通过联合用户协会和3D无人机安置来实现吞吐量最大化的HAP-UAV协作计划的调查
Huda Goehar1, Ahmed S Khwaja1, Ali A Alnoman2
1Department of Electrical, Computer and Biomedical Engineering, Toronto Metropolitan University, Toronto, ON M5B 2K3, Canada.
Sensors (Basel, Switzerland)
|July 14, 2023
概括
本研究介绍了无线网络的高空平台 (HAP) 和无人机 (UAV) 合作. 综合系统通过优化3D放置和用户关联,显著提高了地面用户的总下行通量.
科学领域:
- 无线通信网络 无线通信网络
- 网络优化 网络优化
- 空中通信系统 空中通信系统
背景情况:
- 高空平台 (HAP) 和无人机 (UAV) 为无线通信提供了独特的优势.
- 整合HAP和无人机为增强网络覆盖率和容量提供了机会.
- 在这种混合网络中优化部署和用户协会对于性能至关重要.
研究的目的:
- 调查HAP和无人机之间的无线通信协作计划.
- 为了最大限度地提高地面用户的下行链路总吞吐量.
- 优化无人机的三维 (3D) 放置和用户协会.
主要方法:
- 制定一个优化问题,以最大限度地提高下行链路吞吐量.
- 开发一种基于基因算法的方法,用于无人机安置和用户协会.
- 利用K-means算法用于最初的无人机安置,以缩短收时间.
主要成果:
- 拟议的HAP-UAV集成网络与单一的HAP系统相比,实现了更高的总吞吐量.
- 用户协会和无人机放置的联合优化是提高性能的关键.
- 该算法证明了高效的融合,可管理的复杂性和公平的资源分配.
结论:
- HAP-UAV集成网络是一种有效的架构,可以提高无线通信性能.
- 优化的3D无人机放置和动态用户关联对于最大限度地提高网络吞吐量至关重要.
- 提出的基于遗传算法的方法为这个复杂的优化问题提供了有效的解决方案.
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