Optical Intelligent Reflecting Surface-Aided VLP: Light Spot Coverage Scheduling and Geometry-Aware Localization

Visible light positioning (VLP) has emerged as a high-accuracy solution for indoor Internet of Things (IoT) applications. However, its performance degrades severely when line-of-sight (LOS) links are blocked. Although optical intelligent reflecting surface (OIRS) can alleviate this issue by reconstructing nonline-of-sight (NLOS) links, many existing studies usually model an OIRS element as an ideal point source, overlooking the geometric characteristics of the reflected light spots generated by finite-size OIRS and lack experiment verification. In this work, we propose a VLP system based on OIRS-reflected light spot coverage scheduling, which utilizes the geometric characteristics of OIRS. We develop an offline coverage scheduling strategy based on hierarchical particle swarm optimization (HPSO) to eliminate signal blind zones and enable each OIRS element to achieve full-domain geometric coverage with the minimum number of orientations independently. To solve the nonconvex and discontinuous received signal strength-based positioning problem caused by light spot boundaries, we propose a geometry-aware localization algorithm, namely light spot intersection area-guided Gaussian initialized elite differential black winged kite algorithm (SIGED-BKA). The proposed algorithm uses Gaussian initialization guided by light spot intersection regions to avoid invalid searches and an elite differential evolution mechanism to improve coordinate estimation accuracy. Simulation and experimental results show that, in the considered scenario, the proposed HPSO scheme allows the three OIRSs to realize 100% coverage with only six, seven, and six orientations, respectively, significantly outperforming the greedy baseline requiring 11 orientations. Based on this coverage design, SIGED-BKA achieves average positioning errors (APEs) of 1.87 cm in simulation and 4.60 cm in experiment, superior to the baseline algorithms, which verifies the effectiveness of the proposed system.