电子学报 ›› 2017, Vol. 45 ›› Issue (12): 2848-2854.DOI: 10.3969/j.issn.0372-2112.2017.12.004

• 学术论文 • 上一篇    下一篇

一种基于改进ROMP的MIMO-OFDM信道估计方法

廖勇1,2, 周昕1, 沈轩帆1, 洪观3   

  1. 1. 重庆大学飞行器测控与通信教育部重点实验室, 重庆 400044;
    2. 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;
    3. 重庆大学通信工程学院, 重庆 400044
  • 收稿日期:2016-08-26 修回日期:2016-11-02 出版日期:2017-12-25 发布日期:2017-12-25
  • 通讯作者: 廖勇
  • 作者简介:周昕,女,1993年出生于重庆市渝北区.现为重庆大学通信工程学院硕士研究生.主要研究方向为宽带无线通信、压缩感知、信道估计.E-mail:Mrs-zhouxin@163.com;沈轩帆,男,1994年出生于云南省昆明市.现为重庆大学通信工程学院硕士研究生.主要研究方向为无线通信信道估计.E-mail:shenxuanfan@foxmail.com;洪观,男,1992年出生于辽宁省丹东市.现为重庆大学通信工程学院硕士研究生.主要研究方向为无线通信、频谱感知.E-mail:18696603949@163.com
  • 基金资助:
    国家自然科学基金(No.61501066);重庆市基础与前沿研究计划项目(No.cstc2015jcyjA40003);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开放基金(No.ISN16-03);中央高校基本科研业务费重点基金(No.CDJZR165505)

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

LIAO Yong1,2, ZHOU Xin1, SHEN Xuan-fan1, HONG Guan3   

  1. 1. Key Laboratory of Aerocraft TT & C and Communication, Ministry of Education, Chongqing University, Chongqing 400044, China;
    2. The State Key Laboratory of Integrated Services Networks, Xidian University, Xi'an, Shaanxi 710071, China;
    3. College of Communication Engineering, Chongqing University, Chongqing 400044, China
  • Received:2016-08-26 Revised:2016-11-02 Online:2017-12-25 Published:2017-12-25

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.

关键词: 多入多出, 正交频分复用, 压缩感知, 贪婪方法, 信道估计

Abstract: The regularized orthogonal matching pursuit (ROMP) has two drawbacks,ie,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).

Key words: multiple input multiple output (MIMO), orthogonal frequency division multiplexing (OFDM), compressed sensing, greedy method, channel estimation

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