One-bit massive MIMO precoding via a minimum symbol-error probability design

TL;DR

This paper introduces a novel one-bit precoding scheme for massive MIMO systems that minimizes symbol error rate, using an efficient iterative algorithm to improve performance with low-resolution DACs.

Contribution

It proposes a SER-based one-bit precoding method formulated as a biconvex optimization problem, solved with BCD and FISTA techniques, enhancing high-order modulation performance.

Findings

Outperforms existing algorithms in bit error rate for high-order modulations

Efficient iterative algorithm converges rapidly

Significantly reduces hardware complexity and power consumption

Abstract

Massive multiple-input multiple-output (MIMO) has the potential to substantially improve the spectral efficiency, robustness and coverage of mobile networks. However, such potential is limited by hardware cost and power consumption associated with a large number of RF chains. Recently, one-bit quantization is proposed to address this issue by replacing high-resolution digital-to-analog converters (DACs) with one-bit DACs, thereby simplifying the RF chains. Despite low system cost, advanced signal processing techniques are needed to compensate for quantization distortions caused by low resolution DACs. In this paper, a symbol-error-rate (SER)-based one-bit precoding scheme is proposed to minimize the detection error probability of all users under one-bit constraints. The problem is recast as a continuous optimization problem with a biconvex objective. By applying the block coordinate descent (BCD) method and the FISTA method, we develop an efficient iterative algorithm to obtain a one-bit precoding solution. Simulation results demonstrate its superiority over state-of-the-art algorithms in terms of bit error rate performance in high-order modulation cases.