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适应式双束追踪用于IRS辅助的高速多UAV通信网络

Zhongquan Peng^1,2, Guanglong Huang³, Qian Deng⁴

¹School of Intelligent Manufacturing, Jiangxi Institute of Applied Science and Technology, Nanchang 330100, China.

Sensors (Basel, Switzerland)

|November 13, 2025

概括

本研究介绍了一种适应式双光束跟踪方案,用于智能反射面辅助高速多重无人飞行器网络 (HSMUAVNs). 该方法提高了最糟糕的无人机通信可靠性和性能.

科学领域:

无线通信无线通信
空中网络空中网络
信号处理信号处理

背景情况:

高速多重无人飞行器网络 (HSMUAVNs) 由于动态环境和频道变化而面临性能下降.
智能反射表面 (IRS) 辅助通信是提高空中网络性能的一个有希望的解决方案.
梁错位和严重的通道色是IRS协助的HSMUAVN的关键挑战.

研究的目的:

为IRS协助的HSMUAVN设计一个自适应的双光束跟踪方案.
为了减轻光束错位,并提高最坏情况下的无人机 (UAV) 的性能.
在动态高速空中网络中确保可靠的通信链路.

主要方法:

基于注意力的双层长期短期记忆网络用于无人机空间角度预测.
一个信号与干扰加噪声比率 (SINR) 最大化问题是为最坏的无人机制定的.
优化是通过解问题,并采用半确定的放松,两截式方法和自值分解来实现的.
适应式双光束是由线性加权优化光束组件生成的.

主要成果:

拟议的方案有效地预测UAV空间角度信息,以实现最佳的光束覆盖范围.
梁组件和IRS相位转移的联合优化增强了最糟糕的情况下无人机的SINR.
数字结果显示,在最糟糕的情况下,无人机的性能得到了显著改善.
该计划保证了整个HSMUAVN的足够SINR.

结论:

适应式双光束跟踪方案有效地解决了IRS协助的HSMUAVN中的挑战.
拟议的方法提高了所有无人机的通信可靠性和性能,特别是最坏的情况下.
这项工作为在高速空中网络中保持稳定的通信提供了强大的解决方案.

关键词:

美国国税局 IRS IRS.无人机通信网络的无人机通信网络射线跟踪射线跟踪射线跟踪最大至最小的优化问题

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