Using drones for cellular coverage enhancement is a recent technology that has shown a great potential in various practical scenarios. However, one of the main challenges that limits the performance of drone-enabled wireless networks is the limited flight time. In particular, due to the limited on-board battery size, the drone needs to frequently interrupt its operation and fly back to a charging station to recharge/replace its battery. In addition, the charging station might be responsible to recharge multiple drones. Given that the charging station has limited capacity, it can only serve a finite number of drones simultaneously. Hence, in order to accurately capture the influence of the battery limitation on the performance, it is required to analyze the dynamics of the time spent by the drones at the charging stations. In this paper, we use tools from queuing theory and stochastic geometry to study the influence of each of the charging stations limited capacity and spatial density on the performance of a drone-enabled wireless network.
翻译:使用无人机加强蜂窝覆盖面是一项最新技术,在各种实际情况下都显示出巨大的潜力。然而,限制无人机支持的无线网络运行的主要挑战之一是飞行时间有限。特别是由于机载电池规模有限,无人机需要经常中断运行,飞回充电站进行补给/更换电池。此外,充电站可能负责给多架无人机进行补给。鉴于充电站的容量有限,只能同时为有限数量的无人机提供服务。因此,为了准确捕捉电池限制对性能的影响,它必须分析无人机在充电站所用时间的动态。在本论文中,我们使用来自排队理论和随机几何测量的工具来研究每个充电站的容量有限和空间密度对无人机驱动的无线网络性能的影响。