Sparsity-Aware Adaptive Channel Estimation Based on SNR Detection

Time domain synchronous orthogonal frequency division multiplexing OFDM (TDS-OFDM) has a higher spectral efficiency and faster synchronization than standard cyclic prefix OFDM, but suffers from the performance loss over multipath fading channels due to severe interblock-interference. Recently, compressive sensing (CS) is explored to solve those problems, but it heavily relies on the sparsity level of the channel, which is unknown in practice. In this paper, a signal-to-noise ratio-based sparsity estimation method is proposed to detect the sparsity level of the channel. Then we propose the priori aided subspace pursuit algorithm if the channel sparsity meets the theoretical CS model, otherwise we use an improved iterative channel estimation method with the help of the channel sparsity. Simulation results demonstrate that the proposed scheme could improve the robustness and performance of TDS-OFDM systems compared with the conventional iterative methods or recently proposed CS based methods.