{"title":"A deterministic Schur method for multichannel blind identification","authors":"L. Deneire, D. Slock","doi":"10.1109/SPAWC.1999.783072","DOIUrl":null,"url":null,"abstract":"We address the problem of blind multichannel identification in a communication context. Using a deterministic model for the input symbols and only second order statistics, we develop a simple algorithm, based on the generalized Schur algorithm to apply LDU decomposition of the covariance matrix of the received data. We show that this method leads to identification of the channel, up to a constant. Furthermore, the identification algorithm is shown to yield similar performance as the subspace method (Moulines et al. 1995). This paper complements Deneire and Slock where we developed a stochastic Schur algorithm.","PeriodicalId":365086,"journal":{"name":"1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications (Cat. No.99EX304)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1999-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1999 2nd IEEE Workshop on Signal Processing Advances in Wireless Communications (Cat. No.99EX304)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPAWC.1999.783072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We address the problem of blind multichannel identification in a communication context. Using a deterministic model for the input symbols and only second order statistics, we develop a simple algorithm, based on the generalized Schur algorithm to apply LDU decomposition of the covariance matrix of the received data. We show that this method leads to identification of the channel, up to a constant. Furthermore, the identification algorithm is shown to yield similar performance as the subspace method (Moulines et al. 1995). This paper complements Deneire and Slock where we developed a stochastic Schur algorithm.