This paper studies an unmanned aerial vehicle (UAV)-enabled multiple access channel (MAC), in which multiple ground users transmit individual messages to a mobile UAV in the sky. We consider a linear topology scenario, where these users locate in a straight line and the UAV flies at a fixed altitude above the line connecting them. Under this setup, we jointly optimize the one-dimensional (1D) UAV trajectory and wireless resource allocation to reveal the fundamental rate limits of the UAV-enabled MAC, under the users’ individual maximum power constraints and the UAV’s maximum flight speed constraints. First, we consider the capacity-achieving non-orthogonal multiple access (NOMA) transmission with successive interference cancellation (SIC) at the UAV receiver. In this case, we characterize the capacity region by maximizing the average sum-rate of all users subject to a set of rate profile constraints. To optimally solve this highly non-convex problem with infinitely many UAV location variables over time, we show that any speed-constrained UAV trajectory is equivalent to the combination of a maximum-speed flying trajectory and a speed-free trajectory, and accordingly transform the original speed-constrained trajectory optimization problem into a speed-free problem that is optimally solvable via the Lagrange dual decomposition. It is rigorously proved that the optimal 1D trajectory solution follows the successive hover-and-fly (SHF) structure, i.e., the UAV successively hovers above a number of optimized locations, and flies unidirectionally among them at the maximum speed. Next, we consider two orthogonal multiple access (OMA) transmission schemes, i.e., frequency-division multiple access (FDMA) and time-division multiple access (TDMA). We maximize the achievable rate regions in the two cases by jointly optimizing the 1D trajectory design and wireless resource (frequency/time) allocation. It is shown that the optimal trajectory solutions still follow the SHF structure but with different hovering locations for each scheme. Finally, numerical results show that the proposed optimal trajectory designs achieve considerable rate gains over other benchmark schemes, and the capacity region achieved by NOMA significantly outperforms the rate regions by FDMA and TDMA.

中文翻译：

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具有轨迹优化的 UAV 启用多址信道的基本速率限制

本文研究了一种支持无人机 (UAV) 的多路访问信道 (MAC)，其中多个地面用户向空中的移动 UAV 发送单独的消息。我们考虑一个线性拓扑场景，这些用户位于一条直线上，无人机在连接他们的线路上方的固定高度飞行。在这种设置下，我们联合优化一维（1D）无人机轨迹和无线资源分配，以揭示在用户个人最大功率约束和无人机最大飞行速度约束下启用无人机的 MAC 的基本速率限制。首先，我们考虑在 UAV 接收器上使用连续干扰消除 (SIC) 实现容量实现的非正交多址 (NOMA) 传输。在这种情况下，我们通过最大化受一组速率配置文件约束的所有用户的平均总速率来表征容量区域。为了最佳地解决这个具有无限多个 UAV 位置变量随时间变化的高度非凸问题，我们证明了任何速度受限的 UAV 轨迹等价于最大速度飞行轨迹和无速度轨迹的组合，并相应地变换将原始速度约束的轨迹优化问题转化为无速度问题，该问题可通过拉格朗日对偶分解最优解。严格证明，最优一维轨迹解遵循连续悬停飞行（SHF）结构，即无人机连续悬停在多个优化位置上方，并以最大速度单向飞行。下一个，我们考虑两种正交多址（OMA）传输方案，即频分多址（FDMA）和时分多址（TDMA）。我们通过联合优化一维轨迹设计和无线资源（频率/时间）分配来最大化两种情况下可实现的速率区域。结果表明，最佳轨迹解决方案仍然遵循 SHF 结构，但每个方案的悬停位置不同。最后，数值结果表明，与其他基准方案相比，所提出的最优轨迹设计实现了相当大的速率增益，并且 NOMA 实现的容量区域显着优于 FDMA 和 TDMA 的速率区域。我们通过联合优化一维轨迹设计和无线资源（频率/时间）分配来最大化两种情况下可实现的速率区域。结果表明，最佳轨迹解决方案仍然遵循 SHF 结构，但每个方案的悬停位置不同。最后，数值结果表明，与其他基准方案相比，所提出的最优轨迹设计实现了相当大的速率增益，并且 NOMA 实现的容量区域显着优于 FDMA 和 TDMA 的速率区域。我们通过联合优化一维轨迹设计和无线资源（频率/时间）分配来最大化两种情况下可实现的速率区域。结果表明，最佳轨迹解决方案仍然遵循 SHF 结构，但每个方案的悬停位置不同。最后，数值结果表明，与其他基准方案相比，所提出的最优轨迹设计实现了相当大的速率增益，并且 NOMA 实现的容量区域显着优于 FDMA 和 TDMA 的速率区域。