Current Issue

• • 2023, Vol. 46 No. 1 Published date:28 February 2023 Last issue Next issue

  • Spectrum Sharing Strategy in Multi-Buyer System
  • YIN Zhining, LIU Wenjun
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 1-5.
  • Abstract ( 349 )     　　
  • Dynamic spectrum sharing introduces intra-frequency interferences and security problems, while traditional static spectrum sharing is facing the issue of low spectrum utilization rate. To introduce an interference-free, secure and efficient spectrum sharing strategy,a newsboy model applied to static spectrum sharing strategy is proposed for multi-buyer systems. Since the newsboy strategy considers the service demand as a dynamic procedure, the leasing strategy has to be adjusted periodically. Within one leasing cycle,the theoretical analysis shows how the newsboy strategy is used. The simulation results present the exact values of the optimal leasing cycle,the optimal requested spectrum quantity,and the optimal user service price coefficient under the premise of simulation. Compared with the traditional static spectrum sharing strategy,the newsboy strategy can achieve higher system profit and spectrum efficiency without introducing additional issues.
    
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  • GNSS Pre-Detection Signal Modeling Method and Viterbi-Based Frequency Tracking Algorithm
  • ZHANG Honglun, LU Mingquan
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 6-11.
  • Abstract ( 264 )     　　
  • The mathematical models of intermediate frequency and zero intermediate global navigation satellite system (GNSS) signal are deduced. The pre-detection GNSS signal model is further proposed. A unified method is proposed to add noise for the three signal models. The theoretical analysis and simulation results show that the simulation platforms based on the three model are equivalent. The pre-detection simulation platform reduces the data sampling rate to about 1 000 Hz and reduces the amount of computation, and the simulation efficiency is improved. A frequency tracking scheme based on Viterbi algorithm is proposed, in which the frequency is estimated by traceback approach. This tracking scheme is verified on the pre-detection simulation platform and the results show that the proposed method can track GNSS signal for a carrier-to-noise ratio of 10 dBHz in static scene.
    
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  • A Personalized Federated Learning Algorithm Based on Meta-Learning and Knowledge Distillation
  • SUN Yanhua, SHI Yahui, WANG Zhuwei, LI Meng, SI Pengbo
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 12-18.
  • Abstract ( 611 )     　　
  • In federated learning (FL),the distribution of data in clients is always heterogeneous,which makes the unified model trained in FL unable to meet the demand of each client. To combat this issue, a personalized federated learning algorithm with meta learning and knowledge distillation is proposed,in which the knowledge distillation and meta-learning with FL and incorporating the personalization are combined into the training of FL. In each global iteration,the global model(teacher model) update itself according to the feedback from the local model ( student model) during the knowledge distillation. Therefore,each client can obtain a better personalized model. Simulation results show that compared with the existing personalized algorithms, the proposed algorithm can achieve a better compromise between global accuracy and personalization accuracy while improving the personalization accuracy.
    
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  • Image Inpainting Algorithm with Diverse Aggregation of Contextual Information
  • LI Haiyan, CHAO Yanjing, YU Pengfei, LI Haijiang, ZHANG Yufeng
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 19-25.
  • Abstract ( 251 )     　　
  • To effectively solve the defects of structural distortion and blurry texture when repairing large and irregular semantic missing area images by using the existing algorithms, a diverse aggregation image restoration algorithm based on contextual information is proposed. First,the information on the damaged image is extracted by the encoder to estimate the missing content. Thereafter, the context information from various receptive fields is merged through the multi-information aggregation block to enhance the structure and texture information of the missing area. Then, the original image features are restored through the decoder. Finally, the mask matching discriminator is adopted to perform discrimination training on the generated image,and the model is optimized by combining the counter loss, reconstruction loss,perception loss and style loss to promote the generator to synthesize clear textures. The proposed algorithm is trained and tested on the public data set. The experimental results show that the proposed algorithm can obtain clearer and more reasonable structure and texture details than state-of-the-art when inpainting randomly irregular and large missing areas. Its objective indices such as peak signal-to-noise ratio and structural similarity are superior over the compared algorithms.
    
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  • Retinal Blood Vessel Segmentation Based on Transformer and MLP
  • RONG Zhenyu, LIU Jianyi
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 26-31.
  • Abstract ( 517 )     　　
  • To solve the problem of poor segmentation effect, data over-fitting, and imbalance of positive and negative samples in fundus blood vessel segmentation, a retinal blood vessel segmentation algorithm based on transformer architecture (Transformer) and multilayer perceptron (MLP) is proposed. First, data augmentation is used on training images to prevent over-fitting. Then,several transformers fused with convolution modules are used as a robust encoder to gain multi-scale feature information. Finally, a decoder consisting of MLP is adopted to complete pixel-level classification on a feature map. In addition, the combination of Tversky loss and binary cross-entropy loss is applied to solve the sample imbalance problem. Experiential results on various datasets indicate that the proposed algorithm has a good performance,which is better than other existing algorithms.
    
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  • Recognition of Major Depressive Disorder Based on Facial Behavior and Speech Fusion Features
  • LI Jinlong, CHEN Qiongqiong, DING Zhijie, LIU Zhenyu
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 32-37.
  • Abstract ( 329 )     　　
  • In response to the urgent need to realize computer-assisted automatic depression recognition, a major depressive disorder recognition study based on facial behavior and speech features for the Chinese population has been carried out. First, 72 samples conforming to the research conditions are selected from the constructed depression data set for analysis. Then, the facial activity and speech data are decomposed into different frequency components by using the variational modal decomposition method, and the feature set is constructed by analyzing the energy distribution of different frequency bands. Finally, depression recognition is achieved by using the voting decisions of several classifiers. The experimental results show that the recognition accuracy of the male group can reach 81.1% , and the recognition accuracy of the female group can reach 78.7% . Under the premise of protecting the privacy of the subjects, higher
    classification results are obtained.
    
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  • Language Recognition Based on Log Gammatone-Scale Filter Bank Energies Spectrograms
  • ZHANG Haoge, SHAO Yubin, LONG Hua, PENG Yi, ZHOU Dachun
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 38-43.
  • Abstract ( 203 )     　　
  • To solve the low recognition rate issue of language recognition in noisy environment,a language recognition method based on the log Gammatone-scale filter bank energies is proposed. First the log Gammatone-scale filter bank energies features are extracted based on the auditory features of the Gammatone filter-banks, and the features are transformed into images to obtain feature spectrograms. Then, the dark channel prior is applied to enhance and denoise the images. Finally,the residual neural network model is used for training and recognition. Experimental results show that when the signal-to-noise ratio is 0 dB, and the noise sources are white noise,volvo noise and pink noise,the recognition rate of the proposed method is improved by 32.7% ,10.1% and 29.1% , respectively, compared with the linear gray-scale spectrogram,and the recognition rate under other signal-to-noise ratios is also improved.
    
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  • Certificateless Threshold-Based Conditional Proxy Re-Encryption Scheme
  • LI Zhaobin, ZHANG Lu, ZHAO Hong, WEI Zhanzhen
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 44-49,83.
  • Abstract ( 292 )     　　

  • Conditional proxy re-encryption can grant fine-grained authorization to ciphertext according to conditional information. Most of the existing conditional proxy re-encryption schemes are based on traditional public key infrastructure or identity public key, therefore bringing the problems of certificate management and key escrow. To solve these problems, a new certificateless threshold conditional proxy re-encryption scheme is constructed, in which the conditional information is added when the original ciphertext and re-encryption key are generated, and the proxy node verifies the condition compliance before re-encryption to ensure that only the matching ciphertext can be re-encrypted. Threshold technology is used to protect re-encryption key and private key. Theoretical analysis shows that the proposed scheme is able to resist two types of adversary attacks,the first type-I adversary replaces the user's public key and the type-II adversary holds the system's master key.  The simulation results demonstrate that the proposed scheme has high efficiency in key operations such as re-encryption key generation and re-encryption, therefore, providing the basis for ciphertext sharing in applications such as distributed cloud storage.

    
    
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  • High Dynamic Dual Binary Offset Carrier Signal Acquisition in Narrowband Interference Environment
  • ZHANG Tianqi, FANG Zhu, WANG Xueyi, WANG Rui
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 50-56.
  • Abstract ( 165 )     　　
  • To solve the difficulty in capturing highly dynamic double-binary offset carrier signals in narrowband interference environment, a capture algorithm combining singular value decomposition, the minimum description length criterion, discrete polynomial phase transformation, partial matching filter and fractional Fourier transform plus spectrum correction is proposed. First, the singular value decomposition is used to divide the signal containing narrowband interference into signal subspace and interference subspace, and the minimum description length criterion is used to determine the boundary between target signal and interference signal, and the interference suppression is adaptively completed. Then, the order algorithm is used to determine the dynamic order of the signal to complete the downgrading. Finally the capture of the signal containing only the first-order Doppler rate of change is completed. The simulation results show that the proposed algorithm can easily complete the precise suppression of interference while retaining the original signal characteristics, and the performance is stable. In addition, the proposed capture algorithm improves the capture probability by about 2 dB gain compared with uncorrected under the same conditions
    
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  • Design of Miniaturized Tri-Reflector Compact Antenna Test Range Based on Rolled Edges Structure
  • LI Zhi, YAO Yuan, ZHANG Liang, YU Junsheng, CHEN Xiaodong
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 57-62.
  • Abstract ( 289 )     　　
  • To reduce the influence of electromagnetic wave edge diffraction on the quiet zone of the small-aperture reflector compact antenna test range system, and solve the system’s low cross-polarization isolation issue in the millimeter-wave and terahertz frequency bands, a design scheme of miniaturized tri-reflector compact antenna test range, whose main mirror processed by rolled edges, is proposed. Three reflector structure configuration is adopted to improve the system’s cross-polarization isolation, and the width of the quiet zone is adjusted by the expected exit near-field intensity distribution function. Meanwhile, the method of increasing feed edge taper and adding rolled edges are adopted to achieve the purpose of smaller amplitude and phase ripples. In addition, the method of coordinate transformation matrix is also introduced to simplify the design process of the rolled edges. The simulation results show that the compact antenna test range system can achieve better quiet zone performance by adopting the proposed miniaturized tri-reflector design scheme based on rolled edges structure.
    
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  • Blockchain-Oriented Key Management Scheme for Aeronautical Ad Hoc Networks
  • ZHOU Jingxian, LIU Huiyue, ZHOU Yajian, LYU Zongping
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 63-68.
  • Abstract ( 222 )     　　
  • The existing aeronautical ad hoc network key management scheme relies heavily on trusted centers or infrastructure, resulting in low key management efficiency and low key security. In order to realize the secure information communication between aircraft nodes in high-speed dynamic radio communication links in aviation ad hoc network scenarios, a key management scheme based on blockchain aeronautical ad hoc network is proposed. The proposed scheme can be ensured the security and flexibility of key management by using key cryptography technology and improved key agreement protocol for secure generation and distribution of key pairs. Meanwhile, the verification and addition of public key data, as well as automatic public key storage and revocation operations can be achieved through the smart contract of the blockchain, so as to improve the efficiency and fairness of key management. The performance evaluation results that the proposed scheme is superior to the traditional aeronautical ad hoc network key management scheme in terms of communication consumption and computing consumption.
    
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  • UAV security communication algorithm with Intelligent Reflecting Surface and cooperative Jamming
  • LI Zineng, HU Zhiqun, XIAO Hailin, ZENG Zhangfan
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 69-76.
  • Abstract ( 382 )     　　
  • In order to further enhance the secrecy rate of the unmanned aerial vehicle ( UAV ) communication system, a UAV security communication system base on intelligent reflecting surface(IRS) and cooperative jamming is proposed. By using an IRS to dynamically strengthen the backhaul link and introducing artificial noise through a cooperative UAV to interfere with a illegal eavesdropper, the security of UAV communication system can be improved from the aspect of physical layer security. Considering the trajectory of the source UAV, the trajectory of the jamming UAV, the power control and the phase shift of IRS, a joint optimization problem is proposed with the goal of maximizing the security of the system. An alternate optimization algorithm is proposed, which turns the original problem into four sub-problems, and converts the original non-convex problem into approximately convex sub-problems through successive convex approximation and semidefinite relaxation technique, so that it can be solved directly by convex optimization tools. The simulation results show that the proposed optimization algorithm can converge quickly. Compared with the traditional non-intelligent reflector-assisted communication network, the proposed algorithm can significantly improve the security rate of the system.
    
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  • Resource and Trajectory Optimal Design for Unmanned Aerial Vehicles Full Duplex Two-Way Relay
  • ZHOU Lihui, XIAO Lin, WU Fahui, YANG Dingcheng, WANG Yapeng
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 77-83.
  • Abstract ( 325 )     　　
  • Unmanned aerial vehicles have the advantages of on-demand deployment, high mobility and flexibility. The unmanned aerial vehicles-based full-duplex two-way relay network can further improve the coverage of the relay and enhance the communication performance. Therefore, the unmanned aerial vehicles assisted multi-pair ground users are considered to carry out two-way relay communication, and the average minimum reachable rate between user pairs is maximized by jointly optimizing unmanned aerial vehicles’ trajectory, user scheduling and power distribution. An iterative solution algorithm is proposed based on block coordinate descent and continuous convex approximation. Simulation results show that the proposed algorithm can effectively improve the system performance.
    
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  • Parameters Estimation of Quadrature Multiplexing Binary Offset Carrier Signal
  • WU Chao, ZHANG Tianqi, XIONG Tian, WEN Bin
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 84-89.
  • Abstract ( 181 )     　　
  • In the low signal-to-noise ratio environment, the problem of multi-parameter blind estimation for quadrature multiplexed binary offset carrier ( QMBOC) signals is existed. To solve this problem, a cyclic spectral estimation algorithm is proposed based on frequency domain cumulative averaging. First, the cyclic autocorrelation function of QMBOC signal is obtained from the signal model. The cyclic autocorrelation function is equivalent to the sum of the cyclic autocorrelation function of two subsignals. Then the cyclic autocorrelation function is used to derive the cyclic spectrum by Fourier transform, and the cyclic spectrum is averaged by frequency domain accumulation. Finally, the spectral peak is searched to realize the blind estimation of pseudo-code rate, subcarrier rate and carrier frequency according to the spectral line characteristics of the cyclic frequency section of QMBOC signal. The experimental results show that the proposed algorithm can effectively estimate multiple parameters of QMBOC signal at - 9.5 dB.
    
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  • WSN Localization Algorithm Based on Temporary Best and Worst Centroid Opposite Cross Mutation and Sparrow Optimization
  • YU Xiuwu, SHANG Yadong, LIU Yong
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 90-96.
  • Abstract ( 172 )     　　
  • To solve the issues of that swarm intelligence optimization algorithm has low iterative efficiency and is easy to fall into local optimum in wireless sensor network ( WSN) localization, WSN localization algorithm is proposed based on temporary best and worst centroid opposite cross mutation and sparrow optimization. The algorithm uses the estimated distance of nodes to build a box model, determine the location area of the initial node, and narrow the scope of the previous search area, The Circle chaotic map is used to initialize the population and make the population distribution more uniform. A reverse learning strategy of temporary best and worst centroid is proposed to make full use of the search experience of the population while maintaining the diversity of the population. By combining the cross mutation strategy, the proposed algorithm is easier to jump out of the local optimum, which improves the efficiency of global search. The simulation results show that the proposed algorithm has better positioning accuracy and convergence efficiency.
    
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  • Face Clustering Algorithm Based on Key Links Discovery of Affinity Graph
  • HUANG Yuezhen, DAI Jingguo, ZHANG Chengye, WEI Dong
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 97-102.
  • Abstract ( 175 )     　　
  • In real scenes, unknown number of categories, unbalanced number of samples and complex data distribution can lead to low accuracy of intelligent face image extraction. To solve these problems, a face image clustering algorithm based on the discovery of key edges of association graph is proposed. First, the algorithm merges features of image samples extracted by multiple convolution neural networks to obtain new feature vectors with stronger capability of identification, and then calculates the similarity between different samples. Then, an appropriate threshold value is set for the rejection rate and the recognition rate, and the similarity result obtained in the previous stage is compared with the threshold value. The sample pairs with high similarity degree are screened out, and the association graph is constructed by adding the connecting edge between the above sample pairs. Using the intermediate number centrality measure, the key edge discovery method is designed to dig the important connecting edges that may connect different clusters in the association graph. Finally, the graph convolution network is used to confirm the existence of the above important connection edges, such that the final cluster is obtained. Experimental results show that the proposed algorithm can improve the accuracy of face image
    clustering.
    
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  • High-Precision and Low-Cost Timing Method of Mobile Cellular Network
  • ZHANG Chenyu, WEN Xiangming, CHEN Yawen
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 103-108.
  • Abstract ( 215 )     　　
  • Traditional network timing and satellite timing methods are restricted by timing accuracy and deployment environment. It is challenging to meet the demands of mobile network services for high-precision synchronization. To solve this problem, a design based on the low-cost baseband timing module for mobile terminals is proposed. A prototype consisting of software-defined radio-based 5G base station and Zhanrui module is implemented. An end-to-end error source model, principle and implementation of the network timing technology based on the air interface physical layer signal are defined. Issues including the air interface delay compensation method, error perception method and the robust statistical compensation method are discussed so as to achieve sub-microsecond synchronization accuracy in the mobile network. The experimental results show that the single-time timing accuracy is better than  10 - 7 s.
    
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  • Multi-Carrier Information Hiding Algorithm Based on Vertex Partition of 3D Model
  • REN Shuai, LEI Xuemei, DAN Zhuoyi, HE Xiao, SHI Lei
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 109-114,126.
  • Abstract ( 223 )     　　
  • To improve the robustness of information hiding on a single 3D model carrier, a multi carrier information hiding algorithm based on vertex partition of 3D model is proposed. Each 3D model is transformed into geometric invariant space, and multiple models are combined to form a multi-carrier fusion state by adjusting vertex normal vectors. The fused vertices are divided into feature points according to root mean square curvature. The fused vertex coordinates are sector partitioned, and secret information is hidden by changing the polar coordinates of feature vertices in the partition. Experimental results show that the proposed algorithm can resist attacks on 3D models such as simplification, clipping, noise and smoothing, and its robustness is significantly improved.
    
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  • Rigid Body Localization Based on Time Domain Measurement in Non-Line-of-Sight Environment
  • WAN Pengwu, WEI Jian, YAO Yuanyuan, PENG Kang, LI Wenjie
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 115-120.
  • Abstract ( 196 )     　　
  • To improve the accuracy of the rigid body localization in non-line-of-sight environments, the method of rigid body localization using time domain information of wireless signals is proprosed to overcome the influence of non-line-of-sight errors in the localization performance. First, the non-line-of-sight deviation is introduced as an auxiliary variable to transform the rigid body sensor position estimation into a generalized trust region sub-problem. Then, the position of the rigid body sensor is estimated by the bisection method. Finally, the position and the orientation of the rigid body are calculated according to the singular value decomposition. Simulation results demonstrate that the proposed method performs well in terms of the localization performance.
    
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  • A Binary Fuzzy Test Method for UEFI DXE Drivers
  • LONG Xiang, CUI Baojiang, WU Jiatong
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(1): 121-126.
  • Abstract ( 369 )     　　
  • To simplify the binary security analysis process of existing unified extensible firmware interface driver execution environment ( UEFI DXE) driver, a fuzzing method for UEFI DXE binary based on dependency analysis and call hijacking is proposed. A driver emulation technology and a gray-box fuzzing method based on call guidance and on-the-fly detection is also proposed. The experiment results show that all types of vulnerabilities can be detected on the public evaluation sample set and verified on the UEFI DXE firmware with known common vulnerabilities & exposures. Moreover, the proposed method can achieve higher code coverage with fewer pre-requisites.
    
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