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. 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.

翻译：在可重新配置智能表面辅助通信系统方面,最优化相互信息(MI)的主要困难是无法以可分析的可移动方式提出这一优化问题,因此,我们提议使用截断率作为更可移植的衡量标准,以优化MI,并采用两种优化方法使CR最大化。第一种方法是以预测梯度法(PGM)为基础,而第二种方法则取自连续的convex近似(SCA)原则。模拟结果表明,拟议的优化方法大大加强了CR和相应的MI。