A Novel Time-Varying and Sparse Channel Estimation Based on Compress Sensing

In fast-varying and sparse orthogonal frequency division multiplexing(OFDM) system model,the existing methods utilize basic expansion model to estimation and use constant amplitude zero auto correlation (CAZAC) sequence to detect delays.By means of the channel’s sparse response matrix,this paper proposes a compress sensing(CS) method for detecting delays via orthogonal matching pursuit(OMP).Simulation results show that both CAZAC and OMP methods can improve the effectiveness of channel estimation.However,when Doppler shift is increasing,the proposed method can attain better performance.