User Localization, Tracking and Environment Sensing for RIS-Aided mmWave MIMO-OFDM Systems: Location Serves Communication

Reconfigurable intelligent surface (RIS) is envisioned as a promising technology to enhance communication and sensing performance. In this paper, we study a user localization, tracking and environment sensing problem in the RIS-enabled millimeter-wave (mmWave) multiple-input multipleoutput (MIMO) orthogonal frequency division multiplexing (OFDM) downlink system. Meanwhile, we utilize the estimated location information to realize that location serves communication. Towards this end, we propose a novel frame structure to locate/track the user and scatterers, while implementing the joint beamforming design. Firstly, we propose a two-step localization scheme to determine the initial locations of user and scatterers. Then, we harness the extended Kalman filter (EKF) algorithm to perform the user and scatterer tracking. Next, we jointly optimize the transmit and reflective beamforming to maximize the average achievable rate of the user within the next time slot. Numerical simulations show that the proposed scheme achieves centimeterlevel localization and tracking accuracy, while improving the communication performance.