A priori aided compressive sensing approach for impulsive noise reconstruction

In this paper, a novel impulsive noise (IN) cancellation scheme based on priori aided compressive sensing (CS) for OFDM-based communications systems is proposed. The IN is reconstructed from the frequency-domain measurements at the null sub-carriers based on the CS theory using greedy algorithms. With the aid of the a priori partial support obtained from the proposed time-domain thresholding method, we propose the enhanced greedy algorithm of priori aided sparsity adaptive matching pursuit (PA-SAMP) to improve the accuracy and robustness of the IN recovery. Theoretical analysis and computer simulations validate that the proposed method outperforms conventional CS-based and other classical IN mitigation methods for OFDM-based communications systems.