Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems
Yongzhi Li, Cheng Tao, Gonzalo Seco-Granados, Amine Mezghani, A. Lee, Swindlehurst, Liu Liu

TL;DR
This paper proposes a novel channel estimation method for one-bit massive MIMO systems using Bussgang decomposition, providing analytical insights into system performance and design optimization.
Contribution
It introduces a Bussgang-based channel estimator for one-bit MIMO, outperforming previous methods and deriving closed-form achievable rate expressions for system analysis.
Findings
The proposed estimator outperforms existing methods across all SNRs.
Closed-form achievable rate expressions are derived for flat fading channels.
Insights into optimal resource allocation and system design are obtained.
Abstract
This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output (MIMO) system. Each receive antenna of the base station (BS) is assumed to be equipped with a pair of one-bit analog-to-digital converters (ADCs) to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer as a linear functionwith identical first- and second-order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form expressions for the achievable rate in flat fading channels assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes…
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