LEDs placement in indoor VLC system based on an improved marine predator algorithm

Visible Light Communication (VLC) is a promising and emerging technology that allows both illumination and communication between users using Light Emitting Diodes (LEDs) as transmitters and Photo-Detectors (PDs) as receivers. In indoor VLC systems, the deployment of various number of LEDs with various number of users is a challenging issue. This issue is considered to be an NP-Hard problem, so approximation approaches, especially meta-heuristics, are appropriate to solve it. In this paper, we propose a hybrid swarm intelligence approach (IMPA-FA) based on the combination of the Improved Marine Predators Algorithm (IMPA) with Firefly Algorithm (FA) for solving the LEDs placement problem in an indoor VLC system. The effectiveness of the proposed IMPA-FA is tested on several scenarios under different settings, taking into account the throughput and user coverage metrics. Simulation results demonstrate the accuracy and superiority of the IMPA-FA approach in finding optimal LEDs positions when compared with the standard MPA, FA, Particle Swarm Optimization (PSO), Genetic algorithm (GA), Coronavirus Herd Immunity Optimizer (CHIO), Whale Optimization Algorithm (WOA), Manta Ray Foraging Optimization (MRFO), Bat algorithm (BAT), and Grey Wolf Optimizer (GWO).