Abstract
In this article, we study the uplink transmission scheme and channel estimation design for reconfigurable intelligent surfaces (RIS)-aided orthogonal time-frequency space (OTFS) systems in high-mobility scenarios. To this end, we first propose an efficient and reliable transmission scheme that utilizes the delay-Doppler (DD) 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 channel parameters, 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 linear systems and the mapping relationship of the DD pairs, respectively. With the DD information in hand, a user localization algorithm constructed by the least square (LS) and a channel tracking method relying on extended Kalman filter (EKF) are then presented to 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 under high Doppler channels.
Original language | English |
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Pages (from-to) | 19518-19532 |
Number of pages | 15 |
Journal | IEEE Internet of Things Journal |
Volume | 10 |
Issue number | 22 |
Early online date | 25 Apr 2023 |
DOIs | |
Publication status | Published - 15 Nov 2023 |
Externally published | Yes |
Bibliographical note
This work was supported in part by the National Natural Science Foundation of China under Grant 62101232 and Grant 62201242; in part by the Guangdong Provincial Natural Science Foundation under Grant 2022A1515011257; in part by the Shenzhen Science and Technology Program under Grant JCYJ20220530114412029; and in part by the Special Funds for the Cultivation of Guangdong College Students’ Scientific and Technological Innovation (“Climbing Program” Special Funds) under Grant PDJH2022C0026.Keywords
- Channel estimation
- orthogonal time-frequency space (OTFS)
- passive beamforming
- reconfigurable intelligent surfaces (RIS)