Distributed Support Detection of Jointly Sparse Signals
Sophie M. Fosson, Javier Matamoros, Carles Antón-Haro, Enrico Magli
39th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Firenze, Italy, May 4-9, 2014
Abstract
In this paper, we address the problem of distributed support detection of multiple sparse signals with common support.
Specifically, signals are acquired by the individual nodes of a network according to the so-called Joint Sparsity Model 2 (JSM-2). By leveraging on this model, we propose a distributed scheme for in-network signal recovery, i.e. not requiring data gathering and processing at a fusion center, based on distributed iterative thresholding and consensus strategies. For the proposed scheme, whose convergence properties we rigorously prove, no a priori knowledge on the non-zero number of entries in the signal vector is required.
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