A Compressed Sensing Sparse Channel Estimation Method for Unique Word Prefixed Single Carrier Frequency Domain Equalization

被引：0

作者：

Meng Qingwei ^{[1
]}

Meng Xiangru ^{[1
]}

Ma Zhiqiang ^{[1
]}

机构：

[1] Air Force Engn Univ, Informat & Nav Coll, Xian, Shaanxi, Peoples R China

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (ICSPCC) | 2017年

关键词：

SC-FDE; Compressed Sensing; Unique Word; Toeplitz Measure Matrices; Sparse Channel Estimation; SYSTEMS;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In this paper, a compressed sensing (CS) based sparse channel estimation method is proposed for Unique Word (UW) Prefixed SC-FDE employed in sparse wireless channels, sparse channel estimation is formulated as a typical CS problem, and UW generation schemes arc discussed, in addition, Dantzig square selector is used to recover sparse channel impulse response (CIR) from limited number of noisy observation measurements. Simulation results based on a typical sparse underwater acoustic channel profile show that CS based channel estimation methods outperform the widely utilized time domain and frequency domain least-square (LS) channel estimation methods in bit error rate (BER) and normalized mean-square error (NMSE). The channel estimation accuracy can be significantly improved compared to time domain US estimation method.

引用

页数：5

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