An Improved Reconstruction Method for Compressive Sensing Based OFDM Channel Estimation

In the orthogonal frequency division multiplexing (OFDM) system, channel estimation is significant in that it affects the reliability of coherent detection at the receiver. Compressive sensing based channel estimation demands fewer pilots than traditional methods and improves the resource utilization in a great manner. Greedy algorithms have a weakness in terms of anti-noise capacity. Combining compressive sampling matching pursuit (CoSaMP) with exponential smoothing, an improved reconstruction method is proposed in order to suppress noise. The noise suppression capacity of exponential smoothing is analyzed in theory. Simulation results indicate that the proposed method is superior to CoSaMP especially for high noise or low speed situation at a cost of low additional computational complexity.