  In this paper, to tackle the blockage issue in massive
multiple-input-multiple-output (mMIMO) systems, a reconfigurable intelligent
surface (RIS) is seamlessly deployed to support devices with ultra-reliable and
low-latency communications (URLLC). The transmission power of the base station
and the phase shifts of the RIS are jointly devised to maximize the weighted
sum rate while considering the spatially correlation and channel estimation
errors. Firstly, \textcolor{black}{the relationship between the channel
estimation error and spatially correlated RIS's elements is revealed by using
the linear minimum mean square error}. Secondly, based on the maximum-ratio
transmission precoding, a tight lower bound of the rate under short packet
transmission is derived. Finally, the NP-hard problem is decomposed into two
optimization problems, where the transmission power is obtained by geometric
programming and phase shifts are designed by using gradient ascent method.
Besides, we have rigorously proved that the proposed algorithm can rapidly
converge to a sub-optimal solution with low complexity. Simulation results
confirm the tightness between the analytic results and Monte Carlo simulations.
Furthermore, the two-timescale scheme provides a practical solution for the
short packet transmission.
