DoA-Aided MMSE Channel Estimation for Wireless Communication Systems

Abstract

This paper investigates using side information in minimum mean square error (MMSE) estimation. We propose a direction-of-arrival (DoA)-aided two-stage channel estimation technique that utilizes information about the dominant direction of the channel. To this end, the decomposition of the MMSE channel estimation into two orthogonal subspaces is formulated. After estimating the channel along the dominant direction, we utilize a Gaussian mixture model to estimate the conditionally Gaussian distributed random vector, which represents the multipath propagation. The proposed two-stage estimator allows pre-computing the respective estimation filters, tremendously reducing the computational complexity. Numerical simulations depict the superior performance of our proposed two-stage estimation approach compared to state-of-the-art methods.