{"title":"ENERGY-EFFICIENT JOINT ANTENNA AND USER SELECTION IN SINGLE-CELL MASSIVE MIMO SYSTEMS","authors":"Mangqing Guo, M. C. Gursoy","doi":"10.1109/GlobalSIP.2018.8646642","DOIUrl":null,"url":null,"abstract":"An energy-efficient joint antenna and user selection algorithm in single-cell massive multiple-input multiple-output (MIMO) communication systems is proposed in this paper. The proposed algorithm involves a two-step iterative procedure. At each time, we first obtain a subset of antennas for the given set of users via bisection search and random selection, and then obtain the optimally energy efficient subset of users with the selected antennas using cross-entropy algorithm. This two-step procedure is shown to improve the energy efficiency (EE) at each iteration. Simulation results show that the EE could be improved by 71.16% with the maximum-ratio combining (MRC) receiver when the total number of users is 60.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"128 21","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2018.8646642","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
An energy-efficient joint antenna and user selection algorithm in single-cell massive multiple-input multiple-output (MIMO) communication systems is proposed in this paper. The proposed algorithm involves a two-step iterative procedure. At each time, we first obtain a subset of antennas for the given set of users via bisection search and random selection, and then obtain the optimally energy efficient subset of users with the selected antennas using cross-entropy algorithm. This two-step procedure is shown to improve the energy efficiency (EE) at each iteration. Simulation results show that the EE could be improved by 71.16% with the maximum-ratio combining (MRC) receiver when the total number of users is 60.