无线电工程2026，Vol.56Issue(1)：48-60,13.DOI:10.3969/j.issn.1003-3106.2026.01.006
基于TFAM-AVGNet的CR信号调制识别算法研究
Research on CR Signal Modulation Recognition Algorithm Based on TFAM-AVGNet
摘要
Abstract
Aiming at the problem of poor classification ability when facing complex signal types in the modulation recognition task of Cognitive Radio(CR)signals,an improved CR signal modulation recognition algorithm based on Temporal Fusion Attention Module(TFAM)and Adaptive Visibility Graph Neural Network(AVGNet)is proposed by combining the new graph deep learning theory.The problems such as overfitting of deep Graph Neural Network(GNN),gradient vanishing and simplistic feature fusion methods existing in the current AVGNet model are studied.By conducting data augmentation on the training set and introducing Residual Connections(RC)and TFAM,etc.,the gradient vanishing is alleviated and the feature reuse ability,as well as the training stability and convergence speed is improved.The experimental results show that the average recognition accuracy of the improved TFAM-AVGNet model is increased by more than 1.4%compared with the existing AVGNet model.关键词
认知无线电/调制识别/可视图/TFAM-AVGNet模型Key words
cognitive radio/modulation recognition/visibility graph/TFAM-AVGNet model分类
信息技术与安全科学引用本文复制引用
杜宇鑫,黄光亮,周振兴..基于TFAM-AVGNet的CR信号调制识别算法研究[J].无线电工程,2026,56(1):48-60,13.基金项目
扬州市创新能力建设计划项目(YZ2022174)Yangzhou Municipal Innovation Capability Construction Plan Project(YZ2022174) （YZ2022174）
