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Multi-Modal Environment Semantics Information Aided UAV Beam Alignment

delete2026-02-20
delete0
PRE
AI
L
Lei Huang
S
Shengchun Huang
D
Dengke Guo
D
Dongtang Ma
J
Jun Xiong
H
Haitao Zhao
J
JiBo WEI
DOI：10.1109/tvt.2026.3666561delete
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摘要

摘要

En 中文
在6G定向通信中，高频毫米波（mmWave）和太赫兹（THz）信号受严重传播损耗且极易受阻挡，而无人机（UAV）的高机动性进一步加剧了链路建立难度。为应对这些挑战，本文提出了一种新型UAV波束对准方案，通过利用多模态环境语义信息，将多模态语义集成到高度动态的UAV环境中以提高波束对准精度。具体而言，提出了一种双路径特征提取模块，通过目标检测获取视觉语义，并通过GPS/INS融合获取位置语义。设计了一种基于双向交叉注意力机制的神经网络，以有效融合多模态环境语义信息并输出最优波束。仿真结果表明，通过多模态融合显著提升了波束对准精度。与现有的仅依赖视觉或仅依赖位置的方案相比，所提方案分别将Top-1准确率提升了16.25%和74.66%。
Keyword:
Beam alignment
multi-modal environment semantics information
bidirectional cross-attention
UAV
mmWave

期刊

IEEE Transactions on Vehicular Technology 封面图
IEEE Transactions on Vehicular Technology
IF:
7.1
论文数:
1.8W
被引数:
6.6W

机构

N
national university of defense technology
学者数:
5.0K
论文数: 1.5K
被引数: 0
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