Quantized Precoding for Massive MU-MIMO

TL;DR

This paper investigates low-resolution DACs in massive MU-MIMO systems, showing that 3-4 bit DACs nearly match infinite-resolution performance and proposing nonlinear precoding for 1-bit DACs that significantly outperforms linear methods.

Contribution

It provides a closed-form approximation for the rate with coarse quantization and introduces nonlinear precoding algorithms for 1-bit DACs, reducing performance gap.

Findings

3-4 bit DACs approach infinite-resolution performance

Nonlinear precoding reduces 1-bit DAC penalty to 3 dB

Linear precoding incurs about 8 dB penalty at 10^-3 BER

Abstract

Massive multiuser (MU) multiple-input multiple-output (MIMO) is foreseen to be one of the key technologies in fifth-generation wireless communication systems. In this paper, we investigate the problem of downlink precoding for a narrowband massive MU-MIMO system with low-resolution digital-to-analog converters (DACs) at the base station (BS). We analyze the performance of linear precoders, such as maximal-ratio transmission and zero-forcing, subject to coarse quantization. Using Bussgang's theorem, we derive a closed-form approximation on the rate achievable under such coarse quantization. Our results reveal that the performance attainable with infinite-resolution DACs can be approached using DACs having only 3 to 4 bits of resolution, depending on the number of BS antennas and the number of user equipments (UEs). For the case of 1-bit DACs, we also propose novel nonlinear precoding algorithms that significantly outperform linear precoders at the cost of an increased computational complexity. Specifically, we show that nonlinear precoding incurs only a 3 dB penalty compared to the infinite-resolution case for an uncoded bit error rate of 10^-3, in a system with 128 BS antennas that uses 1-bit DACs and serves 16 single-antenna UEs. In contrast, the penalty for linear precoders is about 8 dB.