Accurate visible light positioning through power adaptation of led arrays

Abstract

In this thesis, we develop power allocation strategies for asynchronous visible light positioning (VLP) systems employing light-emitting diode (LED) arrays with the aim of improving localization accuracy. We first review the literature on visible light positioning in indoor scenarios. Then, we formulate an optimization problem for minimizing the Cramér-Rao lower bound (CRLB) related to the estimation of the receiver location subject to practical constraints on total and individual transmission powers and required illumination levels. Due to the nonconvexity of the proposed formulation, we devise a two-step methodology. First, a convex optimization problem is employed to determine the power allocation that maximizes the total received power. Subsequently, a projected gradient descent algorithm is utilized to refine the power allocation according to the CRLB metric under the power and illumination constraints. In addition, a framework for iterative power allocation and localization is developed for practical deployment, in which each step of the optimization process uses the most recent position estimate. Simulation results indicate that the proposed method can outperform both the uniform and power maximization based allocation schemes, resulting in improved localization accuracy over a wide range of operating conditions. Hence, it can provide robust and high-precision indoor positioning, even in circumstances involving asynchronous transmission and stringent illumination requirements.