An efficient decentralized approach for mmWave MIMO Channel Estimation

In the physical propagation environment, the channel matrices of neighboring users exhibit a joint sparsity structure due to the shared scatterers at the Base Station (BS) side. Based on this observation, we consider a multi-user Multiple-Input Multiple-Output (MIMO) system where the sparse channel estimation problem is tackled via an efficient fully distributed approach based on compressive sensing (CS). The involved users cooperatively estimate the sparsity support sets of the involved channels before individually estimate the channel coefficients, assuming that global and common sparsity support subsets exist. The performance of the proposed algorithm, named Weighted Distributed Simultaneous Orthogonal Matching Pursuit (WDiSOMP), is compared to Distributed Simultaneous Orthogonal Matching Pursuit (DiSOMP), local Simultaneous Orthogonal Matching Pursuit (SOMP) and a centralized solution based on SOMP in terms of the channel estimation under a multi-tasking scenario.