论文标题
用于集成本地化和通信的双功能无人机的部署优化
Deployment Optimization of Dual-functional UAVs for Integrated Localization and Communication
论文作者
论文摘要
在紧急情况下，可以部署无人驾驶汽车（UAV）来协助地面码头的本地化和通信服务。在本文中，我们提出了一种新的集成空中网络范式，该范式使用双功能的无人机来协助地面网络改善通信和本地化性能。我们调查了部署最少无人机数量以满足地面用户的通信和本地化要求的优化问题。该问题存在几个技术困难，包括基数最小化，关于无人机位置的本地化性能度量标准的非跨性别性以及用户和通信终端之间的关联。为了应对困难，我们采用D-典型性作为定位性能指标，并基于准确的近似值来得出2D和3D中可行的无人机悬停区域的几何特性。我们通过将问题转换为最小击球问题，并提出一种低复杂性算法来解决它来解决简化的2D投影部署问题。通过数值模拟，我们将提出的算法与基准方法进行比较。提出的算法所需的无人机数接近最佳解决方案，而其他基准方法则需要更多的无人机来完成相同的任务。
In emergency scenarios, unmanned aerial vehicles (UAVs) can be deployed to assist localization and communication services for ground terminals. In this paper, we propose a new integrated air-ground networking paradigm that uses dual-functional UAVs to assist the ground networks for improving both communication and localization performance. We investigate the optimization problem of deploying the minimal number of UAVs to satisfy the communication and localization requirements of ground users. The problem has several technical difficulties including the cardinality minimization, the non-convexity of localization performance metric regarding UAV location, and the association between user and communication terminal. To tackle the difficulties, we adopt D-optimality as the localization performance metric, and derive the geometric characteristics of the feasible UAV hovering regions in 2D and 3D based on accurate approximation values. We solve the simplified 2D projection deployment problem by transforming the problem into a minimum hitting set problem, and propose a low-complexity algorithm to solve it. Through numerical simulations, we compare our proposed algorithm with benchmark methods. The number of UAVs required by the proposed algorithm is close to the optimal solution, while other benchmark methods require much more UAVs to accomplish the same task.
