Sparse multi-band signal recovery based on support refining for modulated wideband converter

Abstract

The continuous-time sparse multi-band signal can be acquired with sub-Nyquist rate by modulated wideband converter (MWC), which is a novel sampling technique based on compressed sensing and alleviates the pressure of high sampling rate. The performance of existing reconstruction algorithm for MWC suffers from low probability of successful recovery, especially when the signal noise ratio (SNR) is not high. In this paper, a sparse multi-band signal recovery algorithm based on support refining (SRSR) is proposed for MWC. Particularly, the support refining process is incorporated into the reconstruction stage of MWC. The initial support of the original multi-band signal is firstly acquired by the existing multi measurement vector (MMV) algorithm. Then, the support refining process refines the initial support to extract the inaccurate support information. Finally, the whole recovery algorithm ends up with recovering the remaining support by the existing MMV algorithm. Simulation results demonstrate that the proposed SRSR algorithm improves the success rate of sparse multi-band signal recovery and enables MWC require fewer channels of sampling architecture and lower hardware complexity.