Current Issue

• • 2019, Vol. 42 No. 1 Published date:28 February 2019 Last issue Next issue

  Review

  • Research and Prospect of TCP Optimization in 5G Multi-Access Networks
  • WANG Ying, LI Hong-lin, FEI Zi-xuan, ZHAO Hong-yu, WANG Hong
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 1-15. DOI:10.13190/j.jbupt.2018-280
  • Abstract ( 931 )     HTML     　　
  • In order to optimize the transmission control protocol (TCP) in the fifth generation of mobile communications system (5G), a survey on the optimization mechanism of TCP protocols in 5G multi-access networks is given. Firstly, the limitations and challenges of TCP protocols in wireless access networks are analyzed. Then, the TCP optimization schemes in wireless access networks are sorted out, which are mainly classified into single-path TCP optimization and multipath TCP optimization, simultaneously the comparative analysis of various optimization schemes is summarized. Finally, the development directions of TCP protocol optimization are presented.
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  Papers

  • PDVRPTF Based on Dynamic Clustering Hybrid Topological Structure Particle Swarm Optimization
  • YANG Fu-xing, HU Zhi-chao, KONG Ji-li
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 16-21. DOI:10.13190/j.jbupt.2018-111
  • Abstract ( 428 )     HTML     　　
  • Aiming at the problem that the classic logistics distribution model considers the target, the constraints are not comprehensive enough and there are certain defects in the practical application, a integrated pickup and distribution vehicle routing problem on the basis of the classical model considering time window and fuel consumption (PDVRPTF) is constructed. Hybrid topological structure of particle swarm optimization based on k-medoids dynamic clustering is designed, which solves the problem that classical particle swarm optimization is easy to fall into local optimal solution when solving such models. The simulation results show that the improved particle swarm optimization can jump out of the local optimal solution quickly and converge to the global optimal solution quickly, which solve the logistics distribution path optimization problem effectively.
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  • Information Hiding Scheme Based on Texture Mapping of 3D Model in OBJ Format
  • REN Shuai, WANG Zhen, XU Zhen-chao, SU Dong-xu, HE Yuan
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 22-27. DOI:10.13190/j.jbupt.2018-129
  • Abstract ( 481 )     HTML     　　
  • An information hiding algorithm based on texture mapping of one kind of the document formats of 3D models (OBJ) is proposed in order to improve the robustness. First, 3D model texture maps are transformed into multivariate wavelet form. Second, the singular value decomposition theory is used to extract the multivariate wavelet static coefficients. Last, the secret information and the above static coefficients are merged by multiplication using the three-dimensional Arnold scrambling and texture mapping algorithm, and the merged coefficients are operated by orthographic projection to form the embedding regions. The experiment results indicated that the robustness against some attacks such as wireframe rendering, vertex rendering, patch extrusion, and shearing was improved, and the feasibility of this method was acceptable.
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  • Analysis of Evidence Combination Paradox Based on Canonical Decomposition
  • XUE Da-wei, WANG Yong, GAO Kang-kai
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 28-34. DOI:10.13190/j.jbupt.2018-094
  • Abstract ( 409 )     HTML     　　
  • When applying Dempster's rule of combination to fuse pieces of evidence, a combination paradox can occur. It is very difficult to acquire the law or relationship among these combination paradoxes with some different manifestations. In order to resolve this problem, the study is carried out by the aid of canonical decomposition which is used to transform the basic belief assignment into the combination of a set of generalized simple support function. Firstly, two typical counterexamples are analyzed, and then the common characteristic between them, neglecting belief, is summarized. On the basis of this, a further analysis is made. Two forms of neglecting belief and the rules of causing them are generalized. A further analysis of type Ⅱ neglecting belief is made. Some general conclusions,that type Ⅱ neglecting belief cannot occur,are presented. These generalized rules and conclusions provide not only the basis for applying Dempster's rule more reasonably to avoid combination paradoxes, but also the reference for modifying the combination method more effectively.
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  • Beidou Signal Capture Algorithm Based on Pseudo Code and Doppler Frequency Separation
  • ZHANG Wen-xu, WU Ya-tong, DU Qiu-ying
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 35-40,108. DOI:10.13190/j.jbupt.2018-008
  • Abstract ( 494 )     HTML     　　
  • Beidou B1 frequency signal using the secondary encoding structure, bit-flipping of Neumann-Hoffman (NH) codes used for secondary encoding leads to a decrease in receiver acquisition performance. Aiming at this problem, a Beidou signal acquisition algorithm based on pseudocode and Doppler frequency separation is proposed. The algorithm divides the received signal into two paths, and uses the delay difference operation and the bipolarity of the ranging code to process the two signals respectively, thus eliminating the influence of the bit hopping of the NH code. Based on this, the matched filter is used to capture the phase of the code and the fast Fourier transformation is used to search for the Doppler frequency. Capturing the phase and the Doppler frequency at the same time is realized. Finally, the simulation results show that the proposed algorithm successfully captures the signal with bit-flipping. Compared to partial matched filtering-fast Fourier transformation algorithm, the sensitivity is 1.03 dB increased under the same false alarm rate.
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  • Idle Channel Detection Scheme under Impulsive Noise Environments
  • TAO Yi-wen, LU Yang, AN Chun-yan, LI Bin, ZHAO Cheng-lin
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 41-46. DOI:10.13190/j.jbupt.2017-082
  • Abstract ( 357 )     HTML     　　
  • Aiming at the idle channel detection problem under impulsive noise environments, a new detection scheme is proposed based on Bayesian statistical reasoning framework. To cope with impulsive interference and improve probability of detection, a novel dynamic state-space model is established, in which the dynamic variations of impulsive noise and channel status are described by Bernoulli random finite sets. On the basis of above, a novel channel detection mechanism is designed based on sequential estimation and particle filtering theory. At the same time of detecting channel status, the proposed scheme jointly estimates the occurrence and amplitude of impulsive noise, therefore eliminating its interference on channel detection. Moreover, the channel detection performance can be significantly improved based on utilizing the dynamic property of impulsive noise, thus providing a promising solution for channel detection with high reliability under complex electromagnetic environments. Numerical simulations verify the effectiveness of the proposed algorithm.
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  • Method of Mode Recognition for Multi-OAM Multiplexing Based on Convolutional Neural Network
  • YIN Xiao-li, GUO Yi-lin, CUI Xiao-zhou, CHANG Huan, CHEN Xiao-zheng
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 47-52. DOI:10.13190/j.jbupt.2018-083
  • Abstract ( 611 )     HTML     　　
  • In order to solve the problem of detection of different orbital angular momentum (OAM) superimposed vortex beams, a pattern recognition technology based on machine learning (ML) is proposed, which provides a brand-new method for multi-OAM states detection. In order to study the recognition rate of multi-OAM beams using convolutional neural network (CNN) models under different wavelength, transmission distance and atmospheric turbulence conditions, the numerical simulation phase screens are generated by the power spectral inversion method based on the modified von Karman power spectrum model. Multi-step diffraction method is used to simulate numerically the propagation of OAM beams in the atmospheric turbulence, and the training and testing database are obtained under different atmospheric turbulence. Results indicate the accuracy of CNN-based OAM pattern recognition increases as wavelength increases, transmission distance decreases and turbulent intensity decreases. And the CNN trained with the database under strong turbulence has high accuracy for all kind of turbulence condition, and using mixed training database under different turbulence condition can enhance the accuracy. These results contribute to the demultiplexing systems of free space optical-OAM systems.
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  • Block-Wise Two Dimensional Kernel Quaternion Principal Component Analysis
  • CHEN Bei-jing, YANG Jian-hao, FAN Chun-nian, SU Qing-tang, WANG Ding-cheng
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 53-60. DOI:10.13190/j.jbupt.2018-045
  • Abstract ( 401 )     HTML     　　
  • Currently, kernel quaternion principal component analysis (KQPCA) has been proposed and successfully applied to process linear quaternion signals. However, two dimensional version of KQPCA (2DKQPCA) has not been successfully implemented due to the quite time-consuming problem for diagonalizing the high dimensional kernel matrix. So, using the block-based idea and the parallel computing idea, the block-wise 2DKQPCA (B2DKQPCA) is proposed to implement 2DKQPCA really. After the overall consideration of computational complexity, application performance and quaternion Hermitian block, B2DKQPCA mainly processes the blocks of three directions:main-diagonal direction, anti-diagonal direction and side-diagonal direction. Then, B2DKQPCA is applied into RGB-D object recognition by combining B2DKQPCA and quaternion representation of RGB-D images. Experimental results on two publicly available datasets demonstrate that the proposed RGB-D object recognition algorithm based on the column direction B2DKQPCA outperforms some existing algorithms using principal component analysis and some existing algorithms using convolutional neural network.
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  • Image Sentiment Analysis with Multimodal Discriminative Embedding Space
  • Lü Guang-rui, CAI Guo-yong, LIN Yu-ming
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 61-67. DOI:10.13190/j.jbupt.2018-040
  • Abstract ( 450 )     HTML     　　
  • In order to alleviate affective gap and large intra-class variance existing in visual sentiment analysis, firstly a new method is proposed, which exploits simultaneously not only deep latent correlations between visual and textual modalities, but also deep linear discrimination of visual modality and weak supervision of mid-level semantic features of images. The method uses multimodal deep network architecture to find a latent embedding space in which deep correlations between visual and textual modalities are maximized, and at the same time there is a deep discrimination on visual modality. In the latent space, the extracted semantic feature of texts can be transferred to the extracted discriminant visual feature of images. Secondly based on the usfulness of attention mechanism, an attention network is presented, which accepts the extracted features in the latent space as input and is trained as a sentiment classifier. Results of experiments conducted on real datasets show that the proposed approach achieves better sentiment classification accuracy than those state-of-the-art approaches.
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  • Locating Image Splicing by Improved DeepLabv3+
  • ZHANG Ji-wei, NIU Shao-zhang, CAO Zhi-yi, WANG Xin-yi
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 68-73. DOI:10.13190/j.jbupt.2018-244
  • Abstract ( 500 )     HTML     　　
  • As the existing splicing detection algorithms mainly detect whether the image has undergone image splicing, rather than regional localization of the spliced area. An improved DeepLabv3+ network that changes the categories of original DeepLabv3+ network is proposed to locate image regional forgery. In addition, the original images are added to the training dataset, and the ground truth of the original images are set to be black images, which will guide the network to learn the difference between the original images and the spliced images. Experimental results show that the improved DeepLabv3+ network has achieved a finer effect for locating image regional forgery than the existing algorithms on the CASIA database.
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  • A Joint Scheme for Error Correction and Secrecy Based on Rateless Error Correction Codes
  • LEI Wei-jia, LI Yu-yu
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 74-80. DOI:10.13190/j.jbupt.2018-101
  • Abstract ( 359 )     HTML     　　
  • A secure and reliable transmission scheme based on rateless codes is proposed. The encoder and decoder generete random coding matrix and deleting pattern by setting up pseudo-random number generators, enabling random generation and deletion of encoded symbols, and the seed of pseudo-random number generator is the secret key. Since the degree distribution of the encoded symbols after random deletion is not changed, the error correction performance of the rateless codes is not affected. Simulation under additive white Gaussian noise channel and Rayleigh fading channel indicates that the bit-error-rate of the eavesdropper is kept near 0.5, and the word-error-rate remains 1, while the error performance of the legitimate receiver is the same as conventional rateless coding systems, thus error correction and encryption are realized simultaneously.
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  Reports

  • A Probabilistic Model for Discovering Potential High-Value Passengers Based on Trip Purposes Mining
  • XU Tao, ZHANG Ji-shui, LU Min
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 81-86. DOI:10.13190/j.jbupt.2018-016
  • Abstract ( 482 )     HTML     　　
  • Potential high-value passengers can not be effectively discovered by airways due to the limited historical booking records of passengers. Aiming at this problem, a probabilistic model for discovering potential high-value passengers based on trip purposes mining is proposed. Firstly, we present a probabilistic model based on statistics to measure the value of passengers. Then, trip purposes are introduced into the model to discover potential airline demands of each passenger and to optimize passenger potential value calculation. Therefore, potential high-value passengers can be discovered through the trip purposes mining. Experiments show that the proposed model can identify the potential high-value passengers more accurately than the traditional passenger value evaluation methods based on the passengers' cumulative number of flight times, passengers' cumulative mileage and recency frequency monetry model.
  • References | Supplementary Material | Related Articles

  • Investigation on Spectral Aware Resource Allocation Technology Based on Spatial Channel Controlling
  • XIE Chao-chen, TAN Xiao-heng, LIU Qin, YANG Zhi-jun, LIU Yu-chuan
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 87-92. DOI:10.13190/j.jbupt.2018-146
  • Abstract ( 417 )     HTML     　　
  • Aiming at problem of lower utilization the authorized spectrum, due to channel quality and transmission power interference, a resource allocation technology was proposed based on the large scale antenna spatial channel controlling. Main lobes beam of multiple antenna beam forming points to the desired user and places the nulls in the interference direction, which can effectively suppress interference to secondary users and ensure that aware spectrum is used. As a result, the utilization ratio of frequency spectrum increased further in the whole system. The simulation results showed the throughput of the proposed method is better than the scheme in the literatures when signal to noise ratio is 5 dB and 10 dB.
  • References | Supplementary Material | Related Articles

  • Measurement and Modeling of Electromagnetic Noise in Industrial Environments
  • YUAN Ze, LIU Liu, ZHANG Kun
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 93-101. DOI:10.13190/j.jbupt.2018-127
  • Abstract ( 482 )     HTML     　　
  • Factory-level electromagnetic noise has a huge impact on industrial Internet of things which mainly uses low-power wireless sensor devices. For this reason, a log periodic antenna and a spectrum analyzer are used to measure the electromagnetic noise in the welding workshop and the office area of a car factory. We obtain the frequency, power and other information of electromagnetic noise in 0.3~3 GHz bands from the frequency domain measurement. The noise spectrum shows a spike shape, and the truncated Laplace distribution can be used for modeling. In time domain measurement, the noise data of 315 MHz, 779 MHz and 916 MHz are collected, and we also get the three parameters of amplitude probability distribution, pulse duration distribution and pulse separation distribution. The measurement results indicate that the results of horizontal and vertical polarization are similar. The influence of noise in the office area is less than that in the welding workshop.
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  • Algorithm for Least-Norm Inverse Kinematic Solution of Trinal-Branch Robotic Manipulator
  • HONG Lei, WANG Bao-sheng, CHEN Gang
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 102-108. DOI:10.13190/j.jbupt.2018-142
  • Abstract ( 449 )     HTML     　　
  • The inverse kinematics for trinal-branch robotic manipulator is researched based on the theory of linear equations set and conditional extremum, and an improved algorithm for least-norm inverse kinematics solution is proposed. The complicated calculation in conventional algorithm for the generalized inverse of Jacobian is avoided in this algorithm, especially, if the joint degree of each handling branch is equal to or more than the dimension of task space, a further simplified calculation can be obtained with the introduction of the Schimidt orthogonalization procedure. The proposed algorithm is of the higher real-time computation capacity than the common method, through the simulation of carrying a single object, the validity of the proposed algorithm is certificated.
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  • A Service Facility Placement Algorithm for the (p+m)-Median Problem
  • JIAO Ji-ping, LU Hai, HONG Xue-min, SHI Jiang-hong
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 109-113. DOI:10.13190/j.jbupt.2018-036
  • Abstract ( 311 )     HTML     　　
  • This service facility placement problem is investigated, which appears representatively in fog computing for the cost minimization and the optimal resource utilization. After the problem being modelled as a (p+m)-median problem, a novel heuristic placement algorithm is proposed that combines the greedy and tabu-search strategies. The proposed algorithm can be used in networks with arbitrary topology and random demand distribution. Analysis results show that it is polynomial in time complexity and can reach the optimal performance in the case that the number of the extended service nodes in the network is equal to that of the request nodes. Finally, simulations verify the advantages above.
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  • A News Recommendation Method Based on VSM and Bisecting K-means Clustering
  • YUAN Ren-jin, CHEN Gang, LI Feng, WEI Shuang-jian
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 114-119. DOI:10.13190/j.jbupt.2018-067
  • Abstract ( 531 )     HTML     　　
  • Personalized recommendation technology is a good solution to the problem of information overload. In order to improve the user's personalized experience of reading news, a news recommendation method based on the vector space model and Bisecting K-means clustering is proposed. Firstly, the news text vectorization is carried out:using the vector space model and TF-IDF algorithm to construct news feature vectors; then Bisecting K-means clustering algorithm is utilized to cluster the news feature vector set; after that, the clustered news set is divided into training set and test set, according to the training set, a "user-news category-news" three-level structure of the user interest model is built; finally, the cosine similarity method is used to calculate news recommendation results. The experiments are based on user-based collaborative filtering algorithm, item-based collaborative filtering algorithm, combined vector space model and K-means clustering recommendation method, and the results show that the proposed method is feasible, and the accuracy rate, recall rate and F value all have been improved.
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  • Data Pricing Mechanism Status and Development Trends
  • PENG Hui-bo, ZHOU Ya-jian
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 120-125. DOI:10.13190/j.jbupt.2018-108
  • Abstract ( 1094 )     HTML     　　
  • The construction of a data transaction mechanism centered on reasonable pricing has been discussed. Firstly, the well-known data transaction platforms at home and abroad has been introduced and the current data transaction pricing mechanisms can be summarized into four models:a protocol pricing model based on game theory, a third-party pricing model based on data characteristics, a tuple-based pricing model, and the pricing model of the query. Based on comparing the advantages and disadvantages of each model, combined with the relevant theory of data pricing, analyze the existing problems and discuss a method that is suitable for complex real-time trading environments which can accurately measure privacy and correctly evaluate the value of data.
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  • A Hybrid Recommendation Model Based on Fusion of Multi-Source Heterogeneous Data
  • JI Zhen-yan, PI Huai-yu, YAO Wei-na
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 126-132. DOI:10.13190/j.jbupt.2018-176
  • Abstract ( 495 )     HTML     　　
  • In order to reflect users' personalized preferences more comprehensively and improve the accuracy of recommendation, a hybrid recommendation model based on fusion of multi-source heterogeneous data is proposed. This model takes the impacts from both users' social relationships and reviews on ratings into account. Topics are extracted from reviews as user features and business features, and then communities are divided for users via a community discovery algorithm. Finally, a machine learning algorithm is used to model user communities in order to predict ratings. Businesses are ranked based on predicted ratings and then the top N businesses are recommended to the user. The experimental results show that the proposed hybrid recommendation model can improve the rating prediction accuracy and recommendation accuracy compared with the conventional recommendation algorithms.
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  • Detection of OAM State with Post Information Processing and Its Application in Communications
  • ZHAO Sheng-mei, ZHANG Wen-hao, YAO Hao, GU Xiao-fan, LI Wei
  • Journal of Beijing University of Posts and Telecommunications. 2019, 42(1): 133-138. DOI:10.13190/j.jbupt.2017-094
  • Abstract ( 366 )     HTML     　　
  • In order to effectively improve the detection efficiency of orbital angular momentum (OAM), we propose an OAM detection method based on post information processing. In the proposed detection method, a Mach-Zehnder interferometer is applied, and two doves are placed in each arm of the interferometer, where one is setup to 0 degree, and the other is rotated from 0 to 180 degree. The interference beam is received and the fast Fourier transform (FFT) is operated on the received signal. In the FFT domain, each OAM component is separated, named OAM spectrum. Numerical simulation results show that it is separable for one OAM mode, and multiplexed OAM mode by the proposed OAM detection method. Different from the general OAM separation method, the proposed method can obtain the OAM information by summarizing the total energy during a period in FFT domain. And the performance of the communication system can be improved by using this detection method.
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