Reconfigurable intelligent surface (RIS) devices have emerged as an effective way to control the propagation channels for enhancing the end users' performance. However, RIS optimization involves configuring the radio frequency (RF) response of a large number of radiating elements, which is challenging in real-world applications due to high computational complexity. In this paper, a model-free cross-entropy (CE) algorithm is proposed to optimize the binary RIS configuration for improving the signal-to-noise ratio (SNR) at the receiver. One key advantage of the proposed method is that it only needs system performance parameters, e.g., the received SNR, without the need for channel models or channel estimation. Both simulations and experiments are conducted to evaluate the performance of the proposed CE algorithm. The results demonstrate that the CE algorithm outperforms benchmark algorithms, and shows stronger channel hardening with increasing numbers of RIS elements.

翻译：重新配置智能表面(RIS)装置已成为控制传播渠道以提高终端用户性能的有效途径,然而,RIS优化涉及对大量辐射元素的无线电频率反应进行配置,由于计算复杂程度高,这在现实世界应用中具有挑战性。在本文中,提议采用无模型的跨渗透性(CE)算法,优化接收器的二进制RIS配置,以改善接收器的信号对噪音比率。拟议方法的一个主要优点是,它只需要系统性能参数,例如接收的SRR,而不需要频道模型或频道估计。进行模拟和实验,以评价拟议的CE算法的性能。结果显示,CE算法优于基准算法,并显示通过不断增加的RIS元素使频道更加坚硬。