{"title":"The semi-blind multiuser receiver based on antenna array","authors":"Xingqing Cheng, Qiang Wu, Daoben Li","doi":"10.1109/ICCT.2003.1209740","DOIUrl":null,"url":null,"abstract":"Two semi-blind multi-user receiver's algorithms based on antenna array are proposed. Here we suppose multiple receiver antennas are our targets. Firstly we estimate the known users' data and subtract them form the received signal. Secondly we obtain an orthogonal projection matrix (M) of the unknown users' signal through subspace tracking. Finally by using the matrix M, we transform the detection problem of known users' data into a minimization problem of quadratic convex function and so that we can solve it with conjugate gradient (CG) algorithm. The initial estimation of known users' data also serves as the initial value of CG to speed up convergence. We have simulated the performance of the receivers' algorithm under various conditions and concluded that they are better than other corresponding algorithms.","PeriodicalId":237858,"journal":{"name":"International Conference on Communication Technology Proceedings, 2003. ICCT 2003.","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Communication Technology Proceedings, 2003. ICCT 2003.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT.2003.1209740","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
Two semi-blind multi-user receiver's algorithms based on antenna array are proposed. Here we suppose multiple receiver antennas are our targets. Firstly we estimate the known users' data and subtract them form the received signal. Secondly we obtain an orthogonal projection matrix (M) of the unknown users' signal through subspace tracking. Finally by using the matrix M, we transform the detection problem of known users' data into a minimization problem of quadratic convex function and so that we can solve it with conjugate gradient (CG) algorithm. The initial estimation of known users' data also serves as the initial value of CG to speed up convergence. We have simulated the performance of the receivers' algorithm under various conditions and concluded that they are better than other corresponding algorithms.