Improved Channel Estimator Based on Superimposed Training

被引：0
作者：
Shi, Zhe [1 ]
机构：
[1] Chinese Acad Sci, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
来源：
PROCEEDINGS OF FIRST INTERNATIONAL CONFERENCE OF MODELLING AND SIMULATION, VOL III: MODELLING AND SIMULATION IN ELECTRONICS, COMPUTING, AND BIO-MEDICINE | 2008年
关键词：
Channel estimation; Superimposed training; Multipath channels; First order statistics;
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
Because of high bandwidth efficiency and low complexity, channel estimation based on superimposed training (ST) has received wide considerations in recent years. In this paper we first analysis the ST method in frequency domain analysis. Then a new iterative method for channel estimation is proposed based on the ST method. Received sequences and estimation of channel state information are used to do iterative computing in receiver. Computer simulations show that mean square error (MSE) and bit error rate (BER) improvements can be observed after 3-4 iterations.
引用
收藏
页码：251 / 255
页数：5
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