Pub Date : 2024-12-01DOI: 10.23919/JCN.2024.000074
This index covers all papers that appeared in JCN during 2024. The Author Index contains the primary entry for each item, listed under the first author's name, and cross-references from all coauthors. The Title Index contains paper titles for each Division in the alphabetical order from No. 1 to No. 6. Please refer to the primary entry in the Author Index for the exact title, coauthors, and comments / corrections.
{"title":"2024 Index journal of communications and networks, volume 26","authors":"","doi":"10.23919/JCN.2024.000074","DOIUrl":"https://doi.org/10.23919/JCN.2024.000074","url":null,"abstract":"This index covers all papers that appeared in JCN during 2024. The Author Index contains the primary entry for each item, listed under the first author's name, and cross-references from all coauthors. The Title Index contains paper titles for each Division in the alphabetical order from No. 1 to No. 6. Please refer to the primary entry in the Author Index for the exact title, coauthors, and comments / corrections.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"1-5"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834494","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938130","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}
Pub Date : 2024-12-01DOI: 10.23919/JCN.2024.000075
{"title":"Information for authors","authors":"","doi":"10.23919/JCN.2024.000075","DOIUrl":"https://doi.org/10.23919/JCN.2024.000075","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"711-715"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834485","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142937981","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}
Pub Date : 2024-12-01DOI: 10.23919/JCN.2024.000068
Ming Chen;Liang Jin;Zheng Wan;Zheyuan Deng;Bo Zhang;Yajun Chen;Kaizhi Huang
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.
{"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}
Pub Date : 2024-12-01DOI: 10.23919/JCN.2024.000073
{"title":"Reviewer list for 2024","authors":"","doi":"10.23919/JCN.2024.000073","DOIUrl":"https://doi.org/10.23919/JCN.2024.000073","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 6","pages":"700-705"},"PeriodicalIF":2.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10834489","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142938128","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}
Pub Date : 2024-12-01DOI: 10.23919/JCN.2024.000054
Imtiaz Ali Soomro;Hamood ur Rehman Khan;Syed Jawad Hussain;Zeeshan Ashraf;Mrim M. Alnfiai;Nouf Nawar Alotaibi
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.
{"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}
Pub Date : 2024-12-01DOI: 10.23919/JCN.2024.000070
Haogang Feng;Haiyu Xiao;Shida Zhong;Zhuqing Gao;Tao Yuan;Zhi Quan
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.
{"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}
Pub Date : 2024-11-20DOI: 10.23919/JCN.2024.000050
Benedetta Picano;Romano Fantacci
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.
{"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}
Pub Date : 2024-11-20DOI: 10.23919/JCN.2024.000025
Alberto Tarable;Francisco J. Escribano
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.
{"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}
Pub Date : 2024-10-01DOI: 10.23919/JCN.2024.000061
{"title":"copyright transferform","authors":"","doi":"10.23919/JCN.2024.000061","DOIUrl":"https://doi.org/10.23919/JCN.2024.000061","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 5","pages":"1-3"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10748576","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600147","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}
Pub Date : 2024-10-01DOI: 10.23919/JCN.2024.000048
Jin Kwan Kim;Yunjoong Park;Joon Young Kim
The integrated sensing and communications (ISAC) system has become a promising scheme for combining sensing and communication features to send data and sense the physical space concurrently. Although it aims to understand the channel condition and communication environment with sensing capability, it still requires sustainable high-data transmission with efficient spectrum usage. The in-band full-duplex (IBFD) system can be a possible solution to support high data transmission while increasing spectrum efficiency. Since IBFD has a self-interference issue, one of the significant factors that deteriorate its performance, we need to investigate possible solutions to resolve this matter. In this paper, we present an improved self-interference cancellation receiver with successive interference cancellation (SIC)-based channel estimation for the IBFD system. Since SIC aims to mitigate the multiple interference effects, our proposed algorithm applied SIC to the channel estimation for the performance gain. Our results show that SI cancellation with SIC-based channel estimation improves the IBFD bit error rate (BER) of the new radio (NR) for the ISAC system.
综合传感与通信（ISAC）系统已成为将传感与通信功能相结合的一种前景广阔的方案，可同时发送数据和感知物理空间。虽然它的目的是利用传感能力了解信道状况和通信环境，但它仍然需要可持续的高数据传输和有效的频谱利用。带内全双工（IBFD）系统是在提高频谱效率的同时支持高数据传输的一种可行解决方案。由于 IBFD 存在自干扰问题，这也是影响其性能的重要因素之一，因此我们需要研究可行的解决方案来解决这一问题。在本文中，我们为 IBFD 系统提出了一种基于连续干扰消除（SIC）信道估计的改进型自干扰消除接收器。由于 SIC 的目的是减轻多重干扰效应，我们提出的算法将 SIC 应用于信道估计以提高性能。我们的研究结果表明，基于 SIC 的信道估计的自干扰消除提高了 ISAC 系统中新无线电（NR）的 IBFD 误码率（BER）。
{"title":"Successive interference cancellation-based channel estimation for self-interference cancellation in in-band full-duplex systems","authors":"Jin Kwan Kim;Yunjoong Park;Joon Young Kim","doi":"10.23919/JCN.2024.000048","DOIUrl":"https://doi.org/10.23919/JCN.2024.000048","url":null,"abstract":"The integrated sensing and communications (ISAC) system has become a promising scheme for combining sensing and communication features to send data and sense the physical space concurrently. Although it aims to understand the channel condition and communication environment with sensing capability, it still requires sustainable high-data transmission with efficient spectrum usage. The in-band full-duplex (IBFD) system can be a possible solution to support high data transmission while increasing spectrum efficiency. Since IBFD has a self-interference issue, one of the significant factors that deteriorate its performance, we need to investigate possible solutions to resolve this matter. In this paper, we present an improved self-interference cancellation receiver with successive interference cancellation (SIC)-based channel estimation for the IBFD system. Since SIC aims to mitigate the multiple interference effects, our proposed algorithm applied SIC to the channel estimation for the performance gain. Our results show that SI cancellation with SIC-based channel estimation improves the IBFD bit error rate (BER) of the new radio (NR) for the ISAC system.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"26 5","pages":"521-532"},"PeriodicalIF":2.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10748583","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600163","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}
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