Pub Date : 2026-02-10DOI: 10.1109/twc.2026.3660250
Xinren Zhang, Jiadong Yu
{"title":"Improve the Training Efficiency of DRL for Wireless Communication Resource Allocation: The Role of Generative Diffusion Models","authors":"Xinren Zhang, Jiadong Yu","doi":"10.1109/twc.2026.3660250","DOIUrl":"https://doi.org/10.1109/twc.2026.3660250","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"189 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161376","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 : 2026-02-10DOI: 10.1109/twc.2026.3660314
Fangming Zou, Yiqing Zhai, Wuyang Jiang, Ying Cui
{"title":"DNNini-UPSCA: Optimal Beamforming and Power Control for D2D Networks via DNN and UPSCA","authors":"Fangming Zou, Yiqing Zhai, Wuyang Jiang, Ying Cui","doi":"10.1109/twc.2026.3660314","DOIUrl":"https://doi.org/10.1109/twc.2026.3660314","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"46 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161377","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 : 2026-02-10DOI: 10.1109/twc.2026.3660931
Zihao Zhou, Cheng-Xiang Wang, Jie Huang, Lijian Xin, Li Zhang, El-Hadi M. Aggoune
{"title":"A General 6G Cross-Band Channel Model Towards Standardization Verified by 0.7–39 GHz Channel Measurements","authors":"Zihao Zhou, Cheng-Xiang Wang, Jie Huang, Lijian Xin, Li Zhang, El-Hadi M. Aggoune","doi":"10.1109/twc.2026.3660931","DOIUrl":"https://doi.org/10.1109/twc.2026.3660931","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"46 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161365","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 : 2026-02-10DOI: 10.1109/twc.2026.3660948
Zhen Du, Jingjing Xu, Yifeng Xiong, Jie Wang, Musa Furkan Keskin, Henk Wymeersch, Fan Liu, Shi Jin
{"title":"Probabilistic Constellation Shaping for OFDM ISAC Signals Under Temporal-Frequency Filtering","authors":"Zhen Du, Jingjing Xu, Yifeng Xiong, Jie Wang, Musa Furkan Keskin, Henk Wymeersch, Fan Liu, Shi Jin","doi":"10.1109/twc.2026.3660948","DOIUrl":"https://doi.org/10.1109/twc.2026.3660948","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"157 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161371","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 : 2026-02-10DOI: 10.1109/twc.2026.3660841
Kuranage Roche Rayan Ranasinghe, Kengo Ando, Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu, Takumi Takahashi, Marco Di Renzo, G. David Gonźalez
{"title":"A Flexible Design Framework for Integrated Communication and Computing Receivers","authors":"Kuranage Roche Rayan Ranasinghe, Kengo Ando, Hyeon Seok Rou, Giuseppe Thadeu Freitas de Abreu, Takumi Takahashi, Marco Di Renzo, G. David Gonźalez","doi":"10.1109/twc.2026.3660841","DOIUrl":"https://doi.org/10.1109/twc.2026.3660841","url":null,"abstract":"","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"101 1","pages":""},"PeriodicalIF":10.4,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161373","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 : 2026-02-10DOI: 10.1109/TWC.2026.3660641
Xianxin Song;Xianghao Yu;Jie Xu;Derrick Wing Kwan Ng
In this paper, we investigate a bistatic integrated sensing and communications (ISAC) system, consisting of a base station (BS) with multiple transmit antennas, a sensing receiver with multiple receive antennas, a single-antenna communication user (CU), and a point target to be sensed. Specifically, the BS transmits a superposition of Gaussian information and deterministic sensing signals to support ISAC. The BS aims to deliver information symbols to the CU, while the sensing receiver aims to estimate the target’s direction-of-arrival (DoA) with respect to the sensing receiver by processing the echo signals reflected by the target. For the sensing receiver, we assume that only the sequences of the deterministic sensing signals and the covariance matrix of the information signals are perfectly known, whereas the specific realizations of the information signals remain unavailable. Under this setup, we first derive the corresponding Cramér-Rao bounds (CRBs) for DoA estimation and propose practical estimators to accurately estimate the target’s DoA. Subsequently, we formulate the transmit beamforming design as an optimization problem aiming to minimize the CRB, subject to a minimum signal-to-interference-plus-noise ratio (SINR) requirement at the CU and a maximum transmit power constraint at the BS. When the BS employs only Gaussian information signals, the resulting beamforming optimization problem is convex, enabling the derivation of an optimal solution. In contrast, when both Gaussian information and deterministic sensing signals are transmitted, the resulting problem is non-convex and a locally optimal solution is acquired by exploiting successive convex approximation (SCA). Finally, numerical results demonstrate that the utilization of additional deterministic sensing signals is critical for sensing performance enhancement, while solely employing Gaussian information signals leads to a notable performance degradation for target sensing. It is unveiled that the proposed transmit beamforming design achieves a superior ISAC performance boundary compared with various benchmark schemes.
{"title":"CRB-Rate Tradeoff for Bistatic ISAC With Gaussian Information and Deterministic Sensing Signals","authors":"Xianxin Song;Xianghao Yu;Jie Xu;Derrick Wing Kwan Ng","doi":"10.1109/TWC.2026.3660641","DOIUrl":"10.1109/TWC.2026.3660641","url":null,"abstract":"In this paper, we investigate a bistatic integrated sensing and communications (ISAC) system, consisting of a base station (BS) with multiple transmit antennas, a sensing receiver with multiple receive antennas, a single-antenna communication user (CU), and a point target to be sensed. Specifically, the BS transmits a superposition of Gaussian information and deterministic sensing signals to support ISAC. The BS aims to deliver information symbols to the CU, while the sensing receiver aims to estimate the target’s direction-of-arrival (DoA) with respect to the sensing receiver by processing the echo signals reflected by the target. For the sensing receiver, we assume that only the sequences of the deterministic sensing signals and the covariance matrix of the information signals are perfectly known, whereas the specific realizations of the information signals remain unavailable. Under this setup, we first derive the corresponding Cramér-Rao bounds (CRBs) for DoA estimation and propose practical estimators to accurately estimate the target’s DoA. Subsequently, we formulate the transmit beamforming design as an optimization problem aiming to minimize the CRB, subject to a minimum signal-to-interference-plus-noise ratio (SINR) requirement at the CU and a maximum transmit power constraint at the BS. When the BS employs only Gaussian information signals, the resulting beamforming optimization problem is convex, enabling the derivation of an optimal solution. In contrast, when both Gaussian information and deterministic sensing signals are transmitted, the resulting problem is non-convex and a locally optimal solution is acquired by exploiting successive convex approximation (SCA). Finally, numerical results demonstrate that the utilization of additional deterministic sensing signals is critical for sensing performance enhancement, while solely employing Gaussian information signals leads to a notable performance degradation for target sensing. It is unveiled that the proposed transmit beamforming design achieves a superior ISAC performance boundary compared with various benchmark schemes.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"11768-11782"},"PeriodicalIF":10.7,"publicationDate":"2026-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146161366","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 : 2026-02-09DOI: 10.1109/TWC.2026.3659809
Zhe Wang;Jiayi Zhang;Bokai Xu;Dusit Niyato;Bo Ai;Shiwen Mao;Zhu Han
In this paper, we investigate the low-complexity distributed combining scheme design for near-field cell-free extremely large-scale multiple-input-multiple-output (CF XL-MIMO) systems. Firstly, we construct the uplink spectral efficiency (SE) performance analysis framework for CF XL-MIMO systems over centralized and distributed processing schemes. Notably, we derive the centralized minimum mean-square error (CMMSE) and local minimum mean-square error (LMMSE) combining schemes over arbitrary channel estimators. Then, focusing on the CMMSE and LMMSE combining schemes, we propose five low-complexity distributed combining schemes based on the matrix approximation methodology or the symmetric successive over relaxation (SSOR) algorithm. More specifically, we propose two matrix approximation methodology-aided combining schemes: Global Statistics & Local Instantaneous information-based MMSE (GSLI-MMSE) and Statistics matrix Inversion-based LMMSE (SI-LMMSE). These two schemes are derived by approximating the global instantaneous information in the CMMSE combining and the local instantaneous information in the LMMSE combining with the global and local statistics information by asymptotic analysis and matrix expectation approximation, respectively. Moreover, by applying the low-complexity SSOR algorithm to iteratively solve the matrix inversion in the LMMSE combining, we derive three distributed SSOR-based LMMSE combining schemes, distinguished from the applied information and initial values.
本文研究了近场无小区超大规模多输入多输出（CF - XL-MIMO）系统的低复杂度分布式组合方案设计。首先，我们构建了CF xml - mimo系统在集中和分布式处理方案下的上行频谱效率（SE）性能分析框架。值得注意的是，我们推导了任意信道估计上的集中最小均方误差（CMMSE）和局部最小均方误差（LMMSE）组合方案。然后，针对CMMSE和LMMSE组合方案，提出了基于矩阵逼近法和对称逐次过松弛（SSOR）算法的5种低复杂度分布式组合方案。更具体地说，我们提出了两种矩阵逼近方法辅助的组合方案：基于全球统计和局部瞬时信息的MMSE （GSLI-MMSE）和基于统计矩阵反演的LMMSE （SI-LMMSE）。这两种方案分别是通过渐近分析和矩阵期望逼近，分别逼近CMMSE组合中的全局瞬时信息和LMMSE组合中的局部瞬时信息以及全局和局部统计信息。此外，通过采用低复杂度的SSOR算法迭代求解LMMSE组合中的矩阵反演问题，推导出了三种基于sor的分布式LMMSE组合方案，并将其与应用信息和初始值进行了区分。
{"title":"Low-Complexity Distributed Combining Design for Near-Field Cell-Free XL-MIMO Systems","authors":"Zhe Wang;Jiayi Zhang;Bokai Xu;Dusit Niyato;Bo Ai;Shiwen Mao;Zhu Han","doi":"10.1109/TWC.2026.3659809","DOIUrl":"10.1109/TWC.2026.3659809","url":null,"abstract":"In this paper, we investigate the low-complexity distributed combining scheme design for near-field cell-free extremely large-scale multiple-input-multiple-output (CF XL-MIMO) systems. Firstly, we construct the uplink spectral efficiency (SE) performance analysis framework for CF XL-MIMO systems over centralized and distributed processing schemes. Notably, we derive the centralized minimum mean-square error (CMMSE) and local minimum mean-square error (LMMSE) combining schemes over arbitrary channel estimators. Then, focusing on the CMMSE and LMMSE combining schemes, we propose five low-complexity distributed combining schemes based on the matrix approximation methodology or the symmetric successive over relaxation (SSOR) algorithm. More specifically, we propose two matrix approximation methodology-aided combining schemes: Global Statistics & Local Instantaneous information-based MMSE (GSLI-MMSE) and Statistics matrix Inversion-based LMMSE (SI-LMMSE). These two schemes are derived by approximating the global instantaneous information in the CMMSE combining and the local instantaneous information in the LMMSE combining with the global and local statistics information by asymptotic analysis and matrix expectation approximation, respectively. Moreover, by applying the low-complexity SSOR algorithm to iteratively solve the matrix inversion in the LMMSE combining, we derive three distributed SSOR-based LMMSE combining schemes, distinguished from the applied information and initial values.","PeriodicalId":13431,"journal":{"name":"IEEE Transactions on Wireless Communications","volume":"25 ","pages":"11799-11815"},"PeriodicalIF":10.7,"publicationDate":"2026-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146146079","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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