Subspace Tracking and Least Squares Approaches to Channel Estimation in Millimeter Wave Multiuser MIMO

TL;DR

This paper introduces new subspace and least squares algorithms for efficient MIMO channel estimation at millimeter wave frequencies, accounting for hybrid beamforming and demonstrating improved performance and complexity trade-offs.

Contribution

It develops novel subspace tracking and least squares algorithms tailored for hybrid millimeter wave MIMO systems, enhancing channel estimation accuracy and efficiency.

Findings

Algorithms accurately estimate dominant singular vectors.

Proposed methods outperform competing approaches in spectral efficiency.

Effective in both single-user and multi-user scenarios.

Abstract

The problem of MIMO channel estimation at millimeter wave frequencies, both in a single-user and in a multi-user setting, is tackled in this paper. Using a subspace approach, we develop a protocol enabling the estimation of the right (resp. left) singular vectors at the transmitter (resp. receiver) side; then, we adapt the projection approximation subspace tracking with deflation and the orthogonal Oja algorithms to our framework and obtain two channel estimation algorithms. We also present an alternative algorithm based on the least squares approach. The hybrid analog/digital nature of the beamformer is also explicitly taken into account at the algorithm design stage. In order to limit the system complexity, a fixed analog beamformer is used at both sides of the communication links. The obtained numerical results, showing the accuracy in the estimation of the channel matrix dominant singular vectors, the system achievable spectral efficiency, and the system bit-error-rate, prove that the proposed algorithms are effective, and that they compare favorably, in terms of the performance-complexity trade-off, with respect to several competing alternatives.