Weighted Sum Rate Maximization for Muti-Antenna NOMA-UAV System

With the explosive growth of the number of mobile user devices, the next generation of wireless communication networks and the Internet of Things must provide large-scale access. The combination of multi-input multi-output non-orthogonal multiple access technology (MIMO) and UAV has become one of the current research hotspots. A large-scale multi-input multioutput non-orthogonal multiple access communication system model for UAV amplify-and-forward (AF) relay is constructed, and a joint beamforming and power optimization method is proposed. Considering imperfect successive interference cancellation (SIC) and UAV power consumption constraints, the intercluster interference is eliminated by simplifying the beamforming design, and the objective problem is transformed into a convex optimization problem by using successive convex approximation (SCA) to maximize the weighted sum rate under the constraint of service quality. Simulation results show that the performance of the proposed algorithm is obviously better than that of OMA at high SNR, which significantly improves the resource allocation efficiency and user fairness, and provides a new and effective scheme for UAV-enabled large-scale multiple access.