Due to the agile maneuverability, unmanned aerial vehicles (UAVs) have shown great promise for on-demand communications. In practice, UAV-aided aerial base stations are not separate. Instead, they rely on existing satellites/terrestrial systems for spectrum sharing and efficient backhaul. In this case, how to coordinate satellites, UAVs and terrestrial systems is still an open issue. In this paper, we deploy UAVs for coverage enhancement of a hybrid satellite-terrestrial maritime communication network. Using a typical composite channel model including both large-scale and small-scale fading, the UAV trajectory and in-flight transmit power are jointly optimized, subject to constraints on UAV kinematics, tolerable interference, backhaul, and the total energy of the UAV for communications. Different from existing studies, only the location-dependent large-scale channel state information (CSI) is assumed available, because it is difficult to obtain the small-scale CSI before takeoff in practice and the ship positions can be obtained via the dedicated maritime Automatic Identification System. The optimization problem is non-convex. We solve it by using problem decomposition, successive convex optimization and bisection searching tools. Simulation results demonstrate that the UAV fits well with existing satellite and terrestrial systems, using the proposed optimization framework.

中文翻译：

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使用与混合卫星地面网络协调的无人机来增强海上覆盖范围

由于灵活的机动性，无人驾驶飞行器 (UAV) 在按需通信方面显示出巨大的潜力。实际上，无人机辅助的空中基站并不是独立的。相反，他们依靠现有的卫星/地面系统进行频谱共享和高效回程。在这种情况下，如何协调卫星、无人机和地面系统仍然是一个悬而未决的问题。在本文中，我们部署无人机以增强混合卫星-地面海上通信网络的覆盖范围。使用包含大尺度和小尺度衰落的典型复合信道模型，在无人机运动学、可容忍干扰、回程和无人机总能量的约束下，联合优化无人机轨迹和飞行中发射功率。通讯。与现有研究不同，假设只有与位置相关的大规模信道状态信息（CSI）可用，因为在实际起飞前很难获得小规模CSI，而船舶位置可以通过专用的海上自动识别系统获得。优化问题是非凸的。我们通过使用问题分解、连续凸优化和二分搜索工具来解决它。仿真结果表明，使用所提出的优化框架，无人机可以很好地适应现有的卫星和地面系统。我们通过使用问题分解、连续凸优化和二分搜索工具来解决它。仿真结果表明，使用所提出的优化框架，无人机可以很好地适应现有的卫星和地面系统。我们通过使用问题分解、连续凸优化和二分搜索工具来解决它。仿真结果表明，使用所提出的优化框架，无人机可以很好地适应现有的卫星和地面系统。