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Simulation-Based Analysis of Mobility Models for Wireless UAV-to-X Networks

机译:基于模拟的无线UAV-X网络移动模型分析

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Recently, the use of air base stations located on unmanned aerial vehicles (UAVs) has attracted great attention. Static deployment of a sufficient number of UAVs allows uniform wireless coverage in the demanded areas, where the existing cellular infrastructure has white spots or insufficient capacity. However, UAVs mobility may be required for applications, where UAVs are used to provide communications for mobile groups of users (e.g., massive sport or community events like marathon or music festival) or for patrolling tasks with relaxed requirements for data transmission delays (for example, when collecting information from a large number of mMTC sensors). In such tasks, the movement of UAVs can significantly increase the efficiency of the system, since in this case the coverage of the area can be provided by a smaller number of UAVs following the dynamics of ground users. Nowadays, more and more often the question arises about the mobile communications availability in a remote area, for example, during public events or search operations. The lack of on-demand connectivity with sufficient quality in such areas is unacceptable in modern conditions. Therefore, the study of the behavior of a dynamic UAV network is necessary for decision-making operation in such scenarios. The main contribution of this work is making the user mobility model more human-alike according to the real scenarios. The paper considers two models of UAVs movement, the effectiveness of which is estimated from the point of view of the coverage probability and average fade duration of the signal.
机译:最近,使用位于无人驾驶飞行器(无人机)的空气基站引起了极大的关注。足够数量的无人机的静态部署允许在所需区域中均匀无线覆盖,其中现有的蜂窝基础设施具有白色斑点或容量不足。然而,可能需要UAVS移动性,其中UAV用于为移动组的移动组(例如,Marathon或Marathon或音乐节等社区事件)或用于数据传输延迟的宽松要求的巡逻任务(例如, ,从大量MMTC传感器收集信息时)。在这样的任务中,无人机的运动可以显着提高系统的效率,因为在这种情况下,该区域的覆盖范围可以通过接地用户的动态之后的较少数量的UVS提供。如今,越来越多的问题出现了远程区域中的移动通信可用性,例如,在公共事件或搜索操作期间。在现代条件下,这些地区的质量缺乏适当的质量的按需连通性。因此,在这种情况下决策操作是必要的对动态UAV网络的行为的研究。这项工作的主要贡献是根据真实情景使用户移动模型更加人性化。本文考虑了两种模型的无人机运动,其有效性是从覆盖概率的观点和信号的平均褪色持续时间的观点来估计。

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