IRS-Assisted Secrecy Rate Maximization for Visible Light Communication Based on Improved Particle Swarm Optimization Algorithm

Intelligent reflective surfaces (IRS), as an emerging channel tuning technique, have been widely used in visible light communication(VLC) systems. We look at how to adjust the correspondence between the IRS and the transceiver so that the communication system maximizes the secrecy rate while satisfying the basic communication rate as well as the energy harvesting requirements. To address this assignment problem, a gain particle swarm optimization (GPSO) algorithm that leverages channel gain was proposed, which improves the particle velocity and position updating formula by introducing amplified gain. The experimental results indicate that improved GPSO algorithm compared to the PSO algorithm improves the rate by 8Mbit/s under the constraints and the energy harvesting by 5mJ, at the same time, we can see that the GPSO algorithm also has a performance advantage over the SCA and DE algorithms, these results show that GPSO algorithm can be well applied to this kind of allocation problem.