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FEGNN:Graph Neural Network with Feature Embedding for Automatic Modulation Classification

Shaogang Dai Jianwei Xu Jie Chen Shilian Zheng Xiaoniu Yang

电子学报（英文）2025，Vol.34Issue(6)：1746-1756,11.

电子学报（英文）2025，Vol.34Issue(6)：1746-1756,11.DOI:10.23919/cje.2025.00.052

FEGNN:Graph Neural Network with Feature Embedding for Automatic Modulation Classification

Shaogang Dai ¹Jianwei Xu ²Jie Chen ²Shilian Zheng ³Xiaoniu Yang³

作者信息

1. School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310000,China||Zhejiang Key Laboratory of Intelligent Vehicle Electronics Research,Hangzhou 310018,China
2. School of Communication Engineering,Hangzhou Dianzi University,Hangzhou 310000,China
3. Science and Technology on Communication Information Security Control Laboratory,Jiaxing 314033,China
折叠

摘要

关键词

Automatic modulation recognition/Graph neural network/Data augmentation/Deep learning

Key words

Automatic modulation recognition/Graph neural network/Data augmentation/Deep learning

引用本文复制引用

Shaogang Dai,Jianwei Xu,Jie Chen,Shilian Zheng,Xiaoniu Yang..FEGNN:Graph Neural Network with Feature Embedding for Automatic Modulation Classification[J].电子学报（英文）,2025,34(6):1746-1756,11.

基金项目

This work was supported by the National Key R&D Pro-gram of China(Grant No.2024YFB4207200),the Foun-dation of Zhejiang Key Laboratory of Intelligent Vehicle Electronics Research,and the Open Fund of National Defense Science and Technology Key Laboratory(Grant No.2021-JCJQ-LB-053-06). （Grant No.2024YFB4207200）

电子学报（英文）

ISSN：1022-4653

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