Energy Minimization for Data Collection in UAV-Assisted WSNs with All-User Uplink Single-Carrier NOMA

In this paper, we study the optimization of energy consumption for data collection in UAV-assisted wireless sensor networks (WSNs) under the uplink single-carrier non-orthogonal multiple access (NOMA) approach. The total energy consumption of ground users is minimized by jointly optimizing the single UAV trajectory, sensor power allocation and updating access order while ensuring the completion of the data transmission task. This is a mixed integer nonlinear programming problem (MINLP) that is difficult to solve, for this reason we propose an iterative algorithm to solve the resulting optimization problem by using the block coordinate descent (BCD) method. First, for a given UAV trajectory, the sensor access order is determined according to the channel quality; second, we use the successive convex approximation (SCA) method to optimize the two subproblems of sensor transmit power and UAV trajectory, respectively; then the access order is updated according to the optimized UAV trajectory and the energy consumption minimum is obtained by iterative optimization. Simulation results show the effectiveness of the proposed algorithm.