Pub Date : 2026-01-23DOI: 10.1109/twc.2026.3654880
Maher Marwani, Georges Kaddoum
{"title":"Event-Based Temporal Graph Neural Network for Radio Resource Management","authors":"Maher Marwani, Georges Kaddoum","doi":"10.1109/twc.2026.3654880","DOIUrl":"https://doi.org/10.1109/twc.2026.3654880","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"75 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042774","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the proliferation of software-defined radio technology, malicious jamming attacks against wireless communications have become more aggressive and flexible, which could easily create a complex and highly dynamic jamming environment by varying both the jamming parameters and the jamming policies. Such a complex jamming environment makes it challenging for most of deep reinforcement learning (DRL) based anti-jamming schemes in rapidly identifying effective strategies. In this paper, we have developed a dual-tier policy-oriented anti-jamming (DPA) scheme based on DRL to facilitate swift adaptation to the complex jamming environment. Unlike existing works, an upper-tier jamming pattern recognition (JPR) network is introduced to extract underlying jamming policy-related information which serves as a guidance for the lower-tier deep recurrent Q-network on anti-jamming decision-making. The output of the JPR network can enable the sharing of experiences among various jamming patterns originated from the same jamming policy and facilitate more efficient and targeted anti-jamming strategic learning. Extensive experimental results demonstrate that the superiority of our DPA scheme over other DRL-based benchmark schemes in terms of both anti-jamming performance and convergence speed.
{"title":"A Dual-Tier Policy-Oriented Anti-Jamming Scheme Based on Deep Reinforcement Learning","authors":"Xingyun Chen;Haichuan Ding;Ying Ma;Xuanheng Li;Jianping An;Yuguang Fang","doi":"10.1109/TWC.2026.3653807","DOIUrl":"https://doi.org/10.1109/TWC.2026.3653807","url":null,"abstract":"With the proliferation of software-defined radio technology, malicious jamming attacks against wireless communications have become more aggressive and flexible, which could easily create a complex and highly dynamic jamming environment by varying both the jamming parameters and the jamming policies. Such a complex jamming environment makes it challenging for most of deep reinforcement learning (DRL) based anti-jamming schemes in rapidly identifying effective strategies. In this paper, we have developed a dual-tier policy-oriented anti-jamming (DPA) scheme based on DRL to facilitate swift adaptation to the complex jamming environment. Unlike existing works, an upper-tier jamming pattern recognition (JPR) network is introduced to extract underlying jamming policy-related information which serves as a guidance for the lower-tier deep recurrent Q-network on anti-jamming decision-making. The output of the JPR network can enable the sharing of experiences among various jamming patterns originated from the same jamming policy and facilitate more efficient and targeted anti-jamming strategic learning. Extensive experimental results demonstrate that the superiority of our DPA scheme over other DRL-based benchmark schemes in terms of both anti-jamming performance and convergence speed.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10652-10668"},"PeriodicalIF":10.7,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-23DOI: 10.1109/twc.2026.3654761
Hao Lin, Mustafa A. Kishk, Mohamed-Slim Alouini
{"title":"HAPS-enabled Downlink Coverage Enhancement in Islands and Maritime Areas","authors":"Hao Lin, Mustafa A. Kishk, Mohamed-Slim Alouini","doi":"10.1109/twc.2026.3654761","DOIUrl":"https://doi.org/10.1109/twc.2026.3654761","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"40 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146043163","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-23DOI: 10.1109/twc.2026.3654846
Kai Zhang, Xuanyu Cao, Khaled B. Letaief
{"title":"Federated Learning With Energy Harvesting Devices: An MDP Framework","authors":"Kai Zhang, Xuanyu Cao, Khaled B. Letaief","doi":"10.1109/twc.2026.3654846","DOIUrl":"https://doi.org/10.1109/twc.2026.3654846","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"44 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-23DOI: 10.1109/TWC.2026.3655372
Xuhui Chen;Junyu Liu;Min Sheng;Jiandong Li
Reusing existing terrestrial base stations (TBSs) for ground-to-air (G2A) coverage has emerged as a promising method to enhance communication service for aerial users (AUs). However, due to distinct coverage areas, G2A coverage cannot achieve seamless coverage of ground-to-ground coverage, necessitating flexible TBS beam adjustment to satisfy communication demands of different areas. Moreover, reusing TBSs for G2A coverage inevitably sacrifices coverage performance for ground users (GUs). In this paper, we propose a transmissive reconfigurable intelligent surface (RIS)-enabled coverage method and a time-division beam switching (TDBS) strategy, which allows flexible beam adjustment and simultaneous coverage for AUs and GUs. Specifically, coverage probability (CP) for AUs and GUs is analyzed to evaluate the simultaneous coverage performance. Results show that increasing G2A TBSs enhances CP for AU, which, however, comes at the cost of severely degrading CP for GUs. Moreover, an optimal G2A TBS ratio exists, indicating that simply increasing G2A TBSs is not always effective in coverage improvement. Thus, the TDBS strategy is proposed, where part of G2A TBSs alternately serve AUs and GUs. Simulations demonstrate that the proposed strategy significantly enhances CP for GUs and AUs at high altitudes, with only a slight trade-off in CP for AUs at low altitudes.
{"title":"Transmissive RIS-Enabled Simultaneous Coverage for Aerial and Ground Users in Cellular Networks","authors":"Xuhui Chen;Junyu Liu;Min Sheng;Jiandong Li","doi":"10.1109/TWC.2026.3655372","DOIUrl":"https://doi.org/10.1109/TWC.2026.3655372","url":null,"abstract":"Reusing existing terrestrial base stations (TBSs) for ground-to-air (G2A) coverage has emerged as a promising method to enhance communication service for aerial users (AUs). However, due to distinct coverage areas, G2A coverage cannot achieve seamless coverage of ground-to-ground coverage, necessitating flexible TBS beam adjustment to satisfy communication demands of different areas. Moreover, reusing TBSs for G2A coverage inevitably sacrifices coverage performance for ground users (GUs). In this paper, we propose a transmissive reconfigurable intelligent surface (RIS)-enabled coverage method and a time-division beam switching (TDBS) strategy, which allows flexible beam adjustment and simultaneous coverage for AUs and GUs. Specifically, coverage probability (CP) for AUs and GUs is analyzed to evaluate the simultaneous coverage performance. Results show that increasing G2A TBSs enhances CP for AU, which, however, comes at the cost of severely degrading CP for GUs. Moreover, an optimal G2A TBS ratio exists, indicating that simply increasing G2A TBSs is not always effective in coverage improvement. Thus, the TDBS strategy is proposed, where part of G2A TBSs alternately serve AUs and GUs. Simulations demonstrate that the proposed strategy significantly enhances CP for GUs and AUs at high altitudes, with only a slight trade-off in CP for AUs at low altitudes.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10576-10588"},"PeriodicalIF":10.7,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-23DOI: 10.1109/twc.2026.3654423
Xinxin He, Zhiyong Yang, Dianang Li, Jie Zeng, Tao Jiang, Shanzhi Chen
{"title":"Dual-Stage Reinforcement Learning-Based Beam Tracking for Integrated Sensing and Communications in V2I Scenarios","authors":"Xinxin He, Zhiyong Yang, Dianang Li, Jie Zeng, Tao Jiang, Shanzhi Chen","doi":"10.1109/twc.2026.3654423","DOIUrl":"https://doi.org/10.1109/twc.2026.3654423","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"4 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-22DOI: 10.1109/twc.2026.3654401
Nan Li, Yansha Deng, Dusit Niyato
{"title":"Goal-Oriented Semantic Communication for Wireless Video Transmission via Generative AI","authors":"Nan Li, Yansha Deng, Dusit Niyato","doi":"10.1109/twc.2026.3654401","DOIUrl":"https://doi.org/10.1109/twc.2026.3654401","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"101 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146042785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 : 2026-01-22DOI: 10.1109/TWC.2026.3655004
Jinsong Hu;Mingfeng Ji;Yida Wang;Shihao Yan;Youjia Chen;Feng Shu;Jun Li
In this paper, we construct a framework for covert communication assisted by a full-duplex (FD) receiver with movable antennas (MAs). Specifically, we consider artificial noise (AN) whose transmit power follows a uniform distribution to confuse the warden equipped with the MA and derive the closed-form expressions for the communication covertness and the transmission outage probability, respectively. In the considered system, we formulate a problem to maximize the covert throughput by jointly optimizing the MAs’ positions, beamforming vector, and the transmit power of AN. To cope with the high coupling of the proposed problem, we obtain the optimal AN power and then propose an alternating optimization (AO) algorithm, where semidefinite relaxation (SDR) and projected gradient descent (PGD) are employed to optimize the beamforming vector and the MAs’ positions, respectively. Numerical results validate the effectiveness of the proposed algorithm and further compare the cases that the warden is equipped with the MA or the fixed-position antenna (FPA). As for the MA-deployed warden, the utilization of the MA at the transmitter can significantly improve the covert throughput. In addition, as for the conventional FPA-deployed warden, there exists an optimal intermediate distance between the transmit and receive antennas of the FD receiver to maximize the covert transmission throughput.
{"title":"Movable Antennas With Full-Duplex Receiver for Covert Communication","authors":"Jinsong Hu;Mingfeng Ji;Yida Wang;Shihao Yan;Youjia Chen;Feng Shu;Jun Li","doi":"10.1109/TWC.2026.3655004","DOIUrl":"https://doi.org/10.1109/TWC.2026.3655004","url":null,"abstract":"In this paper, we construct a framework for covert communication assisted by a full-duplex (FD) receiver with movable antennas (MAs). Specifically, we consider artificial noise (AN) whose transmit power follows a uniform distribution to confuse the warden equipped with the MA and derive the closed-form expressions for the communication covertness and the transmission outage probability, respectively. In the considered system, we formulate a problem to maximize the covert throughput by jointly optimizing the MAs’ positions, beamforming vector, and the transmit power of AN. To cope with the high coupling of the proposed problem, we obtain the optimal AN power and then propose an alternating optimization (AO) algorithm, where semidefinite relaxation (SDR) and projected gradient descent (PGD) are employed to optimize the beamforming vector and the MAs’ positions, respectively. Numerical results validate the effectiveness of the proposed algorithm and further compare the cases that the warden is equipped with the MA or the fixed-position antenna (FPA). As for the MA-deployed warden, the utilization of the MA at the transmitter can significantly improve the covert throughput. In addition, as for the conventional FPA-deployed warden, there exists an optimal intermediate distance between the transmit and receive antennas of the FD receiver to maximize the covert transmission throughput.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"10589-10603"},"PeriodicalIF":10.7,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146026401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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