A Quantum-Crossover Gravitational Search Algorithm for Energy-Efficient Power Allocation in Serial Relaying Underwater Wireless Optical Communication Systems

Underwater wireless optical communication systems face several challenges, such as path loss, poor signal quality, and limited communication range because of environmental constraints like scattering, turbidity, and attenuation. To address these challenges, this study proposes a serial relaying underwater wireless optical communication system enhanced by a hybrid optimization algorithm called quantum-based crossover gravitational search algorithm. This algorithm incorporates a gravitational search algorithm with a quantum crossover mechanism to optimize power allocation among relay nodes for increasing energy efficiency and reducing signal-to-noise ratio under various environmental constraints. This study adopts a gravitational search algorithm for resolving the power allocation problem that utilizes the concept of gravitational attraction among agents to explore the search space. However, it often suffers from slow convergence and local optima trapping. To resolve this, the proposed technique deploys a quantum crossover mechanism to refine this process by improving solution diversity and convergence speed. By combining the significance of these approaches, the proposed quantum-based crossover gravitational search algorithm effectively solves complex optimization issues and enhances energy efficiency by distributing power optimally and reducing excessive energy consumption. Simulation results demonstrate that Q-CROSS GSA outperforms existing optimization methods in terms of energy efficiency, signal-to-noise ratio, and outage probability, offering a robust approach for an efficient UWOC system in challenging underwater environments.