Journal of Communications and Networks最新文献_第2页

Signal augmentation method based on mixing and adversarial training for better robustness and generalization 基于混合和对抗训练的信号增强方法具有更好的鲁棒性和泛化性

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000067

Li Zhang;Gang Zhou;Gangyin Sun;Chaopeng Wu

{"title":"Signal augmentation method based on mixing and adversarial training for better robustness and generalization","authors":"Li Zhang;Gang Zhou;Gangyin Sun;Chaopeng Wu","doi":"10.23919/JCN.2024.000067","DOIUrl":"https://doi.org/10.23919/JCN.2024.000067","url":null,"abstract":"More and more deep learning methods have been applied to wireless communication systems. However, the collection of authentic signal data poses challenges. Moreover, due to the vulnerability of neural networks, adversarial attacks seriously threaten the security of communication systems based on deep learning models. Traditional signal augmentation methods expand the dataset through transformations such as rotation and flip, but these methods improve the adversarial robustness of the model little. However, common methods to improve adversarial robustness such as adversarial training not only have a high computational overhead but also potentially lead to a decrease in accuracy on clean samples. In this work, we propose a signal augmentation method called adversarial and mixed-based signal augmentation (AMSA). The method can improve the adversarial robustness of the model while expanding the dataset and does not compromise the generalization ability. It combines adversarial training with data mixing and then interpolates selected pairs of samples to form new samples in an expanded dataset consisting of original and adversarial samples thus generating more diverse data. We conduct experiments on the RML2016.10a and RML2018.01a datasets using automatic modulation recognition (AMR) models based on convolutional neural networks (CNN), long short-term memory (LSTM), convolutional long short-term deep neural networks (CLDNN), and transformer. And compare the performance in scenarios with different numbers of samples. The results show that AMSA allows the model to achieve comparable or even better adversarial robustness than using adversarial training, and reduces the degradation of the model's generalization performance on clean data.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"679-688"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834486","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance optimization of IEEE 802.11ax UL OFDMA random access IEEE 802.11ax UL OFDMA随机接入的性能优化

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000069

Pengxue Liu;Yitong Li;Dalong Zhang

引用次数: 0

2024 Index journal of communications and networks, volume 26 2024通信与网络索引杂志，第26卷

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000074

引用次数: 0

Information for authors 作者信息

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000075

引用次数: 0

Robust direction-of-arrival estimation and signal separation method for integrated sensing and communication 融合传感与通信的鲁棒到达方向估计与信号分离方法

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000068

Ming Chen;Liang Jin;Zheng Wan;Zheyuan Deng;Bo Zhang;Yajun Chen;Kaizhi Huang

{"title":"Robust direction-of-arrival estimation and signal separation method for integrated sensing and communication","authors":"Ming Chen;Liang Jin;Zheng Wan;Zheyuan Deng;Bo Zhang;Yajun Chen;Kaizhi Huang","doi":"10.23919/JCN.2024.000068","DOIUrl":"https://doi.org/10.23919/JCN.2024.000068","url":null,"abstract":"In this study, we designed a single-channel direction-of-arrival (DOA) estimation and signal separation algorithm based on a grouping scheme for the time-varying metasurfaces (TVMs) for integrated sensing and communication systems. In this scheme, the harmonic effect of the TVM was used to transform the received single-channel signal into a multichannel signal through an orthogonal Fourier coefficient matrix. After achieving multi-channel DOA estimation, the corresponding weighted beam pointing was designed for signal separation. By applying a periodic modulation function on the TVM to modulate the incident signal, the signal was mapped to a multi-dimensional received space to recover the multi-channel received signal. Thus, conventional multi-channel algorithms could be used on the single-channel signal for DOA estimation. Next, we designed a sub-surface weighted beam pointing to maximize the received signal signal-to-interference-plus-noise ratio. Simulation results revealed that the proposed scheme of DOA estimation can exhibit performances comparable to that of the conventional multichannel antenna array. Moreover, the signal separation scheme designed based on this method was robust and could maintain good signal separation ability under a low signal-to-noise ratio.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"689-698"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834481","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Reviewer list for 2024 2024年评审名单

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000073

引用次数: 0

Lightweight privacy-preserving federated deep intrusion detection for industrial cyber-physical system 面向工业网络物理系统的轻量级隐私保护联合深度入侵检测

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000054

Imtiaz Ali Soomro;Hamood ur Rehman Khan;Syed Jawad Hussain;Zeeshan Ashraf;Mrim M. Alnfiai;Nouf Nawar Alotaibi

{"title":"Lightweight privacy-preserving federated deep intrusion detection for industrial cyber-physical system","authors":"Imtiaz Ali Soomro;Hamood ur Rehman Khan;Syed Jawad Hussain;Zeeshan Ashraf;Mrim M. Alnfiai;Nouf Nawar Alotaibi","doi":"10.23919/JCN.2024.000054","DOIUrl":"https://doi.org/10.23919/JCN.2024.000054","url":null,"abstract":"The emergence of Industry 4.0 entails extensive reliance on industrial cyber-physical systems (ICPS). ICPS promises to revolutionize industries by fusing physical systems with computational functionality. However, this potential increase in ICPS makes them prone to cyber threats, necessitating effective intrusion detection systems (IDS) systems. Privacy provision, system complexity, and system scalability are major challenges in IDS research. We present FedSecureIDS, a novel lightweight federated deep intrusion detection system that combines CNNs, LSTMs, MLPs, and federated learning (FL) to overcome these challenges. FedSecureIDS solves major security issues, namely eavesdropping and man-in-the-middle attacks, by employing a simple protocol for symmetric session key exchange and mutual authentication. Our Experimental results demonstrate that the proposed method is effective with an accuracy of 98.68%, precision of 98.78%, recall of 98.64%, and an F1-score of 99.05% with different edge devices. The model is similarly performed in conventional centralized IDS models. We also carry out formal security evaluations to confirm the resistance of the proposed framework to known attacks and provisioning of high data privacy and security.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"632-649"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834496","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Deep-learning-aided fast successive cancellation decoding of polar codes 深度学习辅助的极性码快速连续对消译码

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000070

Haogang Feng;Haiyu Xiao;Shida Zhong;Zhuqing Gao;Tao Yuan;Zhi Quan

{"title":"Deep-learning-aided fast successive cancellation decoding of polar codes","authors":"Haogang Feng;Haiyu Xiao;Shida Zhong;Zhuqing Gao;Tao Yuan;Zhi Quan","doi":"10.23919/JCN.2024.000070","DOIUrl":"https://doi.org/10.23919/JCN.2024.000070","url":null,"abstract":"With the continuous evolution of 5G communication technology to B5G and the next generation of communication technology, Deep Learning technology will also lead the automation and intelligent transformation of communication systems. Existing research has shown that the combination of deep learning and communication technology is expected to break some performance bottlenecks of traditional communication algorithms and solutions. This paper explores the application of deep learning (DL) in polar decoding algorithms, proposing a DL-aided-FSC (DL-FSC) polar code decoder algorithm. For the DL-FSC decoding algorithm, the conventional successive cancellation (SC) decoder is partitioned into multiple sub-blocks, which are replaced by R0 nodes, R1 nodes and sub-DL decoder. The log-likelihood ratio (LLR) and frozen bit pattern are input to the sub-DL decoder to predict decode codewords under any decoding code rate. Through simulation verification, under the PBCH channel of 5G communication, the DL-FSC decoder achieves similar block error rate (BLER) performance to the SC decoder, even improving by about 1%. In order to verify the performance optimization effect of the proposed algorithm at the hardware level, the DL-FSC deocder circuit design was completed. Through FPGA synthesis, the proposed decoder achieves a throughput of about 4571 Mbps, which is 1.71× improvement in decoding throughput at the expense of increased logic resources.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"593-602"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834493","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient task offloading and resource allocation in an intelligent UAV-MEC system 智能无人机- mec系统的高效任务卸载和资源分配

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-11-20 DOI: 10.23919/JCN.2024.000050

Benedetta Picano;Romano Fantacci

{"title":"Efficient task offloading and resource allocation in an intelligent UAV-MEC system","authors":"Benedetta Picano;Romano Fantacci","doi":"10.23919/JCN.2024.000050","DOIUrl":"https://doi.org/10.23919/JCN.2024.000050","url":null,"abstract":"Nowadays, the functional integration of digital twin (DT) technology and artificial intelligence (AI) methodologies has enabled reliable predictions of many random processes, supporting efficient control and optimization procedures. In line with this trend, this paper explores the joint use of these technologies in an AI-empowered DT framework for an unmanned aerial vehicle-aided multi-access edge computing (UAV-MEC) system. Specifically, this approach defines an intelligent UAV-MEC system capable of significantly improving service quality and deployment flexibility. The focus is on a UAV-MEC network consisting of multiple elementary service areas, where DTs efficiently orchestrate and reduce congestion levels by utilizing UAVs with onboard processing capabilities. A potential architecture for the DTs is outlined, conceptualizing each DT as a collection of basic cyber entities. Additionally, a suitable framework utilizing a matching game approach is proposed to effectively manage task offloading, channel allocation, and the dynamic assignment of UAV support to congested service zones within the same area. Finally, comprehensive simulation results validate the efficacy of the proposed intelligent UAV-MEC system, as indicated by metrics such as task completion delay and accuracy in congestion prediction.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"666-678"},"PeriodicalIF":2.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759571","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Compensation of phase noise in massive-MIMO uplink communications based on expectation-maximization algorithm 基于期望最大化算法的大规模mimo上行通信相位噪声补偿

IF 2.9 3区计算机科学

Journal of Communications and Networks Pub Date : 2024-11-20 DOI: 10.23919/JCN.2024.000025

Alberto Tarable;Francisco J. Escribano

{"title":"Compensation of phase noise in massive-MIMO uplink communications based on expectation-maximization algorithm","authors":"Alberto Tarable;Francisco J. Escribano","doi":"10.23919/JCN.2024.000025","DOIUrl":"https://doi.org/10.23919/JCN.2024.000025","url":null,"abstract":"Phase noise (PN) is a major disturbance in MIMO systems, where the contribution of different oscillators at the transmitter and the receiver side may degrade the overall performance and offset the gains offered by MIMO techniques. This is even more crucial in the case of massive MIMO, since the number of PN sources may increase considerably. In this work, we propose an iterative receiver based on the application of the expectation-maximization algorithm. We consider a massive MIMO framework with a general association of oscillators to antennas, and include other channel disturbances like imperfect channel state information and Rician block fading. At each receiver iteration, given the information on the transmitted symbols, steepest descent is used to estimate the PN samples, with an optimized adaptive step size and a threshold-based stopping rule. The results obtained for several test cases show how the bit error rate and mean square error can benefit from the proposed phase-detection algorithm, even to the point of reaching the same performance as in the case where no PN is present, offering better results than a state-of-the-art alternative. Further analysis of the results allow to draw some useful trade-offs respecting final performance and consumption of resources.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"603-616"},"PeriodicalIF":2.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10759570","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0