Trajectory optimization for maximization of energy efficiency with dynamic cluster and wireless power for UAV-assisted maritime communication

Nowadays, the digital development of marine ranching requires a communication system with wide coverage, high transmission rate and stable communication links. It is known that fixed-wing unmanned aerial vehicles (UAVs) have great advantages in long-range applications. They have the potential to serve as low-altitude communication platforms for maritime communication. In this study, with a developmental perspective, considering the intense growth of marine terminals in the future, a new clustering algorithm applied to cluster nonorthogonal multiple access (C-NOMA) is proposed and its advantages are investigated. In addition, considering the limited energy of marine terminals, combining the wireless power communication (WPC) technology for the UAV to charge terminals, the charging and communication time are optimized with the Lagrange multiplier method and the bisection search method. After completing the above optimization content of charging and communication, combined with the optimization results, it is found the trajectory that maximizes the energy efficiency of the UAV with the convex optimization technique. Experimental results show that the proposed clustering algorithm has good throughput performance, better fairness and lower algorithm complexity, and the proposed trajectory optimization scheme has better energy efficiency. This paper targets on maximizing the energy efficiency in a UAV-assisted maritime communication system, where the UAV charges terminals in the downlink phase by wireless powering and the terminals employs the harvested energy to transmit information in a clustering NOMA method. The time length for downlink and uplink phases, the transmit power, and the trajectory are jointly optimized to improve the energy efficiency. image