Due to the mobility and line-of-sight conditions, unmanned aerial vehicle (UAV) is deemed as a promising solution to sensor data collection. On the other hand, it is vital to guarantee the timeliness of information for UAV-assisted data collection. In this paper, we propose a time-efficient data collection scheme, in which multiple ground devices upload their data to the UAV via uplink non-orthogonal multiple access (NOMA). The total flight time of the UAV is equally divided into NN time slots. The duration of each time slot is minimized by jointly optimizing the straight-line trajectory, device scheduling, and transmit power. To solve this mixed integer non-convex optimization problem, we decompose it into two steps. In the first step, we study the device scheduling strategy based on the UAV trajectory and the channel gains between the UAV and ground devices, through which the original problem can be greatly simplified. In the second step, the duration of each time slot is minimized by optimizing the transmit power and the UAV trajectory. An iterative algorithm based on alternating optimization is proposed, where each subproblem can be alternatively solved by applying successive convex approximation with the device scheduling updated at the end of each iteration. Numerical results are presented to evaluate the effectiveness of the proposed scheme.

中文翻译：

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通过上行链路 NOMA 进行无人机辅助的高效数据收集


由于移动性和视距条件，无人机（UAV）被认为是传感器数据收集的有前途的解决方案。另一方面，保证无人机辅助数据采集信息的及时性也至关重要。在本文中，我们提出了一种高效的数据收集方案，其中多个地面设备通过上行非正交多址（NOMA）将数据上传到无人机。无人机的总飞行时间被平均划分为NN个时隙。通过联合优化直线轨迹、设备调度和发射功率，最小化每个时隙的持续时间。为了解决这个混合整数非凸优化问题，我们将其分解为两个步骤。第一步，我们研究基于无人机轨迹以及无人机与地面设备之间的信道增益的设备调度策略，通过该策略可以大大简化原始问题。第二步，通过优化发射功率和无人机轨迹来最小化每个时隙的持续时间。提出了一种基于交替优化的迭代算法，其中每个子问题都可以通过应用逐次凸逼近交替求解，并在每次迭代结束时更新设备调度。给出了数值结果来评估所提出方案的有效性。