  The paper studies a reconfigurable intelligent surface (RIS)-assisted
multi-user uplink massive multiple-input multiple-output (MIMO) system with
imperfect hardware. At the RIS, the paper considers phase noise, while at the
base station, the paper takes into consideration the radio frequency
impairments and low-resolution analog-to-digital converters. The paper derives
approximate expressions for the ergodic achievable rate in closed forms under
Rician fading channels. For the cases of infinite numbers of antennas and
infinite numbers of reflecting elements, asymptotic data rates are derived to
provide new design insights. The derived power scaling laws indicate that while
guaranteeing a required system performance, the transmit power of the users can
be scaled down at most by the factor 1/M when M goes infinite, or by the factor
1/(MN) when M and N go infinite, where M is the number of antennas and N is the
number of the reflecting units. Furthermore, an optimization algorithm is
proposed based on the genetic algorithm to solve the phase shift optimization
problem with the aim of maximizing the sum rate of the system. Additionally,
the optimization problem with discrete phase shifts is considered. Finally,
numerical results are provided to validate the correctness of the analytical
results.
