基于压缩感知的OFDM系统信道估计中重建算法

Reconstruction Algorithm Based on Compressed Sensing OFDM System Channel Estimation

论文就压缩感知技术在正交频分复用(Orthogonal frequency division multiplexing,OFDM)系统稀疏信道估计中的应用进行研究。在分析正交匹配追踪(Orthogonal matching pursuit,OMP)、压缩采样匹配追踪(Compressive sampling matching pursuit,CoSaMP)、正则正交匹配追踪(Regularized orthogonal matching pursuit,ROMP)这3种压缩感知重建算法的基础上,依据3种算法的均方误差(Mean square error,MSE)和误比特率(Bit error rate,BER),提出性能较优方案。

This paper studies the application of compressed sensing technology in orthogonal frequency division multiplexing （OFDM） systems sparse channel estimation. It analyses three reconstruction algorithms： orthogonal matching pursuit （OMP）, compressive sampling matching pursuit （CoSaMP）, and regularized orthogonal matching pursuit （ROMP）. According to the mean square error （MSE） and the bit error rate （BER） the paper proposes an algorithm of better performance.