Robust 60-GHz Beamforming for UAVs: Experimental Analysis of Hovering, Blockage, and Beam Selection
Robust 60-GHz Beamforming for UAVs: Experimental Analysis of Hovering, Blockage, and Beam Selection
复制标题
DOI：
10.1109/jiot.2020.3019456
复制
发表时间：
2021-06
影响因子：
10.6
通讯作者：
Sara Garcia Sanchez;K. Chowdhury
中科院分区：
文献类型：
--
作者：
Sara Garcia Sanchez;K. Chowdhury
无人机（UAV）安装的毫米波（mmWave）基站以及空中回程链路将实现网络资源的按需部署。然而，先前的工作已经表明，空中链路容易因以下原因而频繁中断：1）由于GPS不准确而影响窄波束宽度的持续悬停; 2）直接视线中的阻塞;以及3）次优波束选择，特别是如果在高度动态环境中搜索减小的角度扇区。本文描述了这些现象对空中毫米波链路的影响，并提出了在部署过程中单独或组合发生这些现象的方法。此外，它还提出了在无人机上的校正措施，适合于特定类型的撞击事件：从其先前位置的物理位移，围绕其垂直轴的角旋转，或波束宽度调整。我们的方法依赖于利用包含在角度域的实验收集的波束选择结果的大数据集的信息，在上述实际情况下。我们将GPS精度模型和天线辐射模式，以创建一个强大的模型的潜在中断。然后，我们提出了设备无关的算法，共同优化无人机的物理运动和波束形成过程。通过在M600 DJI无人机上安装一对60 GHz信道探测器获得的实验结果显示，与经典的802.11ad标准定义的方法相比，损耗降低高达74.7%，转化为260%的物理层比特率提高。
Unmanned aerial vehicle (UAV) mounted millimeter-wave (mmWave) base stations as well as aerial backhaul links will enable on-demand deployment of network resources. However, prior work has shown aerial links are prone to the frequent disruption caused by: 1) constant hovering due to GPS inaccuracies that impact narrow beamwidths; 2) blockages in the direct line of sight; and 3) suboptimal beam selection, especially if reduced angular sectors are searched in a highly dynamic environment. This article characterizes the impact of each of these phenomena for aerial mmWave links and proposes methods to distinctly identify when they occur in isolation or in combination during deployment. Furthermore, it also proposes corrective actions at the UAV, appropriate for the specific type(s) of impacting events: physical displacement from its earlier location, angular rotation around its vertical axis, or beamwidth adjustment. Our approach relies on exploiting the information contained in the angular domain of a large data set of experimentally collected beam-selection outcomes, under the above practical scenarios. We incorporate GPS accuracy models and antenna radiation patterns to create a robust model of potential outages. We then propose device-agnostic algorithms that jointly optimize UAVs’ physical movement and the beamforming procedure. The experimental results obtained by mounting a pair of 60-GHz channel sounders on M600 DJI UAVs reveal loss reduction of up to 74.7%, translated into 260% physical layer bit-rate improvement compared to the classical 802.11ad standards-defined approach.