Analysis of One-Bit Quantized Precoding for the Multiuser Massive MIMO Downlink

TL;DR

This paper analyzes linear precoders for massive MIMO downlink systems with one-bit DACs, deriving performance expressions and proposing an optimized precoder that outperforms traditional methods at low-to-moderate SNR.

Contribution

It provides a mathematical analysis of one-bit quantized precoding, including a new optimized linear precoder, using Bussgang theorem for improved performance insights.

Findings

Quantized ZF precoder performance depends on antenna-to-user ratio.

Proposed optimized precoder outperforms maximum likelihood at low-to-moderate SNR.

Asymptotic expression for symbol error rate derived.

Abstract

We present a mathematical analysis of linear precoders for downlink massive MIMO multiuser systems that employ one-bit digital-to-analog converters at the basestation in order to reduce complexity and mitigate power usage. The analysis is based on the Bussgang theorem, and applies generally to any linear precoding scheme. We examine in detail the special case of the quantized zero-forcing (ZF) precoder, and derive a simple asymptotic expression for the resulting symbol error rate at each terminal. Our analysis illustrates that the performance of the quantized ZF precoder depends primarily on the ratio of the number of antennas to the number of users, and our simulations show that it can outperform the much more complicated maximum likelihood encoder for low-to-moderate signal to noise ratios, where massive MIMO systems are presumed to operate. We also use the Bussgang theorem to derive a new linear precoder optimized for the case of one-bit quantization, and illustrate its improved performance.