  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.
