RIS-Aided OTFS: A Novel ISAC Scheme for Achieving Real-Time Communication and Sensing

In this paper, we study uplink transmission for reconfigurable intelligent surfaces (RIS)-aided orthogonal time frequency space (OTFS) systems to achieve real-time communications and sensing in high-mobility scenarios, which is the urgent requirement for various future networks like Internet of Things (IoT) and Metaverse. To this end, we first propose an efficient and reliable transmission scheme which utilizes the delay-Doppler information in OTFS to facilitate the configuration of RIS. Specifically, the proposed scheme exploits the estimated delay and Doppler shifts of the cascaded channel to sense the user, and the sensing parameters are then used for RIS passive beamforming. It is noteworthy that we estimate the channel state information (CSI) by employing only one OTFS frame and configure the RIS based on the predicted channel parameters, leading to substantially reduced channel training overhead and more real-time RIS configuration. To obtain the essential information for channel information sensing, we then propose a low-complexity algorithm which determines the Doppler and delay shifts of the channel between the user and RIS based on the mapping relationship of the delay-Doppler pairs. With the delay-Doppler information in hand, a user tracking scheme relying on extended Kalman filter (EKF) are then presented to track the user and obtain the spatial angle information. By making use of the channel parameters acquired at the base station (BS), the RIS reflection vector is designed to maximize the achievable rate. The results obtained from the simulation experiments affirm the efficacy of the proposed scheme, thereby confirming its capability to attain efficient communications and sensing under high Doppler channels.