Improved smoothed L0 reconstruction algorithm for ISI sparse channel estimation

doi:10.1016/S1005-8885(14)60284-3

中国邮电高校学报(英文) ›› 2014, Vol. 21 ›› Issue (2): 40-47.doi: 10.1016/S1005-8885(14)60284-3

Improved smoothed L0 reconstruction algorithm for ISI sparse channel estimation

刘婷,周杰

南京信息工程大学

收稿日期:2013-04-19 修回日期:2014-02-17 出版日期:2014-04-30 发布日期:2014-04-30
通讯作者: 刘婷 E-mail:liutingpn@163.com
基金资助:
国家自然科学基金资助项目;国家教育部留学基金委启动基金资助项目;江苏省科技支撑计划（工业）基金资助项目

Improved smoothed L0 reconstruction algorithm for ISI sparse channel estimation

Department of Communications, Nanjing University of Information Science and Technology, Nanjing 210044, China 2. Department of Electronic and Electrical Engineering, Niigata University, Niigata 950-2181, Japan

Received:2013-04-19 Revised:2014-02-17 Online:2014-04-30 Published:2014-04-30
Supported by:
the National Nature Science Foundation of China (61372128), the Scientific & Technological Support Project (Industry) of Jiangsu Province (BE2011195).

摘要/Abstract

摘要：

In this paper, the problem of inter symbol interference (ISI) sparse channel estimation in wireless communication with the application of compressed sensing is investigated. However, smoothed L0 norm algorithm (SL0) has ‘notched effect’ due to the negative iterative gradient direction. Moreover, the property of continuous function in SL0 is not steep enough, which results in inaccurate estimations and low convergence. Afterwards, we propose the Lagrange multipliers as well as Newton method to optimize SL0 algorithm in order to obtain a more rapid and efficient signal reconstruction algorithm, improved smoothed L0 (ISL0). ISI channel estimation will have a direct effect on the performance of ISI equalizer at the receiver. So, we design a pre-filter model which with no considerable loss of optimality and do analyses of the equalization methods of the sparse multi-path channel. Real-time simulation results clearly show that the ISL0 algorithm can estimate the ISI sparse channel much better in both signal noise ratio (SNR) and compression levels. In the same channel conditions, ISL0 algorithm has been greatly improved when compared with the SL0 algorithm and other compressed-sensing algorithms.

关键词:

compressed-sensing, channel model, ISI, improved SL0 algorithm, sparse channel estimation, MIMO system

Abstract:

Key words:

compressed-sensing, channel model, ISI, improved SL0 algorithm, sparse channel estimation, MIMO system

中图分类号:

TN911.6

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Improved smoothed L0 reconstruction algorithm for ISI sparse channel estimation

Improved smoothed L0 reconstruction algorithm for ISI sparse channel estimation

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