Reconfigurable Intelligent Surfaces: A Joint Localization and Communication Perspective

Joint localization and communication services have received growing interest for the next 6G cellular scenarios. Therefore, this paper studies a multi-Reconfigurable Intelligent Surface (RIS) single-user Multiple Input Multiple Output (MIMO) scenario from a dual perspective. From one side, we analyze the capabilities of an Extended Kalman Filter (EKF) to track the trajectory of the user by processing the positioning information gathered by the signals backscattered from the RISs, whereas the RISs are in turn optimized accounting for the outcomes of the EKF estimator. On the other side, we analyze the impact of positioning onto the communication performance in terms of achievable rate. Numerical results have shown that it is possible to track moving nodes with high accuracy leveraging on, solely, the radio signal reflected by the RISs in the absence of a line-of-sight (LOS) path between the transmitter and the receiver ensuring, at the same time, good communications performance.