Hybrid 3D Localization for Visible Light Communication Systems

TL;DR

This paper presents a hybrid 3D localization method for visible light communication systems that combines AOA and RSS information, improving accuracy through analytical models, learning algorithms, and extensive simulations.

Contribution

It introduces a novel hybrid localization approach that integrates AOA and RSS data with advanced algorithms and analytical bounds for enhanced 3D positioning in VLC systems.

Findings

AOA-based localization with least squares is effective.

RSS information improves localization accuracy when considering LED radiation patterns.

The proposed methods outperform benchmarks in diverse scenarios.

Abstract

In this study, we investigate hybrid utilization of angle-of-arrival (AOA) and received signal strength (RSS) information in visible light communication (VLC) systems for 3D localization. We show that AOA-based localization method allows the receiver to locate itself via a least squares estimator by exploiting the directionality of light-emitting diodes (LEDs). We then prove that when the RSS information is taken into account, the positioning accuracy of AOA-based localization can be improved further using a weighted least squares solution. On the other hand, when the radiation patterns of LEDs are explicitly considered in the estimation, RSS-based localization yields highly accurate results. In order to deal with the system of nonlinear equations for RSS-based localization, we develop an analytical learning rule based on the Newton-Raphson method. The non-convex structure is addressed by initializing the learning rule based on 1) location estimates, and 2) a newly developed method, which we refer as random report and cluster algorithm. As a benchmark, we also derive analytical expression of the Cramer-Rao lower bound (CRLB) for RSS-based localization, which captures any deployment scenario positioning in 3D geometry. Finally, we demonstrate the effectiveness of the proposed solutions for a wide range of LED characteristics and orientations through extensive computer simulations.