  The main difficulty concerning optimizing the mutual information (MI) in
reconfigurable intelligent surface (RIS)-aided communication systems with
discrete signaling is the inability to formulate this optimization problem in
an analytically tractable manner. Therefore, we propose to use the cutoff rate
(CR) as a more tractable metric for optimizing the MI and introduce two
optimization methods to maximize the CR, assuming perfect knowledge of the
channel state information (CSI). The first method is based on the projected
gradient method (PGM), while the second method is derived from the principles
of successive convex approximation (SCA). Simulation results show that the
proposed optimization methods significantly enhance the CR and the
corresponding MI.
