Adaptive Digital Channelization of Sparse Wideband Analog Signals at Sub-Nyquist Rate

Abstract

Considering that the conventional digital channelized receiver requires a high sampling rate for a wideband signal and produces a cross-channel problem due to unknown prior information of the received signals, a method of adaptive digital channelization based on compress sensing (CS) theory is proposed in this paper. The method consists of three parts, i.e., modulated wideband converter (MWC) sampling system, sparse recovery algorithm, synthesis filter banks. MWC sampling system is applied to receive sparse wideband analog signals at sub-Nyquist sampling rate. Sparse recovery algorithm such as sparsity adaptive matching pursuit (SAMP) is chosen to recover the channelized signals. Based on the adjacent channels containing signals, the complete wideband signal can be obtained by the synthesis filter banks adaptively, thus solving the cross-channel problem. Finally, the numerical experiments demonstrate that the proposed method can implement adaptive channelization of sparse wideband signal at sub-Nyquist sampling rate.