Reconfigurable Intelligent Surface Aided Integrated Communication and Localization with a Single Access Point

TL;DR

The paper addresses the challenge of indoor UE localization using a single AP by leveraging multiple RISs to create additional reference points. It proposes a two-stage channel estimation framework: stage 1 applies NOMP to extract multi-path components and identify LOS and RIS paths, while stage 2 uses a pseudo-spectrum approach to estimate AOAs at RISs, followed by a linear LS localization using AOAs from the AP and RISs. Key contributions include achieving centimeter-level localization accuracy, characterizing how accuracy scales with transmit power, RIS element count, channel soundings, and reference-point diversity, and showing practical RIS-based ISAC benefits. The findings underscore the practical impact of RISs as reference points that enable accurate indoor localization with a single AP and minimal training data, while also supporting potential enhancements in ISAC-like systems through joint sensing and communication design.

Abstract

Reconfigurable intelligent surfaces (RISs) not only assist communication but also help the localization of user equipment (UE). This study focuses on the indoor localization of UE with a single access point (AP) aided by multiple RISs. First, we propose a two-stage channel estimation scheme where the phase shifts of RIS elements are tuned to obtain multiple channel soundings. In the first stage, the newtonized orthogonal matching pursuit algorithm extracts the parameters of multiple paths from the received signals. Then, the LOS path and RIS-reflected paths are identified. In the second stage, the estimated path gains of RIS-reflected paths with different phase shifts are utilized to determine the angle of arrival (AOA) at the RIS by obtaining the angular pseudo spectrum. Consequently, by taking the AP and RISs as reference points, the linear least squares estimator can locate UE with the estimated AOAs. Simulation results show that the proposed algorithm can realize centimeter-level localization accuracy in the discussed scenarios. Moreover, the higher accuracy of pseudo spectrum, a larger number of channel soundings, and a larger number of reference points can realize higher localization accuracy of UE.

Figures (7)

• Figure 1: Illustration of the RIS-aided indoor communication systems.
• Figure 2: Illustration of the four different types of paths introduced in Sec. \ref{['sec:system-model']}.
• Figure 4: Pseudo spectrum with different transmit power $P$, where the units of $\phi$ and $\theta$ are in rad, the red point represents the peak value of the pseudo spectrum, and the black point represents the true location of AOA at RIS 1.
• Figure 5: RMSEs of the locations and angles with different transmit power.
• Figure 6: RMSEs of the locations and angles with different numbers of RIS elements, and the comparison with liu2021cascaded.