A Novel Distributed Stagewise Orthogonal Matching Pursuit Algorithm for mmWave MIMO Channel Estimation

Abstract

In this letter, we investigate the problem of multiple-input multiple-output (MIMO) mmWave channel estimation in a hybrid analog-digital architecture by exploiting both sparsity and the structure of the channel. To gain noise robustness, we first introduce a method that applies the Stagewise Orthogonal Matching Pursuit (StOMP) algorithm to a distributed setting, where subsystems over sub-carriers share the same support set. To further enhance the accuracy of the estimation, we propose a novel algorithm to estimate the number of paths present in the channel. This technique leverages a modified Silhouette method to determine the exact support for the mmWave sparse system, thereby reducing the ambiguity of the estimate returned by the Distributed StOMP (DStOMP) algorithm. Simulation results demonstrate that our proposed method outperforms the standard OMP method and achieves nearly the same recovery accuracy compared to the Simultaneous OMP method, even without prior knowledge of signal sparsity.