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按需的多普勒偏移光束成型与智能时空元面

Xiaoyue Zhu^1,2,3,4, Chao Qian^1,2,3,4, Jie Zhang^1,2,3

¹ZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.

Nanophotonics (Berlin, Germany)

|December 16, 2024

概括

这项研究引入了深度学习增强的时空元表,以抵消高速通信中的多普勒效应. 这些智能表面能够实现自适应束形,确保快速移动平台的可靠信号.

科学领域:

电磁波操纵是一种电磁波操纵.
超材料工程超材料工程
通信中的人工智能.

背景情况:

高速通信面临多普勒效应的挑战,多普勒效应会改变信号频率.
时空超表面提供了一种轻量级,具有成本效益的解决方案,用于在时间和空间中操纵电磁波.
现有的方法难以适应地补偿实时的动态多普勒位移.

研究的目的:

开发一种智能系统,在快速变化的场景中自动和自适应地中和多普勒效应.
为了实现可靠的通信,根据需求使用补偿多普勒效应进行光束成型.
为应对诸如斜率和多路径效应等实际挑战.

主要方法:

深度学习与时空元面的整合.
利用一个协同的神经网络来快速实现目标与地表之间的连接.
智能时空元面的制造和实验验证.

主要成果:

证明了多普勒效应的自动和自适应性中和.
通过多普勒效应抵消实现了按需的光束成型.
在微波实验中成功地解决了曲发作场景.

结论:

深度学习辅助的时空超表面为快速变化的环境中高质量的通信提供了强大的解决方案.
拟议的系统有效地补偿多普勒位移,并可以减轻多路径效应.
实验验证证证实了在现实世界应用中实际实施的潜力.

关键词:

多普勒效应是一种多普勒效应.反向设计和深度学习空间时空的元地表面空间时空的元地表面无线通信的无线通信是无线的.

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