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• • 2023, Vol. 46 No. 4 Published date:28 August 2023 Last issue Next issue

  • Design of a High-Selectivity Absorptive Dual-Band Balanced Bandpass Filter
  • ZHANG Yifan, WU Yongle, WANG Qing, WANG Weimin
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 1-8.
  • Abstract ( 175 )     　　
  • A high-selectivity dual-band balanced bandpass filter is proposed, which can achieve wideband common-mode noise suppression and absorption. Two operational frequencies can be adjusted by the impedances of coupled-lines. Transmission zeros and bandwidths can be controlled by changing the electrical lengths of coupled-lines and loaded stubs. The filter can realize the wideband common-mode noise absorption and suppression by loading four grounded resistors. A dual-band balanced bandpass filter centered at 710 MHz and 2.37 GHz is fabricated for demonstration. The measured results indicate that the balanced bandpass filter has good differential-mode filtering performance with multiple transmission zeros. The common-mode suppression is better than 28 dB from 0 to 4.04 GHz. The common-mode noise absorption is better than 10 dB from 0 to 3.67 GHz, and the absorption rate of common-mode noise is greater than 90% from 0 to 4.37 GHz, which indicates significant improvements in term of common-mode noise elimination.
    
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  • Test Suite Reduction Method Based on Hierarchical Clustering
  • ZHU Ruiwen, WANG Yawen, LIN Huan, LI Shuaiyun, WU Yanfang
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 9-14.
  • Abstract ( 116 )     　　
  • To reduce the loss of fault detection capability during the test suite reduction process and to minimize the negative impact of the coincidental correctness on test adequacy. A test suite reduction method is proposed based on hierarchical clustering, which uses Euclidean distance to calculate the similarity of test cases and derives the dissimilarity matrix as the input for clustering. In addition, based on the property that mutation testing can improve the fault detection ability of test suite, a formula for calculating the probability of coincidental correctness is given. The reduced test suite are obtained in the resultant clusters using the mutation testing-based test case selection algorithm. The experimental results show that the proposed method reduces the loss of fault detection capability by 9.8% and 12% compared to adequate and other inadequate test suite reduction methods, respectively.
    
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  • Method on Millimeter Wave Cascade Channel Estimation Assisted by Multiple Intelligent Reflecting Surface
  • LI Minzheng, CAO Yuqing, YAN Juanjuan, LU Jian
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 15-20.
  • Abstract ( 162 )     　　
  • Aiming at the problems of complex channel coupling, large channel scale, large pilot cost and difficult estimation of multi-hop cascade channel estimation in the millimeter wave communication system assisted by multiple intelligent reflecting surfaces(IRS), an efficient cascade channel estimation method is proposed based on compressed sensing theory. Firstly, based on the inherent sparsity of millimeter wave channel, the sparse representation of a large-scale multi hop cascade channel is found by using the properties of Katri-Rao and Kronecker product. Then, the large-scale cascade channel estimation problem is transformed into the recovery problem of multiple sparse signals. Finally, an improved OMP algorithm is used to recover the large-scale cascade channel. Simulation results show that the proposed method can greatly reduce the pilot cost of multi hop cascade channel estimation, and can accurately estimate the state information of multi hop cascade channel.
    
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  • Adaptive federated filtering algorithm based on multi-sensor redundant data cooperative tracking
  • LIU Jinming, ZHANG Biling, ZHANG Yuyan
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 21-26.
  • Abstract ( 107 )     　　
  • In order to make full use of redundant data of multiple sensors to achieve high-precision tracking, an redundant data adaptive federated Kalman filter algorithm with outlier detection is proposed based on redundant measurement data. First, in the information distribution stage, an adaptive information sharing factor is designed for redundant information, which improves the information distribution efficiency. Secondly, in the information fusion stage, in order to reduce the influence of error data on tracking results, an outlier detection algorithm is proposed, which combines the judgment results of all filters through D-S evidence theory to evaluate whether the data is outlier data. Finally, the linear least square method is used to fuse and obtain a more accurate final estimation result. The simulation results show the proposed algorithm has better tracking accuracy and robustness than the existing models.  
    
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  • Blockchain-Based Data Storage Model for Land Survey
  • SONG Luona, LU Zikui, DENG Qing, ZHANG Qiang, WANG Xiaojuan
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 27-31,39.
  • Abstract ( 125 )     　　
  • Aiming at the problem that the data in the land surveying and mapping scene is difficult to trace and tamper with, a land data storage model based on the blockchain is proposed. The proposed model can realize the on-chain storage of land survey data and the association retrieval of on-chain and off-chain data. First, chain-uploading compression algorithm is designed for land surveying and mapping data. Then, a distributed digital fingerprint extraction method based on distributed slice storage and erasure code is proposed, and the extraction method is optimized concurrently to speed up the digital fingerprint extraction process and improve the chain-uploading efficiency. Finally, the on-chain and off-chain data association is introduced to further ensure data security. The simulation results show that the proposed model can save storage space effectively, prevent data tampering, achieve efficient upload of large-scale point cloud data, and improve data security and credibility.
    
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  • Visible Light Communication Assisted Perspective Circle and Lines Positioning Algorithm Based on A Single Light Source
  • BAO Rongzhen, ZHU Zhiyu, YANG Yang, FENG Chunyan
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 32-39.
  • Abstract ( 106 )     　　
  • Traditional visible light positioning algorithms usually require multiple light sources to achieve positioning, which limits the practical application of visible light positioning. Aiming at the challenge, a visible light communication assisted perspective circle and lines positioning algorithm based on a single light source is proposed to achieve high-precision positioning. First, a single circular emitting diode (LED)is used as the transmitter to transmit the positioning information to the receiver based on visible light communication. Then, the receiver captures the line features of the ceiling plane and the circle feature of the LED to obtain the orientation and coordinate of the LED in the camera coordinate system. Finally, the pose and position of the receiver in the world coordinate system can be obtained according to the positioning information. The proposed algorithm can achieve accurate three dimensions positioning using a single light source and a camera without tilting angle limitation. The simulation results show that when the radius of the LED is 13 cm, the positioning error of more than 95% of the simulated sample points is within 10 cm by using the proposed algorithm. The experimental results show that the positioning errors are within 10 cm by using the proposed algorithm.
    
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  • A Truth-Oriented Trust Evaluation Model of Shared Messages about Road Events in Internet of Vehicles
  • ZHANG Jiamin, SHUAI Lisha, DONG Gaoya, YANG Xiaolong
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 40-45.
  • Abstract ( 118 )     　　
  • In the Internet of vehicles, the reliability of road condition message shared between vehicles is the key decision-making basis for the efficiency of transportation and the safety of drivers and passengers. To this end, a multi-dimensional collaborative trust evaluation model for shared message based on road facts is proposed, which is based on the concept of “understanding what they say, observing what they do, and emphasizing facts”. In the entity dimension, the entity trust value is calculated according to the trust value of the vehicles acted as sender and evaluator, which overcomes the limitation of inaccurate trust value caused by ignoring the evaluator role of the entity. In the behavior dimension, to achieve a fair evaluation of vehicles with different message records and frequency of real provision, the behavior trust value of the vehicles is calculated according to the sharing rate and honest forwarding rate to the event. In the fact dimension, the fact-centered trust correction is defined to correct misjudgment of the non-subjective malicious behavior of honest vehicles. The simulation results show that the proposed model can accurately and fairly evaluate the credibility of messages, which contributes to suppress the spread of false messages.
    
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  • Information-Aware Layered Weighted Interference Cancellation Coded Caching
  • WANG Pu, LIU Chao, BAO Jianrong, JIANG Bin
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 46-51.
  • Abstract ( 67 )     　　

  • An information-aware hierarchical weighted interference cancellation coded caching scheme is proposed for multiple relay systems to eliminate the interference of unrequested subfiles and improve the degrees-of-freedom of the system. The proposed scheme divides the system into subsystems  I and II  to minimize link load and improve the degrees-of-freedom according to the cache capacities of the user and relays, and the number of users and files by jointly designing weighted interference cancellation, orthogonal unicast scheme, and decentralized coded caching scheme. In subsystem I, when subfiles are more than users in the single interference-free transmission, the unicast is introduced to achieve additional degrees-of-freedom compared to the traditional interference cancellation. In subsystem II , the multi-relay cooperative coded transmission is proposed to reduce massive steps of the delivery and improve the system degrees-of-freedom. Simulation results show that when the number of subfiles is less than that of users in a single interference-free transmission, the system degrees-of-freedom obtained by the proposed scheme is better than that of the traditional orthogonal unicast scheme, and can achieve more than 1.3 times system degrees-of-freedom gains. In addition, it also achieves about 10.6% degrees-of-freedom gains compared with that of the traditional interference cancellation scheme.

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  • An iterative channel parameters estimation algorithm in OTFS systems
  • CHANG Qiqing, WANG Sen, JIN Jing, LI Yixiao, LONG Hang
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 52-57.
  • Abstract ( 229 )     　　
  • An iterative channel estimation algorithm in time-frequency domain based on orthogonal time and frequency space (OTFS) system is proposed for time-frequency dual selection channel environment with high delay and high Doppler offset. Using the property that channel matrix in time-frequency domain can be expressed as the product of Doppler offset matrix, channel complex gain matrix and delay matrix, the estimation results of Doppler offset and delay parameters of each path are updated iteratively to improve the accuracy of each parameter estimation. The channel matrix in the time-frequency domain is calculated according to the parameter estimation results, which is directly used in the time-frequency domain equalizer to reduce the complexity of the receiver. Simulation results show that the proposed algorithm can significantly improve the performance of channel estimation, support more flexible reference signal configuration, and reduce transmission overhead.
    
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  • Lightweight Chinese Lipreading Model and Dataset Construction
  • SUN Baosheng, XIE Dongliang
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 58-63.
  • Abstract ( 114 )     　　
  • In order to promote the rapid development and practical application of Chinese lipreading, a lightweight lipreading model is proposed based on the combination of interleaved group convolution and dilated convolution. In the proposed model, the interleaved group convolution is taken to learn the correlation between different features and the dilated convolution is taken to expand the model receptive field, which greatly reduces the amount and complexity of model parameter and improves the accuracy of model recognition. In addition, the largest sentence-level Chinese lipreading dataset is recorded in a controlled environment to enrich the Chinese lipreading dataset. The applicability of the lightweight lipreading model is verified on the recorded datasets and public datasets. The learning ability of the model to the video frame and text mapping relationship is analyzed visually through the heatmap.
    
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  • Alternate Optimization Beamforming Method for Downlink RIS-NOMA System
  • PENG Yi, WU Tong, YANG Qingqing
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 64-69.
  • Abstract ( 96 )     　　
  • In order to maximize the weighted sum rate of the multi-input single-output non-orthogonal multiple access ( NOMA ) communication system assisted by the reconfigurable intelligent surface ( RIS) , a method combining fractional programming and successive convex approximation is proposed to alternatively optimize active and passive beamforming. First, the weighted sum rate problem is transformed into a fractional problem by fractional programming and the signal and noise power are decoupled. Then, the active and passive beamforming are alternately optimized by the Lagrange multiplier method and successive convex approximation, respectively. Thus, the nonconvex problem of maximizing the weighted sum rate is decomposed into multiple convex optimization problems. Finally, the optimal solution of active beamforming and the suboptimal solution of passive beamforming are obtained. The simulation results show that the proposed method can effectively solve the beamforming problem in the RIS-NOMA communication system and users can obtain an ideal rate increase.
    
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  • Multi-Scale Feature Transformer Based Fine-Grained Image Classification Method
  • ZHANG Tiankui, CAI Changli, LUO Xiaoliang, ZHU Yutao
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 70-75.
  • Abstract ( 273 )     　　
  • Aiming at the long-tail distribution problem of fine-grained image classification task, a multi-scale feature Transformer based fine-grained image classification method is proposed to protect the underlying and deep features and optimize the long-tail distribution. First, a hybrid data sampling method is designed to obtain the ternary data for optimizing the representation learning, long-tail distribution and fine-grained features. Then, the Transformer multi-scale feature optimization method is designed to optimize the feature learning process by the bottom feature comparison learning method and the deep feature balance learning method, respectively, to improve the category confusion and fine-grained feature extraction, and to increase the attention to the tail category while protecting the head category feature learning. Simulation results show that the proposed method can effectively improve the impact of the long-tail distribution in fine-grained image classification tasks, optimize the feature distribution, and improve classification accuracy.
    
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  • An SCL-Flip Decoding Algorithm of Polar Codes to Optimize the Error Pattern Set
  • YUAN Jianguo, YU Linfeng, YOU Wei, PANG Yu
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 76-82.
  • Abstract ( 85 )     　　
  • In order to solve the problems that the error pattern set of polar codes is too large to be counted and the cyclic redundancy check code at the tail is prone to make the errors as well as the poor sorting of the revised critical set of the successive cancellation list flip (SCL-Flip) decoding algorithm, a polar code SCL-Flip decoding algorithm is proposed to optimize the error pattern set. In the algorithm, the error pattern set is reduced by reducing the number of check digits of the cyclic redundancy check code, and the cyclic redundancy check code is placed in the sequence header with the highest reliability to reduce the error as well as optimize the distance spectrum of polar codes. When the decoding fails, the revised critical set is reordered according to the row weight firstly, and then the error pattern set is searched according to the error pattern of the cyclic redundancy check to obtain the location of the first error and place it at the head of the revised critical set. This not only improves the flip accuracy but also reduces the number of the extra flip. The simulation results show that the proposed algorithm has a significant performance gain, furthermore, and the number of the flip is significantly reduced.
    
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  • The Method of Multivariable Time Series Representation Learning Combining Reconstruction with Contrasting
  • HUO Weigang, MENG Lu, GUO Runxia
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 83-90.
  • Abstract ( 137 )     　　
  • The spatiotemporal coupling features of a single multivariate time series(MTS) sample and the invariant discriminative features between the MTS samples can not be simultaneously captured by most of the existing self-supervised representation learning models for MTS. To this end, the MTS representation learning model combining reconstruction with contrasting ( MTS-RC ) is proposed. First, the MTS samples are augmented through binary noise masks, and then the local context features of the MTS and its augmented samples and long-term time-dependent relationship of local context features are respectively extracted by dilated convolution and transformer encoder. Finally, the spatiotemporal coupling characteristics of a single MTS sample are captured by reconstructing the mask value of augmented samples, and the MTS invariant discriminative characteristics are extracted between samples by contrastive learning. Experiments on classification on multiple MTS public datasets show that the classification accuracy of the classifier trained by the representation vector obtained from the MTS-RC outperforms typical baseline models. The results of ablation experiments show that the quality of MTS representation vector can be improved by the combined design of reconstruction and contrasting.
    
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  • Chinese Spelling Correction Model Based on Gated Feature Fusion
  • ZHOU Yuhao, SUN Zhe, WU Xiaofei, YU Ke
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 91-96,122.
  • Abstract ( 116 )     　　
  • In response to the problem of model performance being affected by incorrect pronunciation or glyph when fusing semantic, phonetic and glyph information of Chinese characters equally in Chinese spelling correction, a Chinese spelling correction model based on gated feature fusion is proposed, which uses adaptive gates to selectively fuse semantic, phonetic and glyph information to improve the performance of the model and enhance the interpretability of the model. The improved four corner code is used to encode the glyph features of Chinese characters, effectively extracting the glyph features of Chinese characters, and based on this, the glyph similarity confusion set in the pre-training stage of the model is expanded. The pre-training mask strategy based on confusion set replacement is used to enable the model to effectively learn the erroneous knowledge contained in the text. On the public SIGHAN13, SIGHAN14 and SIGHAN15 datasets, the proposed model achieves correction F1-scores of 78.7% , 67.8% and 77.7% , respectively, which are 1.5% , 1.5% and 1.0% higher than the optimal baseline model.
    
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  • Gated Interactive Fusion Network for Rumor Detection
  • SU Xing, YU Ke, WU Xiaofei
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 97-102.
  • Abstract ( 111 )     　　
  • To address the issue of feature conflicts caused by differences between features when the existing rumor detection methods deal with multiple features, a hierarchical gated interactive fusion network-based rumor detection method is proposed. First, the first-order gate unit is conducted to obtain the enhanced semantic and sentiment features of original posts and comments. Then, the second-order gate unit is used to perform cross-semantic feature fusion on the enhanced features to solve the problem of introducing noise due to differences between different features during feature fusion. On the public Weibo dataset and the self-built Weibo22 dataset, the detection accuracy of the proposed method is 96.71% and 97.36% , respectively. Compared with the baseline methods with the best detection performance, the detection accuracy of the proposed method is improved by 0.84% and 1.31% , respectively, and the training time is reduced by 53% and 46% , respectively.
    
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  • Certificateless Handover Authentication and Key Agreement Protocol for Network Slicing
  • WU Xuan, JI Weifeng, WENG Jiang, LI Yingqi, SHEN Xiuyu
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 103-108.
  • Abstract ( 85 )     　　
  • In order to solve the problems of poor anonymity, complex authentication process and low generality of handover protocol between network slices, an efficient universal secure handover authentication and key negotiation protocol based on no certificate is proposed. The key negotiation protocol based on certificateless mechanism can solve the problems of certificate storage and key management in traditional public key infrastructure, and can effectively improve the efficiency of handover authentication under the premise of ensuring security. The proposed agreement achieves privacy protection for users and network slices by introducing user pseudo-identities and slice identity identifier. For network slicing of different service types, an edge controller is introduced between the user and the slicing service provider to assist the inter-slice handover process to ensure that legal users can achieve fast and universal identity authentication during the handover process. Simulation results show that the proposed protocol can improve the efficiency of inter-chip handover authentication and realize a secure and universal handover process.
    
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  • High Time-Frequency Efficiency Generalized Filter Banks Frequency Division Multiplexing Modulation Scheme
  • XIN Yu, XU You, ZHANG Huaijin, BAO Tong, KONG Dejin
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 109-115.
  • Abstract ( 79 )     　　
  • In order to improve the spectrum efficiency and time-frequency resource utilization of the future wireless communication system, a high time-frequency efficiency modulation technique based on a general filter bank frequency division multiplexing is proposed to solve the shortage of spectrum resources. The proposed technique can combat inter symbol interference and inter carrier interference without the need for circular prefixes by selecting different symbol intervals and different waveform functions. Three typical time slot transmission structures are designed for different symbol spacing, and interference problems introduced in the three cases are analyzed. Furthermore, the iterative frame-based block iterative detection algorithm is further proposed, by continuously compensating for distorted signals, the interference introduced is signficantly reduced. The simulation results show that the technique improves the time-frequency and spectrum efficiency while ensuring the bit error rate performance and has a superior asynchronous performance.
    
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  • A Software Defect Assessment Method with Classification Cost
  • XIE Lixia, LIU Siyu, YANG Hongyu, ZHANG Liang
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 116-122.
  • Abstract ( 89 )     　　
  • To solve the problems that the existing software defect assessment methods do not generate processing priority according to the dichotomous classification results, and the sample-based class imbalanced processing methods are prone to cause important data loss, a software defect assessment method with classification cost is proposed. First, preprocessed samples are obtained by processing multi-source samples through four phases: sample noise processing, sample distribution normalization, sample balance reconstruction and feature dimensionality reduction. Then, the evaluation indexes and index weights on multiple classifiers are calculated to obtain the classification cost, and the heterogeneous weighted voting model is constructed through the classification cost. Finally, the heterogeneous weighted voting model is used to calculate the defective probability values and assess the levels of the defective samples. The experimental results show that the defective probability values and defect levels obtained by the proposed method are more consistent with the actual situation of the real samples, which can accurately reflect the defect levels of the code modules.
    
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  • Aspect Category Classification Integrated in Syntactic Dependency and BERT-Att-BiLSTM
  • BAO Qianhui, WEN Juan, SHI Shuzhen, DONG Mengping, LIU Xue
  • Journal of Beijing University of Posts and Telecommunications. 2023, 46(4): 123-128.
  • Abstract ( 96 )     　　
  • Current aspect category classification in fine-grained sentimental analysis suffers from low accuracy problems. An aspect category classification method is proposed integrates in syntactic dependency and bidirectional encoder representations from Transformers-attention mechanism-bidirectional short-term memory network ( BERT-Att-BiLSTM). Firstly, in the target information extraction layer, aspect-opinion pairs from comments is extracted by syntactic dependency. In the word embedding layer, BERT module is used to combined the dynamic features of context to achieve word vector representation. Then, in feature extraction layer, the BiLSTM module is integrated in attention mechanism to reduce the dimension of feature space. Finally, the aspect category is obtained at the classification layer through activation function. Experimental results show that the precision, recall rate, and F1 value of the proposed method reached 85.25% , 72.38% and 77.06% , surpassed the other chosen models and proved its effectiveness.
    
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