a way to control the number of required resource blocks through adjusting the reuse distance.
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    • Two-Stage Traffic Anomaly Detection Method Based on Entropy and Linear Relation
    • QUI Xue-song, ZHANG Xun, SONG Yan-bin, ZHAO Bing, XU Si-ya
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 56-62. DOI:10.13190/j.jbupt.2017-257
    • Abstract ( 387 )     HTML       
    • To improve the accuracy and real-time traffic anomaly detection methods, a two-stage traffic anomaly detection method based on entropy and linear relation was presented. A two-level dynamic threshold was set and used based on entropy and linear relation to detect abnormal traffic in time domain. The type of traffic anomaly can be indentified through the alarm trigger function. Simulations verify that this method is superior to the existing methods in the accuracy and real-time respects.
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    • A Hybrid Precoding Algorithm Based on Weighted Minimum Mean Square Error in Massive MIMO Systems
    • WEI Min, TANG Wen-jie, TENG Ying-lei, CHEN Guang-quan, SONG Mei
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 63-68. DOI:10.13190/j.jbupt.2017-248
    • Abstract ( 553 )     HTML       
    • To improve the multiplexing gain and reduce the hardware cost of antennas in massive multiple-input multiple-output systems, a hybrid precoding algorithm based on the fully-connected antenna structure was proposed. Aiming at minimizing the multiuser weighted minimum mean square error, an optimization problem was established under the constraints of antenna structure, user fairness and the limitation of power and the hybrid precoding problem was solved by utilizing the best approaching to the digital precoding. Simulations verify that the proposed algorithm narrows down the gap between the hybrid precoder and the optimal one-stage precoder to the greatest extent with a good convergence and obtains a near-optimal solution with significant gain.
    • References | Supplementary Material | Related Articles
    • Improving Semantic Autoencoder Zero-Shot Classification Algorithm by Metric Learning
    • CHEN Xiang-feng, CHEN Wen-bai
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 69-75. DOI:10.13190/j.jbupt.2018-010
    • Abstract ( 389 )     HTML       
    • To improve the robustness of similarity metric method in zero-shot learning, a new metric learning for zero-shot image classification was introduced. It is composed of autoencoders, which can learn the optimal metric function in the feature-aligned semantic embedding space. The similarity between test sample features and the semantic features of the class labels can be calculated by metric function, predicting the label of the class by the neighboring method. Thus, the classification error caused by inappropriate distance function is prevented. Compared with the traditional distance metric algorithm, the experiments show that the proposed method reduces the recognition error rate; the recognition accuracy is improved to 94.7%, 63.7% and 28.59% on the AWA, CUB and ImNet-2 datasets. At the same time, it was confirmed that the recognition accuracy of the semantic-visual mapping direction was 2.5%~10.1% higher than the opposite direction.
    • References | Supplementary Material | Related Articles

    Reports

    • Reliability Analyzing Method of Small Sample Structures and Mechanisms Based on Bootstrap-SVR-SOC
    • MA Yu-peng, ZHANG Jian-guo, QIU Ji-wei
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 81-85. DOI:10.13190/j.jbupt.2017-230
    • Abstract ( 447 )     HTML       
    • In order to solve the small sample reliability problems for structures and mechanisms in real applications,an analyzing framework named Bootstrap-support vector regression-second order cumulant (Bootstrap-SVR-SOC) method together with a sample size extension method combining multi-order moments that could make the extended samples more objective were proposed. Bootstrap was combined with support vector regression method in order to build the limit state function for reliability analysis based on the second order cumulant approach. Finally, numerical case of a crank shaper mechanism was analyzed to demonstrate the effectiveness of the proposed framework.
    • References | Supplementary Material | Related Articles
    • FCBF Feature Selection Algorithm Based on Maximum Information Coefficient
    • ZHANG Li, YUAN Yu-yu, WANG Cong
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 86-90. DOI:10.13190/j.jbupt.2017-229
    • Abstract ( 859 )     HTML       
    • Based on the correlation fast Filtering Feature selection algorithm (FCBF),which is improved by the maximum correlation coefficient. Firstly, It calculates the correlation measure between each feature and label with the ‘maximum normalized information coefficient’ criterion and ‘measurement principle of symmetric uncertainty’ and sort these feature according to the calculated value.Finally, It filters irrelevant features and redundant features by the ‘maximum normalized information coefficient’ criterion and approximate Markov Blanket and obtain the optimal feature subset. Experimental results on machine learning repository of university of california irvine(UCI) eight open datasets show that NFCBF algorithm outperforms FCBF algorithm. The number of features selected by feature selection algorithm based on maximum information coefficient (NFCBF algorithm) is less than 3.625 of the selected feature subset of FCBF algorithm, and the classification accuracy is improved by 0.075%. NFCBF algorithm gives better performance than mutual information maximization algorithm(MIM), Least absolute shrinkage and selection operator algorithm(Lasso) and Ridge algorithm.
    • References | Supplementary Material | Related Articles
    • Information Fusion Algorithm Based on Improved Ant Colony Optimization BP Neural Network in WSN
    • YU Xiu-wu, LIU Qin, LI Xiang-yang, ZHANG Ke, XIAO Ren-rong
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 91-96. DOI:10.13190/j.jbupt.2017-262
    • Abstract ( 437 )     HTML       
    • In order to ensure the effective working of wireless sensor network (WSN) in deep mine, an information fusion algorithm based on improved ant colony optimization back-propagation (BP) neural network in WSN (IFA-IACOBP) is proposed. The heuristic factor of ant colony optimization (ACO) is improved by planning the direction of ants' motion and introducing the residual energy of nodes to improve the selection probability of the ant next-hop node. The improved ant colony algorithm is used to optimize the BP neural network, which is applied to WSN information fusion in mine. These data are processed by two-level fusion, which can remove most redundant information. Simulation results show that the IFA-IACOBP algorithm can effectively decrease the network data communication, improve data real-time performance, reduce network energy consumption and prolong network lifetime.
    • References | Supplementary Material | Related Articles
    • High-Speed Non-Binary Coding and Modulation Techniques of GNSS Message
    • JIN Shu-xin, YAO Zheng, JIA Shen-hui, LU Ming-quan
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 97-103. DOI:10.13190/j.jbupt.2018-009
    • Abstract ( 547 )     HTML       
    • To solve the problem of navigation message rate limiting the performance of global navigation satellite system (GNSS), a new technology of GNSS signal design based on code shift keying modulation and non-binary low density parity check code is discussed. At a receiving level of -130 dBm and an error rate of no more than 10-7, the information rate can be up to 1 500 bit/s. Meanwhile, it has the advantages of simple signal structure and strong compatibility with existing GNSS signals. Theoretical analysis and simulation prove that this technology can break through the limit of information rate under the existing GNSS signal system, and overcome the difficulties of acquisition and tracking caused by complex signal structure. Therefore, it has important practical value in GNSS.
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    • A New Authentication Protocol for Wireless Medical Sensor Network
    • ZHANG Jun-song, ZHANG Qi-kun, GAN Yong, MENG Ying-hui
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 104-109. DOI:10.13190/j.jbupt.2017-250
    • Abstract ( 334 )     HTML       
    • Due to the inefficiency of the existing identity authentication protocol during the login and password update phase in the existing wireless medical sensor network environment, an elliptic curve cryptosystem based authentication protocol suing smart card was presented. The proposed protocol can quickly detect incorrect inputs. The proposed protocol combines the Hash function with the elliptic curve encryption algorithm, which makes its login and password update phases more efficient. Finally, using the BAN logic analysis, it is given that the proposed scheme is more secure than other protocols. The proposed protocol's computing performance and communication costs is also superior to other related authentication protocols.
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    • Survey of Polar Codes for Control Channels in 5G
    • WU Zhan-ji, WU Xi
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 110-118. DOI:10.13190/j.jbupt.2017-212
    • Abstract ( 789 )     HTML       
    • Polar codes are important channel coding for the fifth generation mobile communication (5G), which are already used for control channels for enhance mobile broadband (eMBB) scenarios. At present, the 5G-polar codes specified in the 3GPP TS 38.212 standard have three code structures, but the design reasons and corresponding decoding methods have not been given yet. Firstly, the reliability sequence design and rate-matching method are introduced, and then the principle, the key feature and the decoding algorithm of every code structure are analyzed. Through the performance and complexity comparison analysis of three kinds of polar codes, the applicable condition and reason for each code structure are detailed. At the same time, the performance advantages of the short-size 5G-polar codes over LTE TBCC and 5G-LDPC codes are given quantitatively by computer simulations.
    • References | Supplementary Material | Related Articles
    • Survey on Research of Automatic Design Pattern Detection
    • WANG Zhi-guang, WANG Lei
    • Journal of Beijing University of Posts and Telecommunications. 2018, 41(4): 119-124. DOI:10.13190/j.jbupt.2018-034
    • Abstract ( 356 )     HTML       
    • The development history of the field of automatic design pattern detection was briefly introduced; the research of this field was respectively reviewed from four major categories of approaches:graph theory-based, formal technologies-based, software metrics-based and artificial intelligence-based design pattern detection; the four major categories of approaches are compared through 3 indexes:applicable pattern type(s), time performance and possibility of fully automated; finally the problems and shortcomings of the current research were analyzed, and the future research directions were pointed out. This paper analyzes and discusses the applicable pattern type(s), the advantages/disadvantages and the inner connections of the various approaches, and expounds the research progress of this field from the macro level.
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