LAUSR

In this paper, we are interested in the joint estimate of user equipment (UE) position and orientation for visible light communication (VLC) with uncertain emission power. This joint estimation is a non-convex problem with a huge search space. To address this challenge, a novel VLC localization algorithm is proposed, which converges to the stationary solution of the joint estimation problem at an asymptotic quadratic convergence rate due to our problem-specific surrogate function design. A closed-form update rule is obtained via exploiting the hidden convex structure of the non-convex optimization problem. Hence, our algorithm has low complexity compared with the particle swarm-based optimization methods. In addition, the closed-form Cramer-Rao lower bounds (CRLBs) on the estimation errors of the respective UE location, orientation and LED emitting power are derived. Moreover, the effect of critical parameters such as signal-to-noise ratio (SNR), the number of LED transmitters, transmission distance and non-line-of-sight propagation on the VLC localization performance are revealed. The simulation result verifies that the proposed VLC localization algorithm under unknown VLC emitting power can achieve a huge performance gain over the state-of-the-art localization baselines.