Narrow-Band Interference Mitigation Using Compressive Sensing for AF-OFDM Systems

We investigate narrow-band-interference (NBI) mitigation for single and multiple relay amplify-and-forward (AF) orthogonal-frequency-division-multiplexing (OFDM) cooperative communication systems. Based on the channel gains between the interferer, destination, and relay nodes, three copies or more of the NBI signal are received at the destination node, in addition to the desired signal. NBI degrades the performance of AF-OFDM systems, which motivates the need for NBI mitigation techniques. NBI is a sparse signal in the frequency-domain (FD); hence, a compressive sensing framework can be used to estimate NBI and cancel it before detecting the transmitted signal. However, frequency-grid-mismatch destroys the sparsity of NBI in the FD at the receiver. Therefore, we propose a structured-dictionary-mismatch formulation to estimate the frequency-grid-mismatch and recover NBI in the FD. While convex optimization techniques can be used to recover NBI, their computational complexity is high. Therefore, we apply a block-orthogonal-matching-pursuit greedy algorithm to reduce the computational complexity of NBI recovery, where the sensing matrix is rearranged to have sparse blocks. Simulation results demonstrate the advantages of our proposed approach.