Narrowband Channel Estimation for Hybrid Beamforming Millimeter Wave Communication Systems with One-bit Quantization

TL;DR

This paper introduces a novel narrowband channel estimation algorithm for mmWave systems using hybrid beamforming and one-bit ADCs, demonstrating improved accuracy over traditional methods through simulation.

Contribution

It proposes a GAMP-based channel estimation algorithm tailored for one-bit quantized hybrid beamforming mmWave systems, addressing the challenge of channel estimation under low-resolution quantization.

Findings

GAMP variants outperform least-squares methods without quantization

The proposed one-bit GAMP achieves the lowest estimation error among variants

Using more frames and RF chains improves estimation performance

Abstract

Millimeter wave (mmWave) spectrum has drawn attention due to its tremendous available bandwidth. The high propagation losses in the mmWave bands necessitate beamforming with a large number of antennas. Traditionally each antenna is paired with a high-speed analog-to-digital converter (ADC), which results in high power consumption. A hybrid beamforming architecture and one-bit resolution ADCs have been proposed to reduce power consumption. However, analog beamforming and one-bit quantization make channel estimation more challenging. In this paper, we propose a narrowband channel estimation algorithm for mmWave communication systems with one-bit ADCs and hybrid beamforming based on generalized approximate message passing (GAMP). We show through simulation that 1) GAMP variants with one-bit ADCs have better performance than do least-squares estimation methods without quantization, 2) the proposed one-bit GAMP algorithm achieves the lowest estimation error among the GAMP variants, and 3) exploiting more frames and RF chains enhances the channel estimation performance.