Low-rank mmWave MIMO channel estimation in one-bit receivers

TL;DR

This paper introduces low-rank channel estimation algorithms for mmWave systems with one-bit ADCs, addressing the challenges of extreme quantization and large antenna arrays, and demonstrating improved reconstruction over sparsity-based methods.

Contribution

It proposes novel low-rank based channel estimation algorithms and a low complexity training method tailored for one-bit mmWave receivers.

Findings

Achieves better channel reconstruction than compressed sensing methods.

Utilizes low-rank property of mmWave channels for improved estimation.

Offers a low complexity implementation for practical use.

Abstract

Receivers with one-bit analog-to-digital converters (ADCs) are promising for high bandwidth millimeter wave (mmWave) systems as they consume less power than their full resolution counterparts. The extreme quantization in one-bit receivers and the use of large antenna arrays at mmWave make channel estimation challenging. In this paper, we develop channel estimation algorithms that exploit the low-rank property of mmWave channels. We also propose a novel training solution that results in a low complexity implementation of our algorithms. Simulation results indicate that the proposed methods achieve better channel reconstruction than compressed sensing-based techniques that exploit sparsity of mmWave channels.