An Improved Channel Estimation Algorithm Based on Superimposed Training Sequence

被引：0

作者：

Yang Jie ^{[1
]}

Zhang Huamin ^{[1
]}

Xie Wu ^{[2
]}

机构：

[1] Heilongjiang Univ, Coll Elect Engn, Harbin 150080, Peoples R China

[2] Harbin Engn Univ, Informat & Commun Engn Coll, Harbin 150001, Peoples R China

来源：

MATERIALS SCIENCE AND ENGINEERING, PTS 1-2 | 2011年 / 179-180卷

关键词：

MIMO; Training Sequence; LS; CRB; Channel Estimation;

D O I：

10.4028/www.scientific.net/AMR.179-180.482

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

A channel estimation algorithm based on superimposed training sequence is proposed in this paper. The algorithm does not need the allocation of time slot for superimposed training sequence, and it can estimate the channel coefficients without loss of bandwidth. The mean squared difference, Cramer-Rao bound and the lower bound of channel capacity are deduced based on the LS algorithm of channel estimation. It has simple structure, less computational requirement by using the LS algorithm. The result of simulation shows that the performance of system is improved to a large extent by using superimposed training sequence rather than direct training sequence, and the capacity of system is also increased.

引用

页码：482 / +

页数：2

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