OFDM sparse channel estimation based on RSAMP algorithm

被引：1
|
作者：
Ji C. [1 ,2 ]
Wang J. [1 ,2 ]
Li B. [3 ]
机构：
[1] School of Computer Science and Engineering, Northeastern University, Shenyang
[2] Key Laboratory of Intelligent Computing in Medical Image, Ministry of Education, Northeastern University, Shenyang
[3] School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan
来源：
Li, Boqun | 1600年 / Chinese Institute of Electronics卷 / 43期
关键词：
Channel estimation; Observation matrix; Orthogonal frequency division multiplexing (OFDM) system; Prediction of sparsity; Reconstruction algorithm; Restricted isometry property (RIP) criterion;
D O I：
10.12305/j.issn.1001-506X.2021.08.31
中图分类号：
学科分类号：
摘要：
In order to improve the reconstruction performance of the sparsity adaptive greedy iteration (SAGI) algorithm and shorten the reconstruction time, a restricted isometry property (RIP) based prediction-sparsity adaptive matching pursuit (RSAMP) algorithm is proposed and successfully applied to channel estimation of orthogonal frequency division multiplexing (OFDM) system. Firstly, a RIP based sparsity prediction method is proposed, which can approximate the real sparsity quickly and accurately in the case of unknown sparsity, greatly reducing the running time of the algorithm. Secondly, the observation matrix is optimized by principal component analysis, which improves the reconstruction performance of the algorithm. Simulation experiments show that the proposed RSAMP algorithm in this paper can achieve better channel estimation performance and shorter running time compared with SAMP algorithm and SAGI algorithm. © 2021, Editorial Office of Systems Engineering and Electronics. All right reserved.
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页码：2290 / 2296
页数：6
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