Flight to Efficiency: Trajectory Optimization in SWIPT-Enabled UAV-Assisted NOMA for Future Wireless Networks

Integration of simultaneous wireless information and power transfer (SWIPT) enabled non-orthogonal multiple access (NOMA) in an unmanned aerial vehicle (UAV) is a novel variant that benefits enhanced spectrum efficiency and energy efficiency. Despite these potential advantages, resource allocations and UAV trajectory optimizations pose major challenges to its realization. Thus, in this work, we optimize the UAV’s trajectory including its positioning, in up-link, and down-link NOMA-enabled UAV-assisted communication network while maximizing achievable rates at the ground users. To further enhance energy efficiency, the UAV is equipped with SWIPT to harvest energy from the received signals. The proposed solution utilizes the particle swarm optimization (PSO) tool to optimize the UAV’s position to maximize the minimum achievable rate while maximizing SWIPT-based energy harvesting. Simulation results demonstrate the improved minimum achievable rate of the proposed solution making the proposed communication model effective over conventional UAV communications.