3-D Trajectory Optimization for UAV-Assisted Hybrid FSO/RF Network With Moving Obstacles

IF 5.7 2区 计算机科学 Q1 ENGINEERING, AEROSPACE IEEE Transactions on Aerospace and Electronic Systems Pub Date : 2024-09-18 DOI:10.1109/TAES.2024.3462685
Xiwen Zhang;Shanghong Zhao;Yuan Wang;Xiang Wang;Xinkang Song;Xin Li;Jianjia Li
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Abstract

The utilization of unmanned aerial vehicles (UAVs) as relays significantly enhances the availability of aeronautical free space optical (FSO)/radio frequency (RF) communication links. In this article, a trajectory optimized scheme that maximizes the energy efficiency of the UAV relay is proposed. The focus of our study lies in the maximization of energy efficiency for UAVs, taking into account practical constraints in aeronautical FSO/RF communication networks, particularly the obstruction caused by moving clouds and the required data rates. Based on the cloud modeling, a feasible deployment area for UAVs that ensures line-of-sight communication is obtained. Especially, we derive a theoretical model of propulsion energy consumption for fixed-wing UAV at variable altitudes for three-dimensional (3-D) trajectory optimization. Accordingly, energy-efficient trajectory planning gaining-sharing knowledge is presented to address this issue, and its effectiveness is tested. Through this algorithm, the trajectories of maximum data rate, minimum energy consumption, and optimal energy efficiency are presented, taking into consideration cloud movement. Furthermore, we find optimized energy efficiency values in various atmospheric environments. The numerical results demonstrate that the proposed design achieves significantly higher energy efficiency for the UAV-assisted hybrid FSO/RF network in comparison to other benchmark schemes.
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具有移动障碍物的无人机辅助混合 FSO/RF 网络的 3D 轨迹优化
无人驾驶飞行器(uav)作为中继的利用显著提高了航空自由空间光学(FSO)/射频(RF)通信链路的可用性。本文提出了一种使无人机中继能量效率最大化的轨迹优化方案。我们的研究重点在于无人机的能源效率最大化,同时考虑到航空FSO/RF通信网络的实际限制,特别是移动云和所需数据速率造成的阻碍。在云建模的基础上,获得了保证无人机视距通信的可行部署区域。特别地,我们建立了固定翼无人机变高度推进能量消耗的理论模型,用于三维轨迹优化。针对这一问题,提出了获取共享知识的节能轨迹规划方法,并对其有效性进行了验证。通过该算法,在考虑云移动的情况下,给出了最大数据速率、最小能耗和最优能效的轨迹。此外,我们还发现了各种大气环境下的最佳能源效率值。数值计算结果表明,与其他基准方案相比,所提出的设计方案能够显著提高无人机辅助的FSO/RF混合网络的能量效率。
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来源期刊
CiteScore
7.80
自引率
13.60%
发文量
433
审稿时长
8.7 months
期刊介绍: IEEE Transactions on Aerospace and Electronic Systems focuses on the organization, design, development, integration, and operation of complex systems for space, air, ocean, or ground environment. These systems include, but are not limited to, navigation, avionics, spacecraft, aerospace power, radar, sonar, telemetry, defense, transportation, automated testing, and command and control.
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