Wideband MIMO Channel Estimation for Hybrid Beamforming Millimeter Wave Systems via Random Spatial Sampling

Abstract

Millimeter Wave (mmWave) massive Multiple Input Multiple Output (MIMO) systems realizing directive communication over large bandwidths via Hybrid analog and digital BeamForming (HBF) require reliable estimation of the wideband wireless channel. However, the hardware limitations with HBF architectures in conjunction with the short coherence time inherit in mmWave communication render this estimation a challenging task. In this paper, we develop a novel wideband channel estimation framework for mmWave massive MIMO systems with HBF reception. The proposed framework jointly exploits the low rank property and the available angular information to provide more accurate channel recovery, especially for short beam training intervals. We introduce a novel analog combining architecture that includes a random spatial sampling structure placed before the input of the analog received signals to the digital component of the HBF receiver. This architecture supports the proposed matrix-completion-based estimation approach in providing the sampling set of measurements for recovering the unknown channel matrix. The performance improvement of the proposed approach over representative state-of-the-art techniques is demonstrated through numerous computer simulation results.