LAUSR

The use of unmanned aerial vehicles (UAV) as aerial communication platforms has gained significant attention due to their favorable air-to-ground channels, on-demand deployment, and highly controllable mobility. In this paper, we aim at developing an efficient algorithm for the joint transmit power and UAV trajectory design via maximizing the minimum average throughput in a UAV-enabled network. The conventional method to tackle this problem is to optimize transmit power or trajectory in an alternative manner, which generally incurs high computational complexities. Moreover, how to find a favorable initial point is a challenging task. To this end, we impose a novel constraint by assuming that the UAV will not communicate until it approaches the closest position to a user, thus transforming the initial problem into an approximate one with reduced variables. Based on this result, we further propose two low-complexity algorithms by exploiting the alternating directional method of multipliers (ADMM), whose updating step is performed in closed-form solutions. In the first algorithm, both UAV trajectory and transmit power are determined simultaneously. We also propose a second algorithm which iteratively optimizes transmit power and trajectory. The simulation results show that by using the proposed ADMM-based algorithms, one can achieve higher performance than state-of-the-art methods with reduced computation time.