Doubly-selective multiuser channel estimation using superimposed training and discrete prolate spheroidal basis expansion models

被引:0
|
作者
He, Shuangchi [1 ]
Tugnait, Jitendra K. [1 ]
机构
[1] Auburn Univ, Dept Elect & Comp Engn, Auburn, AL 36849 USA
关键词
doubly-selective channels; channel estimation; basis expansion models; multiuser channels;
D O I
暂无
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Channel estimation for multiuser doubly-selective channels is considered using superimposed training. The time-varying channel is assumed to be described by a discrete prolate spheroidal basis expansion model (DPS-BEM). A user-specific periodic training sequence is arithmetically added (superimposed) at a low power to each user's information sequence at the transmitter before modulation and transmission. A two step approach is adopted where in the first step we estimate the channel using only the first-order statistics of the observations. Using the estimated channel from the first step, a Viterbi detector is used to estimate the information sequence. In the second step a deterministic maximum likelihood (DML) approach is used to iteratively estimate the multiuser channel and the information sequences sequentially.
引用
收藏
页码:861 / +
页数:2
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