{"title":"Distributed Sparse Activity Detection in Cell-Free Massive MIMO Systems","authors":"Mangqing Guo, M. C. Gursoy","doi":"10.1109/GlobalSIP45357.2019.8969500","DOIUrl":null,"url":null,"abstract":"Distributed sparse activity detection in cell-free massive multiple-input multiple-output (MIMO) systems is considered in this paper. At the beginning of each channel coherence interval, all the active users send pilots to the access points (APs). Then, each AP makes its own decision on the activity of all the users based on the approximate message passing (AMP) iterative procedure. Following this, the optimal fusion rule is used at the fusion center to make the final decisions on the activity of all the users based on the individual decisions and the corresponding reliability obtained at all the APs. The performance levels of this distributed sparse activity detection method are analyzed with Monte Carlo simulations.","PeriodicalId":221378,"journal":{"name":"2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP45357.2019.8969500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
Distributed sparse activity detection in cell-free massive multiple-input multiple-output (MIMO) systems is considered in this paper. At the beginning of each channel coherence interval, all the active users send pilots to the access points (APs). Then, each AP makes its own decision on the activity of all the users based on the approximate message passing (AMP) iterative procedure. Following this, the optimal fusion rule is used at the fusion center to make the final decisions on the activity of all the users based on the individual decisions and the corresponding reliability obtained at all the APs. The performance levels of this distributed sparse activity detection method are analyzed with Monte Carlo simulations.