  In this paper, we study the problem of sparse channel estimation via a
collaborative and fully distributed approach. The estimation problem is
formulated in the angular domain by exploiting the spatially common sparsity
structure of the involved channels in a multi-user scenario. The sparse channel
estimation problem is solved via an efficient distributed approach in which the
participating users collaboratively estimate their channel sparsity support
sets, before locally estimate the channel values, under the assumption that
global and common support subsets are present. The performance of the proposed
algorithm, named WDiOMP, is compared to DiOMP, local OMP and a centralized
solution based on SOMP, in terms of the support set recovery error under
various experimental scenarios. The efficacy of WDiOMP is demonstrated even in
the case in which the underlining sparsity structure is unknown.
