{"title":"Secrecy Capacity Maximization for IRS-Assisted High-Speed Train Communications","authors":"Cuiran Li;Jiahui Luan;Zepeng Zhang;Bo Ai;Hao Wu;Jianli Xie","doi":"10.1109/LCOMM.2025.3559484","DOIUrl":null,"url":null,"abstract":"In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanism are utilized to characterize highly time-varying wireless channels. The secrecy capacity optimization problem is formulated by jointly optimizing the transmit beamforming, artificial noise (AN) matrix, and IRS phase shifts, subject to transmit power and unit modulus constraints. To solve the non-convex problem, it is transformed into convex optimization problem by using weighted minimum mean square error (WMMSE) algorithm, and an alternating optimization strategy with coupled variables is used to derive the optimal solution. Simulation results show that the optimization algorithm proposed in this letter converges quickly and achieves higher secrecy capacity.","PeriodicalId":13197,"journal":{"name":"IEEE Communications Letters","volume":"29 6","pages":"1290-1294"},"PeriodicalIF":3.7000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10962236/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanism are utilized to characterize highly time-varying wireless channels. The secrecy capacity optimization problem is formulated by jointly optimizing the transmit beamforming, artificial noise (AN) matrix, and IRS phase shifts, subject to transmit power and unit modulus constraints. To solve the non-convex problem, it is transformed into convex optimization problem by using weighted minimum mean square error (WMMSE) algorithm, and an alternating optimization strategy with coupled variables is used to derive the optimal solution. Simulation results show that the optimization algorithm proposed in this letter converges quickly and achieves higher secrecy capacity.
期刊介绍:
The IEEE Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of communication over different media and channels including wire, underground, waveguide, optical fiber, and storage channels. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of communication systems.