The use of unmanned aerial vehicles (UAV) as flying radio access network (RAN) nodes offers a promising complement to traditional fixed terrestrial deployments. More recently yet still in the context of wireless networks, drones have also been envisioned for use as radio frequency (RF) sensing and localization devices. In both cases, the advantage of using UAVs lies in their ability to navigate themselves freely in 3D and in a timely manner to locations of space where the obtained network throughput or sensing performance is optimal. In practice, the selection of a proper location or trajectory for the UAV very much depends on local terrain features, including the position of surrounding radio obstacles. Hence, the robot must be able to map the features of its radio environment as it performs its data communication or sensing services. The challenges related to this task, referred here as radio mapping, are discussed in this paper. Its promises related to efficient trajectory design for autonomous radio-aware UAVs are highlighted, along with algorithm solutions. The advantages induced by radio-mapping in terms of connectivity, sensing, and localization performance are illustrated.
翻译:使用无人驾驶航空器作为飞行无线电接入网络(RAN)节点是传统固定地面部署的一个很有希望的补充,最近,在无线网络方面,无人驾驶航空器也设想用作无线电频率(RF)遥感和地方化装置,在这两种情况下,使用无人驾驶航空器的优势在于它们能够以3D和及时的方式在空间地点自由巡航,在那里获得的网络通过量或感测性能是最佳的,实际上,无人驾驶航空器的适当位置或轨迹的选择在很大程度上取决于当地地形特征,包括周围无线电障碍的位置,因此,机器人必须能够在进行数据通信或感测服务时绘制其无线电环境特征的地图,本文将讨论与这项任务有关的挑战,这里称为无线电制图,重点介绍与自动无线电觉测无人驾驶飞行器有效轨迹设计有关的承诺,以及算法解决办法。