Abstract

Visible-light communication (VLC) is a promising method for indoor positioning. The received signal strength algorithm is the most widely used localization algorithm in visible-light positioning (VLP) systems. However, in a VLP system, the photodiode (PD) will have a small rotation angle during movement, which will result in a massive positioning error ignoring the angle. In this study, a three-dimensional (3D) indoor VLP system using an improved whale optimization algorithm (IWOA) is proposed to reduce the error caused by the PD rotation. Firstly, the model of the VLC system with the PD rotation angles is introduced. Secondly, a novel IWOA with an elite opposition-based learning strategy and Lévy flight strategy is proposed. The convergence speed and accuracy of the WOA are improved. Lastly, the IWOA algorithm is efficiently utilized to address the problem with the PD rotation in the indoor VLP system. Simulation results show that the average error of 3D positioning is 2.14 cm with no PD rotation. When the PD has a rotation angle, the average positioning error estimated by ignoring the rotation angle is 27.14 cm, while that estimated by considering the rotation angle is 7.85 cm. In the VLP system, the positioning error with the PD rotation angle is effectively reduced by the proposed algorithm, which can be applied in a variety of indoor location scenes.

Highlights

  • Many technologies are applied to indoor positioning, with typical systems based on a global positioning system (GPS), radiofrequency identification (RFID), wireless local area network (WLAN), ultrawide-band radio (UWB), and visible-light communication (VLC)

  • To solve the PD random-rotation problem, this paper proposes a 3D indoor location system based on visible-light communication using an improved whale optimization algorithm (IWOA)

  • The results show that the IWOA, which took PD rotation angle estimation into account, could significantly improve 3D positioning accuracy

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Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Xu et al presented an indoor 3D visible-light location system using adaptive parameter particle swarm optimization, and the system achieved similar positioning results with a smaller swarm [19]. Chen et al proposed an indoor VLP system based on an improved hybrid bat algorithm, and the system achieved an average positioning error of 1.16 cm in a space of 5 m × 5 m × 3 m [20]. Chen et al proposed an indoor 3D VLC system based on an improved immune particle swarm optimization algorithm, which considered the influence of environmental interference, and an average positioning error of 3.12 cm was achieved [21]. To solve the PD random-rotation problem, this paper proposes a 3D indoor location system based on visible-light communication using an improved whale optimization algorithm (IWOA).

VLC System Model
VLC SystemH
Whale Optimization Algorithm
Improved Whale Optimization Algorithm
Elite Opposition-Based Learning
Lévy Flight
Simulation Results and Analysis
Single-Point
Multipoint
Conclusions

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