{"title":"Optimization of Physical Layer Security in IRSs-assisted Cell-Free Massive MIMO Systems","authors":"Xuan-Toan Dang, Oh-Soon Shin","doi":"10.1109/APWCS60142.2023.10234028","DOIUrl":null,"url":null,"abstract":"In this study, we examine the physical layer security challenge in a cell-free massive multiple-input multiple-output (MIMO) system with multiple intelligent reflecting surfaces (IRSs), referred to as IRSs-CFMM. To maximize the secrecy downlink rate, we introduce a problem formulation that simultaneously optimizes the beamforming at all access points (APs) and the phase shift of all IRSs. To tackle this intricate optimization problem, we utilize an alternating algorithm that achieves at least a locally optimal solution. Our numerical findings confirm that the proposed algorithm effectively addresses the problem with low computational complexity.","PeriodicalId":375211,"journal":{"name":"2023 VTS Asia Pacific Wireless Communications Symposium (APWCS)","volume":"279 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 VTS Asia Pacific Wireless Communications Symposium (APWCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APWCS60142.2023.10234028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we examine the physical layer security challenge in a cell-free massive multiple-input multiple-output (MIMO) system with multiple intelligent reflecting surfaces (IRSs), referred to as IRSs-CFMM. To maximize the secrecy downlink rate, we introduce a problem formulation that simultaneously optimizes the beamforming at all access points (APs) and the phase shift of all IRSs. To tackle this intricate optimization problem, we utilize an alternating algorithm that achieves at least a locally optimal solution. Our numerical findings confirm that the proposed algorithm effectively addresses the problem with low computational complexity.