We address the problem of distributed recovery of sparse signals in a resource constrained network. We assume that the network nodes sense a common sparse signal and therefore share an approximately common support. We propose a Bayesian algorithm that performs distributed recovery of the sparse signals and is agnostic to the sparse signal distribution. The algorithm requires nodes in the network to communicate only with their neighbors to estimate the sparse signals and is designed to reduce the communication load between nodes. Simulations have been performed to show that the algorithm requires significantly less communication among the nodes as compared to other algorithms.
Distributed Bayesian Sparse Signal Recovery Algorithm with Minimal Communication Load in Networks
24.06.2024
393048 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Sparse Signal Recovery via Residual Minimization Pursuit
British Library Online Contents | 2014
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