The integration of unmanned aerial vehicles (UAVs), non-orthogonal multiple access (NOMA), and visible light communication (VLC) advances future communication technologies. Despite its potential to overcome spectrum limitations and extend coverage, challenges such as link attenuation and power allocation imbalances hinder performance. This study focuses on UAV-assisted NOMA-VLC systems and proposes dynamic UAV positioning to address limitations of fixed-light-source deployments. A dual marine predator algorithm (DMPA) for power allocation optimisation is introduced, featuring dual-predator reinforcement search, adaptive acceleration factors for improved convergence, and dynamic thresholds based on rate standard deviation and Jain fairness index. Experimental results show that the DMPA outperforms competing schemes in both ideal and obstructed environments. Dynamic UAV positioning enhances signal coverage and system robustness, particularly in obstacle-rich environments.
Liu et al. (2026) studied this question.