  We investigate a reconfigurable intelligent surface (RIS)-aided multi-user
massive multiple-input multi-output (MIMO) system where low-resolution
digital-analog converters (DACs) are configured at the base station (BS) in
order to reduce the cost and power consumption. An approximate analytical
expression for the downlink achievable rate is derived based on maximum ratio
transmission (MRT) and additive quantization noise model (AQNM), and the rate
maximization problem is solved by particle swarm optimization (PSO) method
under both continuous phase shifts (CPSs) and discrete phase shifts (DPSs) at
the RIS. Simulation results show that the downlink sum achievable rate tends to
a constant with the increase of the number of quantization bits of DACs, and
three quantization bits are enough to capture a large portion of the
performance of the ideal perfect DACs case.
