Fast communication: Retrieval of sparse solutions of multiple-measurement vectors via zero-point attracting projection

Authors:
Yang You;Laming Chen;Yuantao Gu;Wei Feng;Hui Dai
Affiliations:
Institute of Communication Engineering, PLA University of Science and Technology, Nanjing, China;Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;Department of Electronic Engineering, Tsinghua University, Beijing 100084, China;China Electronic Equipment System Engineering Corporation, Beijing, China;China Electronic Equipment System Engineering Corporation, Beijing, China
Venue:
Signal Processing
Year:
2012

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Abstract

A new sparse signal recovery algorithm for multiple-measurement vectors (MMV) problem is proposed in this paper. The sparse representation is iteratively drawn based on the idea of zero-point attracting projection (ZAP). In each iteration, the solution is first updated along the negative gradient direction of an approximate @?"2","0 norm to encourage sparsity, and then projected to the solution space to satisfy the under-determined equation. A variable step size scheme is adopted further to accelerate the convergence as well as to improve the recovery accuracy. Numerical simulations demonstrate that the performance of the proposed algorithm exceeds the references in various aspects, as well as when applied to the modulated wideband converter, where recovering MMV problem is crucial to its performance.