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 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 requires system performance indicators, e.g., the received SNR, without the need for channel models or channel state information. Both simulations and experiments are conducted to evaluate the performance of the proposed CE algorithm. This study provides an experimental demonstration of the channel hardening effect in a multi-antenna RIS-assisted wireless system under rich multipath fading.

翻译：可重构智能表面（RIS）设备已成为控制传播信道以提升用户性能的有效手段。然而，RIS优化需配置大量辐射单元的射频响应，在实际应用中因计算复杂度高而极具挑战性。本文提出一种无模型交叉熵（CE）算法，通过优化二进制RIS配置以提升接收端信噪比（SNR）。该方法的关键优势在于仅需系统性能指标（如接收信噪比），无需信道模型或信道状态信息。通过仿真与实验对CE算法性能进行了评估。本研究实验验证了多天线RIS辅助无线系统在丰富多径衰落环境下的信道硬化效应。