An Improved Zero-attracting Normalized Least Mean Square Algorithm for Sparse Channel Estimation

被引：0
|
作者：
Li, Yingsong [1 ]
Wang, Yanyan [1 ]
Jin, Zhan [1 ]
机构：
[1] Harbin Engn Univ, Coll Informat & Commun Engn, Harbin, Peoples R China
来源：
2016 PROGRESS IN ELECTROMAGNETICS RESEARCH SYMPOSIUM (PIERS) | 2016年
关键词：
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
An improved zero-attracting normalized least mean square (IZA-NLMS) algorithm is proposed for sparse channel estimation. The proposed algorithm is realized by using the error sequence to design the step-size of the sparse-aware normalized least mean square (NLMS) algorithms. Also, the computational complexity reduction strategy is used in the proposed IZA-NLMS algorithm. Computer simulations are constructed to verify the performance of the proposed IZA-NLMS algorithm over a sparse multi-path channel. The simulation results show that the proposed IZA-NLMS algorithm provides faster convergence speed and lower mean square error in comparison with the previously proposed sparse-aware NLMS algorithms.
引用
收藏
页码：5001 / 5005
页数：5
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