Structured compressive sensing based narrowband interference mitigation for vehicular communications

Abstract

In this paper, a novel narrowband interference (NBI) cancellation scheme based on structured compressive sensing (SCS) for dependable vehicular communications systems is proposed. The temporal joint correlation of the repeated training sequences in the preamble are exploited by SCS-based differential measuring (SCS-DM) to acquire the joint measurements matrix of the NBI. Using the proposed structured sparsity adaptive matching pursuit (S-SAMP) algorithm, the sparse high-dimensional NBI signal can be accurately recovered and cancelled out at the receiver. Simulation results validate that the proposed SCS-DM approach outperforms conventional CS-based and non-CS-based NBI mitigation schemes under wireless vehicular channels.