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Enhanced optical visible light positioning via RSS-based evolutionary optimization under LOS and NLOS conditions.
Pankaj Pathak1, S Sharavanan2, M Karthikeyan3
1Symbiosis Institute of Digital and Telecom Management (SIDTM), Symbiosis International (Deemed University), Pune, India. pankajpathak@sidtm.edu.in.
Scientific Reports
|November 26, 2025
Summary
This study enhances visible light positioning accuracy by using genetic and particle swarm optimization algorithms to minimize errors. Results show these methods significantly reduce positioning inaccuracies compared to traditional techniques.
Area of Science:
- Optical communication
- Wireless positioning systems
- Indoor navigation
Background:
- Visible light positioning (VLP) offers a low-cost, safe alternative to RF-based positioning.
- Existing VLP methods using Received Signal Strength (RSS) algorithms suffer significant errors due to noise and multipath effects.
- Linear approximation in RSS-based VLP introduces further inaccuracies.
Purpose of the Study:
- To investigate and reduce positioning errors in VLP systems.
- To compare the effectiveness of evolutionary algorithms against traditional least squares estimation for error minimization.
- To analyze the impact of various parameters on VLP accuracy.
Main Methods:
- Utilized the Received Signal Strength (RSS) algorithm for locating within a simulated 6x6x4 m³ room.
- Implemented genetic algorithm (GA) and particle swarm optimization (PSO) to minimize positioning error functions.
- Simulated scenarios including Line-of-Sight (LOS) and Non-Line-of-Sight (NLOS) conditions, and analyzed effects of LED distance, transmitted power, receiver height, and reflections.
Main Results:
- GA and PSO significantly reduced positioning errors compared to least squares estimation.
- Increased transmitted power and number of transmitters decreased positioning error.
- Higher receiver height and presence of reflections increased positioning error.
- Achieved Root Mean Square Errors (RMSE) of 0.3493 m (LOS) and 0.4461 m (NLOS).
Conclusions:
- Evolutionary algorithms like GA and PSO are effective in enhancing VLP accuracy.
- Optimizing LED placement, transmitted power, and minimizing reflections are crucial for improving VLP performance.
- A method for selecting high-power LEDs was proposed to further reduce positioning errors.
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