Pub Date : 2024-12-26DOI: 10.1109/LCOMM.2024.3522281
Wenhan Li;Jiangong Wang;Taijun Liu;Gaoming Xu
Specific emitter identification (SEI) is a unique physical-layer security technology that plays a crucial role in protecting wireless communication systems from various security threats. Although SEI based on artificial neural network models has achieved good identification performance, its performance degrades when labeled samples are limited. To address this issue, this letter proposes a few-shot SEI method based on a contrastive masked learning framework. This method combines contrastive learning and masked learning to enhance the model’s representation capability, and it consists of an encoder, a signal decoder, a feature decoder, and a momentum encoder. Simulation experiments on the open-source datasets LoRa and ADS-B show that the proposed method outperforms other SEI methods.
{"title":"Few-Shot Specific Emitter Identification Based on a Contrastive Masked Learning Framework","authors":"Wenhan Li;Jiangong Wang;Taijun Liu;Gaoming Xu","doi":"10.1109/LCOMM.2024.3522281","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3522281","url":null,"abstract":"Specific emitter identification (SEI) is a unique physical-layer security technology that plays a crucial role in protecting wireless communication systems from various security threats. Although SEI based on artificial neural network models has achieved good identification performance, its performance degrades when labeled samples are limited. To address this issue, this letter proposes a few-shot SEI method based on a contrastive masked learning framework. This method combines contrastive learning and masked learning to enhance the model’s representation capability, and it consists of an encoder, a signal decoder, a feature decoder, and a momentum encoder. Simulation experiments on the open-source datasets LoRa and ADS-B show that the proposed method outperforms other SEI methods.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"408-412"},"PeriodicalIF":3.7,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Graph has been proven to be an emerging tool for spectrum sensing (SS), with detection performance closely related to the graph characteristics. Existing graph-based SS has been mainly investigated based on the unweighted graph for single user scenario, which leads to the poor performance at the low signal-to-noise. To address this issue, we introduce a weighted graph-based cooperative spectrum sensing method in this letter. Specifically, a signal-to-weighted-graph (STWG) mechanism for multi-user is proposed, which converts the signals of different users into a single weighted graph. To characterize the features of the weighted graph, graph sparsity is employed to represent the graph connectivity, upon which a test statistic is constructed. Moreover, a simple but practical method is proposed to estimate the detection threshold. Experimental results verify the theoretical analysis and demonstrate the superior performance of the proposed method.
{"title":"Cooperative Spectrum Sensing Using Weighted Graph Sparsity","authors":"Yuxin Li;Guangyue Lu;Yinghui Ye;Gaojie Chen;Jingyu Feng","doi":"10.1109/LCOMM.2024.3522112","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3522112","url":null,"abstract":"Graph has been proven to be an emerging tool for spectrum sensing (SS), with detection performance closely related to the graph characteristics. Existing graph-based SS has been mainly investigated based on the unweighted graph for single user scenario, which leads to the poor performance at the low signal-to-noise. To address this issue, we introduce a weighted graph-based cooperative spectrum sensing method in this letter. Specifically, a signal-to-weighted-graph (STWG) mechanism for multi-user is proposed, which converts the signals of different users into a single weighted graph. To characterize the features of the weighted graph, graph sparsity is employed to represent the graph connectivity, upon which a test statistic is constructed. Moreover, a simple but practical method is proposed to estimate the detection threshold. Experimental results verify the theoretical analysis and demonstrate the superior performance of the proposed method.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"403-407"},"PeriodicalIF":3.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-23DOI: 10.1109/LCOMM.2024.3521045
Shiya Hao;Hua Li;Qianqian Li;Jiaqi Feng;Xiaoming Dai
Orthogonal time sequency multiplexing (OTSM) has recently attracted significant attention due to its enhanced robustness in doubly selective fading channels. However, the computational complexity of conventional OTSM receivers increases significantly in scenarios with fractional Doppler shifts. In this work, we first analyze the effects of inter-Doppler interference on the performance of OTSM systems. We then propose a sparse compensation maximum ratio combining (SC-MRC) detection algorithm to mitigate computational complexity. Specifically, a channel sparsification procedure is implemented by eliminating amplitude values that fall below a predetermined threshold, thereby substantially reducing the computational complexity associated with matrix multiplication. A low-complexity adaptive compensation scheme is introduced to mitigate the associated performance degradation. Simulation results demonstrate that the proposed SC-MRC algorithm achieves superior performance compared to the conventional MRC algorithm while offering reduced computational complexity.
{"title":"Low-Complexity Sparse Compensation MRC Detection Algorithm for OTSM Systems","authors":"Shiya Hao;Hua Li;Qianqian Li;Jiaqi Feng;Xiaoming Dai","doi":"10.1109/LCOMM.2024.3521045","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3521045","url":null,"abstract":"Orthogonal time sequency multiplexing (OTSM) has recently attracted significant attention due to its enhanced robustness in doubly selective fading channels. However, the computational complexity of conventional OTSM receivers increases significantly in scenarios with fractional Doppler shifts. In this work, we first analyze the effects of inter-Doppler interference on the performance of OTSM systems. We then propose a sparse compensation maximum ratio combining (SC-MRC) detection algorithm to mitigate computational complexity. Specifically, a channel sparsification procedure is implemented by eliminating amplitude values that fall below a predetermined threshold, thereby substantially reducing the computational complexity associated with matrix multiplication. A low-complexity adaptive compensation scheme is introduced to mitigate the associated performance degradation. Simulation results demonstrate that the proposed SC-MRC algorithm achieves superior performance compared to the conventional MRC algorithm while offering reduced computational complexity.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"398-402"},"PeriodicalIF":3.7,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-20DOI: 10.1109/LCOMM.2024.3520667
Zhengyang Zhang;Ozgur B. Akan
This letter explores Terahertz communication in Mars surface channel models, analyzing Terahertz communication applicable to Mars through Mars-related simulations. Firstly, the basic components and system model of the Terahertz frequency communication system are discussed. Secondly, simulations involving data rate, frequency, transmission distance, power budget, dust density, and signal-to-noise ratio reveal the main relevant factors of Terahertz communication on Mars. The study focuses on signal transmission in the Mars environment under thin Martian air and intense dust storms, analyzing the impact of transmission distance, air molecule absorption, and dust particle scattering. Additionally, this letter examines Terahertz channel coding and capacity analysis in the special Martian environment, aiming to more accurately assess the feasibility of applying Terahertz communication to the Martian surface. Finally, the wireless link is validated through simulations, demonstrating its capabilities and limitations.
{"title":"Analysis of Terahertz Communication Under Dust Storm Conditions on Mars","authors":"Zhengyang Zhang;Ozgur B. Akan","doi":"10.1109/LCOMM.2024.3520667","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3520667","url":null,"abstract":"This letter explores Terahertz communication in Mars surface channel models, analyzing Terahertz communication applicable to Mars through Mars-related simulations. Firstly, the basic components and system model of the Terahertz frequency communication system are discussed. Secondly, simulations involving data rate, frequency, transmission distance, power budget, dust density, and signal-to-noise ratio reveal the main relevant factors of Terahertz communication on Mars. The study focuses on signal transmission in the Mars environment under thin Martian air and intense dust storms, analyzing the impact of transmission distance, air molecule absorption, and dust particle scattering. Additionally, this letter examines Terahertz channel coding and capacity analysis in the special Martian environment, aiming to more accurately assess the feasibility of applying Terahertz communication to the Martian surface. Finally, the wireless link is validated through simulations, demonstrating its capabilities and limitations.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"388-392"},"PeriodicalIF":3.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403915","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The existing spatial domain anti-jamming research relies on the prior information of the jamming channel to support the anti-jamming design, which is difficult to deal with the malicious jamming with strong concealment. The study proposes a stacked intelligent metasurfaces (SIM) assisted integrated-sensing-and-resistance (ISAR) anti-jamming scheme. Precisely, to obtain the jamming channel information in real time to assist the receiver in filtering out the jamming, an ISAR receiving system model is established, where the SIM consists of two layers of transmissive RIS (TRIS) is deployed around the receiving antenna, functioning as jamming sensing TRIS and anti jamming TRIS in cascade. Then a TRIS based jamming sensing method is proposed to accurately estimate the channel information. And a TRIS anti jamming phase shift optimization algorithm is proposed to optimize the phase shift according to the acquired jamming information, so as to effectively filter out the jamming signal. Simulation results show that the anti-jamming performance of the proposed scheme can approximate the scheme with perfect jamming channel state information under the premise of completely unknown prior information of the jamming channel.
{"title":"Stacked Intelligent Metasurfaces Assisted Integrated-Sensing-and-Resistance Anti Jamming","authors":"Chen Pei;Kaizhi Huang;Liang Jin;Xiaoming Xu;You Zhou;Yuze Guo","doi":"10.1109/LCOMM.2024.3520510","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3520510","url":null,"abstract":"The existing spatial domain anti-jamming research relies on the prior information of the jamming channel to support the anti-jamming design, which is difficult to deal with the malicious jamming with strong concealment. The study proposes a stacked intelligent metasurfaces (SIM) assisted integrated-sensing-and-resistance (ISAR) anti-jamming scheme. Precisely, to obtain the jamming channel information in real time to assist the receiver in filtering out the jamming, an ISAR receiving system model is established, where the SIM consists of two layers of transmissive RIS (TRIS) is deployed around the receiving antenna, functioning as jamming sensing TRIS and anti jamming TRIS in cascade. Then a TRIS based jamming sensing method is proposed to accurately estimate the channel information. And a TRIS anti jamming phase shift optimization algorithm is proposed to optimize the phase shift according to the acquired jamming information, so as to effectively filter out the jamming signal. Simulation results show that the anti-jamming performance of the proposed scheme can approximate the scheme with perfect jamming channel state information under the premise of completely unknown prior information of the jamming channel.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"383-387"},"PeriodicalIF":3.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-20DOI: 10.1109/LCOMM.2024.3520700
Sangeeta Nalluru;Sapta Girish Neelam
This study introduces an innovative detection strategy for perfectly phase optimized Intelligent Reflecting Surface (IRS)-aided Multiple-Input Multiple-Output (MIMO) systems using Orthogonal Time Sequency Multiplexing (OTSM) modulation, specifically designed to perform well even with hardware limitations such as carrier frequency offset (CFO). The approach leverages maximum ratio combining (MRC) to enhance signal quality by mitigating multipath and inter-antenna interference. It also integrates advanced sub-channel estimation techniques to address CFO and features a meticulously designed frame structure that reduces interference and supports efficient parallel processing. This low-complexity detection method significantly boosts the performance of IRS-aided MIMO-OTSM systems, highlighting its transformative potential for wireless communication. Results demonstrate that an IRS-aided single-user MIMO-OTSM with an MRC detector outperforms traditional detectors, showcasing the effectiveness of incorporating IRS elements.
{"title":"Low Complexity Detection of IRS-Aided MIMO-OTSM Under Perfect Phase Optimization","authors":"Sangeeta Nalluru;Sapta Girish Neelam","doi":"10.1109/LCOMM.2024.3520700","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3520700","url":null,"abstract":"This study introduces an innovative detection strategy for perfectly phase optimized Intelligent Reflecting Surface (IRS)-aided Multiple-Input Multiple-Output (MIMO) systems using Orthogonal Time Sequency Multiplexing (OTSM) modulation, specifically designed to perform well even with hardware limitations such as carrier frequency offset (CFO). The approach leverages maximum ratio combining (MRC) to enhance signal quality by mitigating multipath and inter-antenna interference. It also integrates advanced sub-channel estimation techniques to address CFO and features a meticulously designed frame structure that reduces interference and supports efficient parallel processing. This low-complexity detection method significantly boosts the performance of IRS-aided MIMO-OTSM systems, highlighting its transformative potential for wireless communication. Results demonstrate that an IRS-aided single-user MIMO-OTSM with an MRC detector outperforms traditional detectors, showcasing the effectiveness of incorporating IRS elements.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"393-397"},"PeriodicalIF":3.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel framework of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided rate-splitting multiple access (RSMA)-enabled bistatic backscatter communication (BiBC) is proposed in this letter, considering double reflections and transmissions at STAR-RIS. An optimization problem is formulated to maximize the sum rate at the reader by the joint design of beamforming at the STAR-RIS and power allocation at the tag, guaranteeing the targeted rate requirement and energy harvesting constraint of each tag. To solve the coupling non-convex problem, an alternating optimization (AO) algorithm based on the successive convex approximation (SCA) and sequential rank-one constraint relaxation (SROCR) is presented. Simulation results reveal that the proposed framework provides ~61 % and ~40 % gains in system sum rate over benchmarks and achieves better trade-off between harvested energy and data rate.
{"title":"Joint Beamforming and Resource Allocation Design for STAR-RIS Aided RSMA-BiBC System","authors":"Chenyan Xiao;Fei Du;Dacai Wei;Xiaoqing Wang;Xiongwen Zhao","doi":"10.1109/LCOMM.2024.3520125","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3520125","url":null,"abstract":"A novel framework of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided rate-splitting multiple access (RSMA)-enabled bistatic backscatter communication (BiBC) is proposed in this letter, considering double reflections and transmissions at STAR-RIS. An optimization problem is formulated to maximize the sum rate at the reader by the joint design of beamforming at the STAR-RIS and power allocation at the tag, guaranteeing the targeted rate requirement and energy harvesting constraint of each tag. To solve the coupling non-convex problem, an alternating optimization (AO) algorithm based on the successive convex approximation (SCA) and sequential rank-one constraint relaxation (SROCR) is presented. Simulation results reveal that the proposed framework provides ~61 % and ~40 % gains in system sum rate over benchmarks and achieves better trade-off between harvested energy and data rate.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"378-382"},"PeriodicalIF":3.7,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The emerging B5G and 6G applications have brought forth the need for high-precision indoor localization. However, the complexity of indoor environments poses significant challenges to this goal, particularly due to the presence of non-line-of-sight (NLOS) conditions and multipath effects. This letter proposes an attention-based positioning network (ABPN) that exploits fine-grained features from MIMO channel state information (CSI) by spatial attention to combat the limited receptive field of traditional convolutional neural networks (CNNs) as well as channel attention to discriminate the importance of different wireless channels. Extensive experiments, conducted on two real-world datasets, demonstrate that the proposed ABPN outperforms the popular PirnatEco, AAresCNN, MIMOnet and CLnet with an average localization accuracy improvement of over 50%.
{"title":"A Deep Learning-Based Indoor Positioning Approach Using Channel and Spatial Attention","authors":"Jiawei Zhang;Zhendong Xu;Shiyu Zhang;Keke Hu;Yuan Shen","doi":"10.1109/LCOMM.2024.3519340","DOIUrl":"https://doi.org/10.1109/LCOMM.2024.3519340","url":null,"abstract":"The emerging B5G and 6G applications have brought forth the need for high-precision indoor localization. However, the complexity of indoor environments poses significant challenges to this goal, particularly due to the presence of non-line-of-sight (NLOS) conditions and multipath effects. This letter proposes an attention-based positioning network (ABPN) that exploits fine-grained features from MIMO channel state information (CSI) by spatial attention to combat the limited receptive field of traditional convolutional neural networks (CNNs) as well as channel attention to discriminate the importance of different wireless channels. Extensive experiments, conducted on two real-world datasets, demonstrate that the proposed ABPN outperforms the popular PirnatEco, AAresCNN, MIMOnet and CLnet with an average localization accuracy improvement of over 50%.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 2","pages":"373-377"},"PeriodicalIF":3.7,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}