Current Issue

• • 2021, Vol. 44 No. 6 Published date:28 December 2021 Last issue Next issue

  REVIEW

  • Satellite-Ground Fusion Intelligent Networking: Vision and Key Technologies
  • LIU Yang, PENG Mu-gen
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 1-12. DOI:10.13190/j.jbupt.2021-113
  • Abstract ( 1244 )     HTML( 956 )     　　
  • The satellite-ground fusion networks can not only meet the demands of emerging services such as auto-driving and large connections, but also be widely used in the disaster alarming and public safety applications. To serve ground applications with high efficiency and low delay for satellite ground fusion network, the key technologies of satellite-ground fusion intelligent networking are proposed. The technologies including networking architecture, data perception, access control, multi-dimensional network slicing, and time-sensitive routing and forwarding are then expounded in terms of principle and performance. Finally, the existing challenges and future directions are discussed.
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  PAPERS

  • A Feature Point Descriptor for Texture-Less Images
  • CHENG Peng-fei, ZHOU Xiu-zhuang, TANG Ling, WEI Shi-min, GAO Huan
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 13-19. DOI:10.13190/j.jbupt.2021-072
  • Abstract ( 1078 )     HTML( 625 )     　　
  • Most of the existing feature point extraction algorithms are suitable for processing images with rich texture, but they cannot extract effective feature points for texture-less images. To solve this problem, a new feature point descriptor, termed as multi-neighborhood structure tensor features (MNSTF) is proposed. The algorithm is based on a series of fixed neighborhoods and image structure tensors. By expressing the structure and texture information of local images, it solves the problems such as feature point extraction and matching in texture-less and non-texture scenes in existing feature point extraction algorithms. At the same time, by calculating the relative direction between neighborhoods, the rotation invariance of the MNSTF feature descriptor. The experimental results show that the accuracy of feature point matching of the MNSTF algorithm on the rotated texture-less image test set is over 99.9%, which verifies the good applicability, rotation invariance and robustness of the MNSTF feature descriptor.
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  • A Broadband Reflective Polarization Rotator
  • LIU Xiao-ming, QI Tao, GAN Lu
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 20-25,32. DOI:10.13190/j.jbupt.2021-035
  • Abstract ( 1156 )     HTML( 309 )     　　
  • To promote the application of polarization rotational devices in the fields of communication, radar and remote sensing, a polarization rotator based on periodical structure is designed. This design uses the skewed array consisting of split rectangular ring and rectangular patch, so that a reflective polarization rotator that can cover the frequency range of 22.5~50 GHz is realized. This device provides -3 dB fractional bandwidth up to 75.86%. The polarization conversion ratio reached 0.8 in the range of 24~47.8 GHz over an angular range of 30°. The measured results demonstrate satisfactory agreement with simulation.
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  • Throughput Fairness Guarantee in Cognitive Backscattering Networks
  • GAO Xiao-na, LU Guang-yue, YE Ying-hui, ZAN Jin-mei
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 26-32. DOI:10.13190/j.jbupt.2021-096
  • Abstract ( 410 )     HTML( 323 )     　　
  • To guarantee the throughput fairness among Internet of things (IoT) nodes in cognitive backscatter communication networks, a resource allocation scheme based on max-min criterion is proposed. Based on the dynamic circuit energy consumption model and the nonlinear energy harvesting model of IoT nodes, a non-convex multi-dimensional resource allocation problem is formulated, in which the communication capacity is maximized by jointly optimizing the transmitting power, reflection coefficient and time division. First, the contradiction, successive convex approximation and auxiliary variables method are used to transform the original problem into a convex optimization problem. Then, an iterative algorithm is proposed to solve the transformed problem. Simulation results show the proposed resource allocation scheme improves the communication capacity of IoT nodes while guaranteeing the throughput fairness among IoT nodes.
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  • Aircraft Elastic Wing Deformation Algorithm Based on Distributed Inertial Navigation Measurement
  • ZHANG Hua-qiang, LIU Lin, QIN Chang-li, CHEN Yu, SU Qing-hua
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 33-39,66. DOI:10.13190/j.jbupt.2021-052
  • Abstract ( 417 )     HTML( 263 )     　　
  • To deal with the difficulties in predicting elastic deformation of aircraft wrings during the flight, a distributed inertial navigation method for wing deformation measurement is proposed. First, the layout optimization of the critical test points on the wing is conducted based on the modal analysis and the thin plate model combined with the particle swarm optimization algorithm. Second, a relative motion inertial navigation calculating method is proposed by establishing the federated Kalman filter model for the estimation of the relative inertial navigation error. It achieves real-time alignment of each node under wing flexure deformation. Then, wing deformation is described by the positional information of multiple sub-nodes simultaneously. Finally, a wing loading test is conducted to verify the accuracy and effectiveness of the algorithm. The results show that the root means squares (RMSs) of the wing's three-directional position are 0.534 mm, 0.547 mm, 0.451 mm, respectively, and the RMSs of the wing's three-directional posture are 0.772', 2.87', 0.541', respectively. The results demonstrate that the proposed method has high estimation accuracy and good deformation monitoring ability in a dynamic environment.
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  • An Image Encryption Algorithm Combining S-Box and Chaotic Mapping
  • ZHANG Lei, CHEN Chuan, TAN Qi-yun, HAO Mao-xin, YANG Xue-kang
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 40-47. DOI:10.13190/j.jbupt.2021-061
  • Abstract ( 732 )     HTML( 411 )     　　
  • To solve the problems of low encryption quality and poor plaintext sensitivity in the existing image encryption algorithms, an image encryption algorithm combining S-box and chaotic mapping is proposed. The Hash value of the plaintext image is used to generate the key of the chaotic system, which can operate scrambling and diffusion. In addition, the S-box is generated through the Logistic chaotic system. By using the two-dimensional Logistic mapping and Chen chaotic system to generate two chaotic sequences, which have the same image size with the plaintext image, the algorithm operates exchange and the first-order diffusion for each pixel of the image. Then, the algorithm selects the S-box elements based on the chaotic sequences to do bit XOR and XNOR operations for each pixel value, and operates the second-order and third-order diffusion on all the pixels. Simulation results and security performance analysis show that, the proposed algorithm has good encryption effect, robustness and plaintext sensitivity, and thus it can resist various attacks.
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  • Closed-Form IA Solution Based on Ring-Typed Alignment Chain
  • LIU Wei-hua, WANG Zhong-fang, ZHANG Qiu-wen, XU Jin, DING Han-qing
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 48-52. DOI:10.13190/j.jbupt.2021-023
  • Abstract ( 346 )     HTML( 241 )     　　
  • To obtain the closed-form interference alignment (IA) solution for general interference networks, a novel closed-form IA solution method based on ring-typed alignment chain is proposed. Frist, the IA precoding matrices are decomposed into several sub-matrices, and the ring-typed alignment chains are elaborately designed by compressing the interference subspace as much as possible. Then, based on the ring-typed alignment chains, the IA precoding matrices and filtering matrices are computed by the matrix theory. Simulation results verify that the proposed method achieves high sum-rate performance with low computational complexity.
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  • Evaluation Method of Traditional Pattern Vector Diagram Based on Perception Drive
  • ZHAO Hai-ying, LI Huan-hong, HOU Xiao-gang
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 53-58. DOI:10.13190/j.jbupt.2021-097
  • Abstract ( 362 )     HTML( 235 )     　　
  • Aiming at the question of how to evaluate the quality of vector materials in the construction of the Chinese cultural vector material library, three visual evaluation indicators of accuracy, continuity and simplicity are proposed and quantitatively analyzed. First, the vector diagram is analyzed to obtain the document object model of the vector diagram, and the document tree is traversed to obtain the vector information. Then, by combining the Gestalt psychology, the visual error, curve continuity, and complexity of the decorative pattern of the vector diagramis quantified. Finally, an evaluation method based on perception-driven traditional pattern vector diagrams is proposed. The proposed algorithm provides three quantitative indicators that can be used for automatic evaluation, sorting and screening of vector diagrams in a multitask-driven vectorization system. Simulation results on the texture vector data set show that the evaluation results of the vector graphics meet the visual aesthetics and expectations of mainstream designs.
  • References | Supplementary Material | Related Articles

  • Communication Networks Fault Prediction Method Based on Sample Equalization and Feature Interaction
  • JIA Jun, FENG Chun-yan, XIA Hai-lun, ZHANG Tian-kui, LI Cheng-gang
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 59-66. DOI:10.13190/j.jbupt.2021-051
  • Abstract ( 474 )     HTML( 345 )     　　
  • To eliminate the inaccurate fault predictions caused by the imbalanced samples in the communication network fault prediction dataset, a communication network fault prediction method based on sample equalization and feature interaction is proposed. Wasserstein generative adversarial networks-gradient penalty (WGAN-GP) is used to generate new minority samples to solve the problem of sample imbalance in the alarm dataset. Then a memory based feature generation by convolutional neural network (M-FGCNN) model is proposed. The proposed model is based on multi-layer perceptron and convolutional neural networks to strengthen the interaction between features. Meanwhile, the expert experience in the alarm field is used to generate new alarm features based on factorization machine model. Further, a memory vector is introduced to the model's embedding matrix and the loss function is modified to improve the memorability of the proposed model. The experimental results based on the public unbalanced dataset verify that the WGAN-GP model can generate new data with better quality than the existing models. The experimental results also verify that the proposed M-FGCNN model can achieve better communication network fault prediction performance than other deep learning models.
  • References | Supplementary Material | Related Articles

  • Self-Localization Algorithm for Drifting-Restricted Underwater Acoustic Sensor Networks under Mixed Noise
  • HU Ke-yong, SONG Xiang-lin, GUO Xiao-lan, SUN Zhong-wei, SONG Chuan-wang
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 67-73. DOI:10.13190/j.jbupt.2021-016
  • Abstract ( 329 )     HTML( 207 )     　　
  • Existing localization algorithms for underwater acoustic sensor networks need the presence of beacon nodes and assume that measurement noises follow Gaussian distributions, resulting in high cost and low accuracy. To address these problems, a self-localization algorithm based on maximum a posteriori is proposed for drifting-restricted underwater acoustic sensor networks under mixed measurement noises. We analyze nodes' mobility patterns to obtain the prior knowledge for localization, and characterize distance measurements under the assumption of additive and multiplicative noises as the likelihood information for localization. Under the Bayesian framework, the priori and likelihood information are fused to derive localization objective function by maximum a posteriori probability. Then Broyden, Fletcher, Goldfarb and Shanno quasi-Newton method is resorted to solve the objective function. The simulation results show that compared with similar localization methods, the proposed method does not need the presence of beacon nodes, and it has the advantages of high localization accuracy, fast convergence speed, and being robust to changes in measurement noises.
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  • A Recognition Method for Radar Emitter Signals Based on Convolutional Neural Network with Multiple Learning Units
  • PU Yun-wei, GUO Jiang, LIU Tao-tao, WU Hai-xiao
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 74-82. DOI:10.13190/j.jbupt.2021-055
  • Abstract ( 657 )     HTML( 307 )     　　
  • Existing radar emitter signal recognition methods based on manually extract features have problems including low timeliness and poor recognition rate. To address these issues, a new recognition method based on a convolutional neural network with multiple learning units is proposed. First, the burr and distortion caused by noise of ambiguity function of emitter signals are corrected through the Gaussian smoothing. Then, the orthogonal slice is extracted as the further feature extraction objects. Finally, a convolutional neural network with multiple learning units is built to learn and extract the deep and ubiquitous features of the orthogonal slice, which are further classified through the softmax classifier. Simulation results show that the overall average recognition rate of six typical radar signals are all above 99.86% when the signal-to-noise ratio is -2 dB. The recognition rate can reach up to 88.50% when the signal-to-noise ratio is -6 dB. The results prove the good performance and feasibility of the proposed method when signal-to-noise ratiois extremely low.
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  • Hyperparameter Optimization of Convolutional Neural Network Based on Multi-Strategy MRFO Algorithm
  • LIU Yong-li, ZHU Ya-meng, CHAO Hao
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 83-88,95. DOI:10.13190/j.jbupt.2021-068
  • Abstract ( 540 )     HTML( 344 )     　　
  • The performance of convolutional neural network is closely related to the configuration of hyperparameters. However, the selection of optimal hyperparameters is time-consuming and labor-consuming. In order to improve the efficiency of hyperparameter selection, a multi-strategy manta ray foraging optimization algorithm is proposed. On the one hand, half uniform initialization strategy is adopted to improve population diversity. On the other hand, it combines new weight factor update strategy and splitting strategy to improve the convergence speed and fitting accuracy respectively. According to the real coding strategy, this algorithm is applied to the research of convolutional neural network hyperparameter optimization, which can be iterated according to three foraging methods to obtain the optimal hyperparameter configuration. In order to evaluate the effectiveness of hyperparameter optimization, the proposed algorithm is compared with the mainstream convolutional neural network hyperparameter optimization algorithms on mixed national institute of standards and technology and CIFAR-10 datasets. Experimental results show that the proposed algorithm achieves higher accuracy with less resources.
  • References | Supplementary Material | Related Articles

  • High-Performance UPF Prototype Based on VPP
  • LIU Yu, WEN Xiang-ming, WANG Lu-han, LU Zhao-ming, DU Ke-liang
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 89-95. DOI:10.13190/j.jbupt.2021-091
  • Abstract ( 1040 )     HTML( 741 )     　　
  • The fifth generation of mobile communications (5G) technology is expected to be flexible enough to meet the diverse requirements of future applications. Enabled by software defined network/network function virtualization, 5G network functions could be software running on general servers. But the performance will decrease compared to traditional dedicated hardware paradigm, especially for user plane functions (UPFs). In order to improve the performance of data processing in softwareized UPF, we design and implement a UPF prototype following vector packets processing (VPP) technology, which consists of packet forwarding control protocol module, open-source VPP module, and corresponding interfaces. Two experiments are constructed for the validation of its functionalities and performance. The results show that the proposed UPF can interconnect with commercial base station, commercial terminals, and open-source 5G core network. Meanwhile, its data throughput makes obvious improvement over Linux kernel-based approaches.
  • References | Supplementary Material | Related Articles

  • Agile AIOps Framework and Maintenance Data Quality Assessment Method
  • WU Zhen-yu, SHI Chang
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 96-102,133. DOI:10.13190/j.jbupt.2021-045
  • Abstract ( 571 )     HTML( 366 )     　　
  • An agile artificial intelligence for information technology operations(AIOps)framework and maintenance data quality assessment method are proposed. The agile AIOps framework advances the model construction stage to the test stage, and uses the monitoring data generated during the test stage to replace the data collected online to train the model, thereby realizing the early development and early use of intelligent operation. The maintenance data quality assessment method is based on the maximum mean discrepancy to evaluate the trend, stage, detectability, and diagnosability of training data for health assessment and fault diagnosis, so as to estimate the applicability of the data to the model. Based on the test environment provided by Huawei, the test cases are set up and the experimental data set is constructed. The experimental results on the data set verify the feasibility of the agile AIOps framework and the effectiveness of the data quality assessment method.
  • References | Supplementary Material | Related Articles

  REPORTS

  • A Multi-Value Prediction Location Privacy Protection Mechanism
  • SONG Cheng, JIN Tong, HE Jun-yi
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 103-108. DOI:10.13190/j.jbupt.2021-041
  • Abstract ( 990 )     HTML( 206 )     　　
  • To solve the security and efficiency issues in the existing location privacy protection schemes, a location privacy protection scheme based on Markov chain technology for multi-value predictive query is proposed. First, the state transition matrix is used to calculate the input multiple query values, and generate the predicted position and the query content at the next moment. Then, Bloom filter technology is adopted to establish a caching mechanism for points of interest. Security analyses demonstrate that the proposed scheme satisfies security features such as anonymity, unforgeability, and is able to resist to query service tracking. Simulation results show that the proposed scheme has higher execution efficiency, lower communication costs, and a higher cache hit rate, which can effectively reduce the number of interactions with the location based service server.
  • References | Supplementary Material | Related Articles

  • Neural Radiance Field by Joint Sampling
  • LIU Shao-hua, LI Ming-hao, LI Zhao-xin, MAO Tian-lu, LIU Jing
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 109-115. DOI:10.13190/j.jbupt.2021-095
  • Abstract ( 508 )     HTML( 398 )     　　
  • Compared with the traditional light field, the neural reflectance field (NeRF) method uses the neural network to fit the light sampling of scenes, which implicitly encodes the light field from input images to render novel view. However, NeRF method requires long training time and has slow rendering speed. To solve this problem, a joint sampling-based NeRF is proposed, which can make the coarse network and fine network share uniform sampling results, thereby accelerating the network training and view synthesis by reducing unnecessary light sampling. The experiments demonstrate that, in the case of the similar view synthesis quality, compared with the baseline method, the proposed method can reduce the training time by 20% and improve the view synthesis efficiency by 25%.
  • References | Supplementary Material | Related Articles

  • Construction of Heterogeneous Fractional Repetition Codes of Huffman Tree
  • YU Chun-lei, WANG Jing, YANG Cheng-fu, PENG Xiao-li
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 116-121. DOI:10.13190/j.jbupt.2021-026
  • Abstract ( 349 )     HTML( 226 )     　　
  • Considering access frequency differences of data in distributed storage systems, a heterogeneous variable fractional repetition (HVFR) code based on Huffman tree is proposed. First, taking the data blocks with different access frequencies as the weighted leaf nodes of the Huffman tree, the Huffman tree is constructed and the duplication of the data blocks is determined. Then, the pairwise balanced design is used to construct heterogeneous fractional repetition codes. Performance analysis and experimental results show that, compared with reed-solomon codes and simple regenerating codes, HVFR codes can significantly reduce the repair time and repair locality of the failed nodes, improves the parallel access speed of the hot data, and achieves load balance with low computation complexity.
  • References | Supplementary Material | Related Articles

  • Design and Realization of a Filtering Gysel Power Divider
  • YANG Yu-hao, WU Yong-le, WANG Wei-min
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 122-128. DOI:10.13190/j.jbupt.2021-080
  • Abstract ( 443 )     HTML( 259 )     　　
  • In order to improve the ability of the power divider to suppress useless signals, on the basis of the structural characteristics of the Gysel power divider, a brief and universal idea of filtering integration is put forward. A filtering Gysel power divider is designed and realized. According to the odd- and even-mode analysis method, the circuit decomposition is carried out to obtain the odd- and even-mode equivalent circuits which can be analyzed easily. The port admittances and impedances are solved by using the admittance matrixes, and S-parameter expressions are further constructed to describe the circuit characteristics of the proposed filtering Gysel power divider. Simulations are given to verify the correctness of the theoretical analysis. The measured results show that a filtering Gysel power divider, whose amplitudes of the reflection coefficients are less than -10 dB at the core band of the fifth-generation mobile communication system and the isolation is 17.38 dB at the center frequency, is realized. This Gysel power divider also achieves a good out-of-band suppression.
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  • Design of a Miniaturized Patch Antenna for WLAN
  • YANG Hui-chun, WANG Li-xia, TANG Sheng-chun, WEI Ying
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 129-133. DOI:10.13190/j.jbupt.2021-043
  • Abstract ( 451 )     HTML( 315 )     　　
  • To develop wireless local area network (WLAN)antennas for micro-small wireless devices, a 5 mm×5 mm micro patch antenna is designed on a 20 mm×20 mm FR4 dielectric substrate. In addition to the U-shaped radiation structure on the front of the patch antenna, two in-line loading units with one end grounded and the other open are added, while the reverse structure of the patch antenna is a mirror image of the front loading unit. Besides, the front micro-strip feeding method is adopted. The experimental results show that the antenna has good radiation characteristics in the 2.4~2.483 5 GHz frequency band, and its voltage standing wave ratio satisfies the requirements of miniaturized antenna engineering applications. Besides, the antenna has the advantages of simple and compact structure, low cost and easy integration with active circuits.
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  • Language Identification in Real Noisy Environments
  • SHAO Yu-bin, LIU Jing, LONG Hua, LI Yi-min
  • Journal of Beijing University of Posts and Telecommunications. 2021, 44(6): 134-140. DOI:10.13190/j.jbupt.2021-053
  • Abstract ( 428 )     HTML( 325 )     　　
  • Language identification is heavily influenced by the real noise environment, resulting in poor identification results. To solve this problem, an image processing method for language identification is proposed based on the logarithmic gray-scale speech spectrogram. The logarithmic gray-scale speech spectrogram is obtained by combining the human auditory properties and the voice filtered in real noise environments according to the different distribution of noise and speech on the speech spectrogram. Then, the principal component of the spectrogram is extracted as language features and, a residual neural network model is used for training and testing. Experimental results show that the average identification rate of the proposed method is improved by 27.5% in the noisy cockpit of a Blackburn Buccaneer compared to the linear grey-scale speech spectrogram method. In other noisy environments, the average identification rate is also improved.
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