Abstract: An optimization scheme is proposed to ensure QoS guarantee in UAV-assisted multi-cluster NOMA downlink networks with limited resources.In this paper,the UAV serves as an airborne mobile base station to communicate with ground users.Due to limited energy,hovering time is introduced as an optimization variable to allocate more energy for communication.The total throughput is maximized by optimizing user clustering,intra-cluster power allocation,and communication time allocation.Due to its non-convexity,the optimization problem is divided into three sub-problems.The power allocation problem is addressed using the SCA method,and the communication time allocation is solved via linear programming.First of all,the Mean Shift algorithm is employed for user clustering.Unlike K-means,it clusters users by calculating local density peaks,ensuring higher intra-cluster user concentration.Then,an improved Mean Shift algorithm is proposed to balance user distribution by splitting oversized clusters,thereby ensuring individual user QoS.Finally,an original cluster head hovering scheme is introduced to avoid increasing the UAV’s flight distance due to additional sub-clusters,then GA is used for trajectory optimization,enhancing total throughput by reducing the UAV’s non-communication energy consumption while ensuring user QoS.The optimization scheme has low computational complexity and strong real-time performance.Simulation results show that the optimization scheme with an improved Mean Shift algorithm reduces the non-communication energy consumption than the K-means algorithm,and improves the system throughput by an average of 5.94% at different transmit power and energy efficiency by an average of 6.82% at different number of users.

Key words: Unmanned Aerial Vehicle, Non-orthogonal multiple access, Quality of service, Energy-efficient, Trajectory optimization