Nonlinear 1-Bit Precoding for Massive MU-MIMO with Higher-Order Modulation

TL;DR

This paper introduces nonlinear precoding algorithms for massive MU-MIMO systems with 1-bit DACs, enabling higher-order modulation schemes like 8-PSK and 16-QAM with low error rates, reducing power and costs.

Contribution

It develops novel low-complexity nonlinear precoding algorithms supporting high-order modulation in 1-bit DAC massive MU-MIMO systems, outperforming linear methods.

Findings

Nonlinear precoding achieves low error rates with high-order modulation.

Linear-quantized precoding suffers from high error floors.

Algorithms are compatible with blind and training-based channel estimation.

Abstract

Massive multi-user (MU) multiple-input multiple- output (MIMO) is widely believed to be a core technology for the upcoming fifth-generation (5G) wireless communication standards. The use of low-precision digital-to-analog converters (DACs) in MU-MIMO base stations is of interest because it reduces the power consumption, system costs, and raw baseband data rates. In this paper, we develop novel algorithms for downlink precoding in massive MU-MIMO systems with 1-bit DACs that support higher-order modulation schemes such as 8-PSK or 16-QAM. Specifically, we present low-complexity nonlinear precoding algorithms that achieve low error rates when combined with blind or training-based channel-estimation algorithms at the user equipment. These results are in stark contrast to linear-quantized precoding algorithms, which suffer from a high error floor if used with high-order modulation schemes and 1-bit DACs.