Joint RIS Calibration and Multi-User Positioning

TL;DR

This paper introduces a joint RIS calibration and multi-user positioning scheme that accounts for RIS state uncertainty, deriving bounds and analyzing performance impacts in single and multi-user scenarios for 6G wireless networks.

Contribution

It formulates the JrCUP problem considering RIS state uncertainty, deriving analytical bounds and analyzing the impact of user location and RIS size on performance.

Findings

Derived the Fisher information-based lower bounds for user and RIS states.

Showed the geometric impact of user locations on JrCUP performance.

Extended analysis to multi-user scenarios, demonstrating improved state estimation.

Abstract

Reconfigurable intelligent surfaces (RISs) are expected to be a key component enabling the mobile network evolution towards a flexible and intelligent 6G wireless platform. In most of the research works so far, RIS has been treated as a passive base station (BS) with a known state, in terms of its location and orientation, to boost the communication and/or terminal positioning performance. However, such performance gains cannot be guaranteed anymore when the RIS state is not perfectly known. In this paper, by taking the RIS state uncertainty into account, we formulate and study the performance of a joint RIS calibration and user positioning (JrCUP) scheme. From the Fisher information perspective, we formulate the JrCUP problem in a network-centric single-input multiple-output (SIMO) scenario with a single BS, and derive the analytical lower bound for the states of both user and RIS. We also demonstrate the geometric impact of different user locations on the JrCUP performance while also characterizing the performance under different RIS sizes. Finally, the study is extended to a multi-user scenario, shown to further improve the state estimation performance.