基于射线发射生成REMs的无人机辅助移动网络性能评估

Silvia Mignardi, M. J. Arpaio, C. Buratti, E. Vitucci, F. Fuschini, R. Verdone
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引用次数: 2

摘要

无人驾驶飞行器(UAV),也被称为无人机,作为许多新兴技术和应用的推动者,正受到越来越多的关注,这一趋势可能会在未来继续下去。在这方面,使用无人机基站(uabs),即由无人机携带的基站,是最有希望为那些没有地面基站服务的用户提供5G应用覆盖和容量的手段之一。在本文中,我们提出了一种新的方法,用于无人机辅助网络的弹道设计和无线电资源管理(RRM),利用从精确无线电环境图(REM)中检索的信息,基于射线发射(RL)模拟,用于射频传播和窄带估计。此外,我们考虑了安装在多个uabs上的天线的不同可能模型,以及能够利用REM输入的适当RRM策略。仿真结果将显示系统对不同方法所取得的性能,并将它们与以前使用的统计模型进行比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Performance Evaluation of UAV-Aided Mobile Networks by Means of Ray Launching Generated REMs
Unmanned Aerial Vehicles (UAV), also known as drones, are receiving increasing attention as enablers for many emerging technologies and applications, a trend likely to continue in the next future. In this regard, using Unmanned Aerial Base Stations (UABSs), i.e. base stations carried by UAVs, is one of the most promising means to offer coverage and capacity in 5G applications to those users that are not being served by terrestrial base stations. In this paper, we propose a novel approach for trajectory design and Radio Resource Management (RRM) in UAV-aided networks using information retrieved from precise Radio Environmental Map (REM) based on Ray Launching (RL) simulations for RF propagation and narrow band estimations. Furthermore, we consider different possible models for antennas to be installed on multiple UABSs as well as proper RRM strategies which are able to take advantage of REM inputs. Simulation results will show the performance achieved by the system for the different approaches and it will compare them with the previous use of statistical models.
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