Joint Placement and Power Allocation Optimization for Sum Rate Maximization in NOMA-based UAV Networks

Unmanned aerial vehicle (UAV) network based on non-orthogonal multiple access (NOMA) jointly optimizes the location and power allocation (PA) of UAV to achieve better sum rate. However, this non-convex sum rate maximization problem is difficult to solve. Therefore, we decompose this non-convex problem into two sub-problems. First, genetic algorithm (GA) is used to solve the position optimization problem, which is equivalent to sum rate maximization problem. Then, the closed-form PA algorithm is used to further maximize the sum rate under a fixed UAV’s location obtained by GA. Compared with PA algorithm with geometric center placement, numerical results demonstrate the effectiveness of the proposed algorithm.