{"title":"Blind code timing and carrier offset estimation for DS-CDMA systems","authors":"K. Amleh, Hongbin Li","doi":"10.1109/ICASSP.2003.1202714","DOIUrl":null,"url":null,"abstract":"We consider the problem of joint carrier offset and code timing estimation for CDMA (code division multiple access) systems. In contrast to most existing schemes which require a multi-dimensional search over the parameter space, we propose a blind estimator that solves the joint estimation problem algebraically. By exploiting the noise subspace of the covariance matrix of the received data, the multiuser estimation is decoupled into parallel estimations of individual users, which makes computations efficient. The proposed estimator is non-iterative and near-far resistant. It can deal with frequency-selective and time-varying channels. The performance of the proposed scheme is illustrated by some computer simulations.","PeriodicalId":104473,"journal":{"name":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03).","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2003.1202714","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
We consider the problem of joint carrier offset and code timing estimation for CDMA (code division multiple access) systems. In contrast to most existing schemes which require a multi-dimensional search over the parameter space, we propose a blind estimator that solves the joint estimation problem algebraically. By exploiting the noise subspace of the covariance matrix of the received data, the multiuser estimation is decoupled into parallel estimations of individual users, which makes computations efficient. The proposed estimator is non-iterative and near-far resistant. It can deal with frequency-selective and time-varying channels. The performance of the proposed scheme is illustrated by some computer simulations.