一种基于改进ROMP的MIMO-OFDM信道估计方法

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.

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

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).