RIS-Assisted Smart Radio Environment for Enhanced Non-Orthogonal Multiplexing Indoor Positioning System

Indoor Positioning Systems (IPS) based on Received Signal Strength (RSS) often face challenges in achieving high accuracy due to spatial and temporal uncertainties in complex indoor environments. To address these limitations, this paper proposes a novel Static Reconfiguration Algorithm (SRA) leveraging Reconfigurable Intelligent Surface (RIS) technology to optimize RSS distributions. Unlike traditional methods, the SRA eliminates the need for dynamic RIS reconfiguration, instead employing a static approach that maximizes differentiation between RSS values at predefined Reference Points (RPs). This enhances localization precision by reducing spatial correlation and improving distinguishability, even in noisy environments. Simulation results demonstrate that the SRA significantly outperforms conventional RSS-based approaches, achieving positioning errors as low as 75 cm in high-noise scenarios compared to 150 cm with traditional methods. Furthermore, the algorithm proves effective across broader RSS measurement ranges (-100 to 0 dB) and achieves superior performance even with a single Access Point (AP). The multidimensional SRA approach further enhances accuracy by leveraging diverse RSS distributions through additional APs and time-division multiplexing. These results underscore the robustness, scalability, and efficiency of the SRA, positioning it as a transformative solution for next-generation IPS in smart environments.