  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.
