A Channel Estimation Method Based on Improved Regularized Orthogonal Matching Pursuit for MIMO-OFDM Systems

LIAO Yong; ZHOU Xin; SHEN Xuan-fan; HONG Guan

doi:10.3969/j.issn.0372-2112.2017.12.004

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A Channel Estimation Method Based on Improved Regularized Orthogonal Matching Pursuit for MIMO-OFDM Systems

更新时间：2025-07-16

- A Channel Estimation Method Based on Improved Regularized Orthogonal Matching Pursuit for MIMO-OFDM Systems
- Acta Electronica Sinica Vol. 45, Issue 12, Pages: 2848-2854(2017)
- 作者机构：
  
  1. 重庆大学通信工程学院,重庆,400044
  2. 重庆大学飞行器测控与通信教育部重点实验室,重庆,400044
  3. 西安电子科技大学综合业务网理论及关键技术国家重点实验室,陕西,西安,710071
- 作者简介：
- 基金信息：
  
  National Natural Science Foundation of China (No.61501066);Chongqing Research Program of Basic and Frontier Technology (No.cstc2015jcyjA40003);Open Fund for State Key Laboratory of Integrated Service Networks of Xidian University (No.ISN16-03);Fundamental Research Funds for the Central Universities (No.CDJZR165505)
- DOI：10.3969/j.issn.0372-2112.2017.12.004
  CLC： TN911.72
- Published Online：25 December 2017，
  
  Published：2017
- 稿件说明：
移动端阅览
LIAO Yong, ZHOU Xin, SHEN Xuan-fan, et al. A Channel Estimation Method Based on Improved Regularized Orthogonal Matching Pursuit for MIMO-OFDM Systems[J]. Acta Electronica Sinica, 2017, 45(12): 2848-2854.
DOI：

LIAO Yong, ZHOU Xin, SHEN Xuan-fan, et al. A Channel Estimation Method Based on Improved Regularized Orthogonal Matching Pursuit for MIMO-OFDM Systems[J]. Acta Electronica Sinica, 2017, 45(12): 2848-2854. DOI： 10.3969/j.issn.0372-2112.2017.12.004.

摘要

本文根据信道响应的时域稀疏性，引入压缩感知理论，针对正则化正交匹配追踪（ROMP）需已知稀疏度和原子一旦选入无法删除两大缺点，提出一种基于改进ROMP的信道估计方法.该方法结合压缩采样匹配追踪（CoSaMP）、稀疏度自适应匹配追踪（SAMP）和变步长的优点，实现稀疏信号快速准确的重建.仿真结果表明，与基于OMP、ROMP、CoSaMP、SAMP的信道估计方法相比，所提方法有效提高了MIMO-OFDM系统的归一化均方误差（NMSE）和误码率（BER）性能.

Abstract

The regularized orthogonal matching pursuit (ROMP) has two drawbacks

the sparsity should be known beforehand and once the atom is determined it can not be deleted.According to these two problems

this paper presents an improved ROMP channel estimation method based on compressive sensing by exploiting the sparse structure of channel impulse response.The proposed method combines the advantages of compressive sampling matching pursuit (CoSaMP)

sparsity adaptive matching pursuit (SAMP) and variable step size to achieve the reconstruction of sparse signal quickly and accurately.Simulation results demonstrate that compared with the channel estimations respectively based on OMP

ROMP

CoSaMP and SAMP

the proposed method effectively improve the performance of the MIMO-OFDM systems in the normalized mean square error (NMSE) and bit error rate (BER).

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