The ability to operate virtually anywhere and carry payload makes Unmanned Aerial Vehicles (UAVs) perfect platforms to carry communications nodes, including Wi-Fi Access Points (APs) and cellular Base Stations (BSs). This is paving the way to the deployment of flying networks that enable communications to ground users on demand. Still, flying networks impose significant challenges in order to meet the Quality of Experience expectations. State of the art works addressed these challenges, but have been focused on routing and the placement of the UAVs as APs and BSs serving the ground users, overlooking the backhaul network design. The main contribution of this paper is a centralized traffic-aware Gateway UAV Placement (GWP) algorithm for flying networks with controlled topology. GWP takes advantage of the knowledge of the offered traffic and the future topologies of the flying network to enable backhaul communications paths with high enough capacity. The performance achieved using the GWP algorithm is evaluated using ns-3 simulations. The obtained results demonstrate significant gains regarding aggregate throughput and delay.
翻译:几乎在任何地方运行并携带有效载荷的能力使无人驾驶航空飞行器(无人驾驶飞行器)能够完美地搭载通信节点,包括无线接入点和蜂窝基地站。这为部署飞行网络铺平了道路,使需要时能够向地面用户提供通信。不过,飞行网络也带来了重大挑战,以满足对经验质量的预期。最新工艺成果克服了这些挑战,但侧重于将无人驾驶飞行器作为为地面用户服务的APs和BS置于路线和位置,忽略了回航网络的设计。本文的主要贡献是利用中央交通通航网关UAV定位(全球升温潜能值)算法,用于控制地形的飞行网络。全球升温潜能值利用所提供的交通知识以及飞行网络今后的地形学,使回航线路能够有足够能力,使用全球升温潜能值算法的绩效是通过Ns-3模拟进行评估的。获得的结果表明,在总流量和延迟方面,取得了显著的成绩。