Integrated Imaging and Communication with Reconfigurable Intelligent Surfaces


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Reconfigurable intelligent surfaces, with their large number of antennas, offer an interesting opportunity for high spatial-resolution imaging. In this paper, we propose a novel RIS-aided integrated imaging and communication system that can reduce the RIS beam training overhead for communication by leveraging the imaging of the surrounding environment. In particular, using the RIS as a wireless imaging device, our system constructs the scene depth map of the environment, including the mobile user. Then, we develop a user detection algorithm that subtracts the background and extracts the mobile user attributes from the depth map. These attributes are then utilized to design the RIS interaction vector and the beam selection strategy with low overhead. Simulation results show that the proposed approach can achieve comparable beamforming gain to the optimal/exhaustive beam selection solution while requiring 1000 times less beam training overhead.
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Key words
Integral Image,Reconfigurable Intelligent Surface,Imaging System,Communication Systems,Depth Map,Low Overhead,Integrated Communication,Beamforming Gain,Background Subtraction,Analog-to-digital Converter,Exhaustive Search,Azimuth Angle,Access Points,Ground Plane,Depth Estimation,Vertical Dimension,Pixel Coordinates,Zenith Angle,Horizontal Dimension,User Equipment,Channel Path,Reconfigurable Intelligent Surface Elements,Chirp Signal,Target Path,Array Response Vector
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