Single Antenna Tracking and Localization of RIS-enabled Vehicular Users

TL;DR

This work tackles the problem of tracking and localizing multiple RIS-equipped vehicular users with a single-antenna transmitter and several single-antenna receivers. It introduces a phase-shift design to isolate signals through each RIS, estimates ToA, Doppler, and geometry-based parameters, and formulates a localization LS problem to recover RIS positions; it further employs an EKF to track RIS trajectories over time. A comprehensive CRLB analysis is provided for RIS position and ToA/geometry parameters, and simulations show that the RIS-based approach can reduce localization error by up to a factor of three compared to ToA-only methods, while tracking demonstrates robustness and improved accuracy with increased bandwidth, subcarriers, and power. The results highlight the practical benefits of RIS-enabled sensing in vehicular networks, offering improved localization and tracking performance with feasible computational schemes.

Abstract

Reconfigurable Intelligent Surfaces (RISs) are envisioned to be employed in next generation wireless networks to enhance the communication and radio localization services. In this paper, we propose novel localization and tracking algorithms exploiting reflections through RISs at multiple receivers. We utilize a single antenna transmitter (Tx) and multiple single antenna receivers (Rxs) to estimate the position and the velocity of users (e.g. vehicles) equipped with RISs. Then, we design the RIS phase shifts to separate the signals from different users. The proposed algorithms exploit the geometry information of the signal at the RISs to localize and track the users. We also conduct a comprehensive analysis of the Cramer-Rao lower bound (CRLB) of the localization system. Compared to the time of arrival (ToA)-based localization approach, the proposed method reduces the localization error by a factor up to three. Also, the simulation results show the accuracy of the proposed tracking approach.

Figures (11)

• Figure 1: A capture of the considered scenario, as $N_{\mathrm{r}}=3$, $K=2$ and $L=2$.
• Figure 2: Representation of locations and AoA and AoD in a scenario including the Tx, the $n^{\mathrm{th}}$Rx, and the $k^{\mathrm{th}}$RIS.
• Figure 3: The localization error of the proposed approach for different number of Rx in terms of (a): Subcarrier bandwidth. (b): Number of subcarriers. (c): Total transmit power ($N E_s$). The RIS location is $[7, 7]$.
• Figure 4: The localization error of the proposed approach in terms of (a): $N_T$ (b): $T$. The RIS location is $[7, 7]$.
• Figure 5: The localization error in terms of (a): Subcarrier bandwidth. (b): Number of subcarriers. (c): Total transmit power ($N E_s$). The RIS location is $[7, 7]$.