Distributed support detection of jointly sparse signals
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.