Adaptive subspace pursuit based channel estimation method for TDS-OFDM systems

Recently, compressive sensing (CS) algorithms have been adopted to improve the accuracy of channel estimation for wide-band wireless communication systems. Since the wireless channel is usually time and frequency doubly selective fading, the performance of CS based channel estimation is limited by the estimation accuracy of the channel's sparsity level. In this paper, an adaptive subspace pursuit (ASP) algorithm is proposed which can search the sparsity level and update channel estimation result dynamically. The advantage of the proposed ASP method is that it does not need sparsity level as a priori information. Simulation results demonstrate that the proposed method outperforms conventional methods and the latest CS based methods.