RIS-Enabled Self-Localization: Leveraging Controllable Reflections With Zero Access Points

TL;DR

This paper proposes a novel RIS-based method for user self-localization in wireless systems, enabling position estimation through reflected OFDM signals, with theoretical bounds and a practical low-complexity algorithm demonstrating high accuracy.

Contribution

It introduces a new RIS-enabled localization approach using controllable reflections and develops a low-complexity estimator that approaches theoretical bounds.

Findings

The proposed algorithm attains the Cramer-Rao lower bound at high SNR.

RIS phase profiles can be designed to separate reflected signals from multipath.

The method enables user self-localization without requiring access points.

Abstract

Reconfigurable intelligent surfaces (RISs) are one of the most promising technological enablers of the next (6th) generation of wireless systems. In this paper, we introduce a novel use-case of the RIS technology in radio localization, which is enabling the user to estimate its own position via transmitting orthogonal frequency-division multiplexing (OFDM) pilots and processing the signal reflected from the RIS. We demonstrate that user localization in this scenario is possible by deriving Cramer-Rao lower bounds on the positioning error and devising a low-complexity position estimation algorithm. We consider random and directional RIS phase profiles and apply a specific temporal coding to them, such that the reflected signal from the RIS can be separated from the uncontrolled multipath. Finally, we assess the performance of our position estimator for an example system and show that the proposed algorithm can attain the derived bound at high signal-to-noise ratio values.