DoA-Aided MMSE Channel Estimation for Wireless Communication Systems

TL;DR

This paper introduces a DoA-aided two-stage MMSE channel estimation method that decomposes channels into LoS and multipath components, significantly reducing complexity and outperforming existing techniques.

Contribution

It proposes a novel two-stage estimation approach combining DoA estimation with Gaussian mixture models, enhancing efficiency and accuracy in wireless channel estimation.

Findings

Superior performance over state-of-the-art methods

Reduced computational complexity

Effective decomposition of channels into LoS and multipath components

Abstract

This paper investigates the combination of parametric channel estimation with minimum mean square error (MMSE) estimation. We propose a direction-of-arrival (DoA)-aided two-stage channel estimation technique that utilizes the decomposition of wireless communication channels into a line-of-sight (LoS) path and its orthogonal subspace. 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 with typical channel models depict the superior performance of our proposed two-stage estimation approach compared to state-of-the-art methods.