A reconfigurable intelligent surface (RIS) is a prospective wireless technology that enhances wireless channel quality. An RIS is often equipped with passive array of elements and provides cost and power-efficient solutions for coverage extension of wireless communication systems. Without any radio frequency (RF) chains or computing resources, however, the RIS requires control information to be sent to it from an external unit, e.g., a base station (BS). The control information can be delivered by wired or wireless channels, and the BS must be aware of the RIS and the RIS-related channel conditions in order to effectively configure its behavior. Recent works have introduced hybrid RIS structures possessing a few active elements that can sense and digitally process received data. Here, we propose the operation of an entirely autonomous RIS that operates without a control link between the RIS and BS. Using a few sensing elements, the autonomous RIS employs a deep Q network (DQN) based on reinforcement learning in order to enhance the sum rate of the network. Our results illustrate the potential of deploying autonomous RISs in wireless networks with essentially no network overhead.

翻译：可重构智能表面（RIS）是一种具有前景的无线技术，能够提升无线信道质量。RIS通常配备无源天线阵列，为无线通信系统的覆盖扩展提供成本效益高且能效优的解决方案。然而，由于缺乏射频链路或计算资源，RIS需要从外部单元（如基站）接收控制信息。控制信息可通过有线或无线信道传输，且基站必须掌握RIS及其相关信道状态，方能有效配置其行为。近期研究提出了混合RIS结构，该结构包含少量可感知并数字化处理接收数据的有源单元。本文提出一种完全自主的RIS运行方案，无需RIS与基站之间的控制链路。该自主RIS利用少量感知单元，采用基于强化学习的深度Q网络（DQN）以提升网络总速率。研究结果表明，在无线网络中部署自主RIS具有巨大潜力，且几乎不产生网络开销。