Fingerprint-Based Indoor Localization via RIS-Enabled over-the-Air Modulation

Abstract

Accurate and cost-effective indoor localization re-mains a critical challenge for smart environments. Traditional fingerprint-based methods require measurements from multiple access points (APs), which increases deployment costs and system complexity. Reconfigurable intelligent surfaces (RISs) have recently been explored to enrich the spatial diversity of fingerprint data, allowing localization with fewer APs. However, many existing RIS-aided approaches rely on RIS phase shift optimization, limiting their practicality. In this paper, we propose a novel RIS-assisted fingerprint localization method that eliminates the need for multiple APs and RIS phase shift optimization. In the proposed method, multiple RISs reflect the unmodulated signal transmitted by a radio frequency (RF) source using their unique phase shift reflection patterns (PSRPs). These modulated reflections allow the user equipment (UE) to extract fingerprint features by correlating the received signal with the known PSRPs of the RISs. Computer simulation results demonstrate that the proposed method achieves submeter-level accuracy under moderate transmit power conditions.