  In this paper, we propose a novel computer vision-based approach to aid
Reconfigurable Intelligent Surface (RIS) for dynamic beam tracking and then
implement the corresponding prototype verification system. A camera is attached
at the RIS to obtain the visual information about the surrounding environment,
with which RIS identifies the desired reflected beam direction and then adjusts
the reflection coefficients according to the pre-designed codebook. Compared to
the conventional approaches that utilize channel estimation or beam sweeping to
obtain the reflection coefficients, the proposed one not only saves beam
training overhead but also eliminates the requirement for extra feedback links.
We build a 20-by-20 RIS running at 5.4 GHz and develop a high-speed control
board to ensure the real-time refresh of the reflection coefficients. Meanwhile
we implement an independent peer-to-peer communication system to simulate the
communication between the base station and the user equipment. The vision-aided
RIS prototype system is tested in two mobile scenarios: RIS works in near-field
conditions as a passive array antenna of the base station; RIS works in
far-field conditions to assist the communication between the base station and
the user equipment. The experimental results show that RIS can quickly adjust
the reflection coefficients for dynamic beam tracking with the help of visual
information.
