STF-GCN: A Multi-Domain Graph Convolution Network Method for Automatic Modulation Recognition via Adaptive Correlation

IF 7 1区计算机科学 Q1 TELECOMMUNICATIONS

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2025-08-13 DOI:10.1109/tccn.2025.3598243

Mingyuan Shao, Zhengqiu Fu, Dingzhao Li, Fuqing Zhang, Yilin Cai, Shaohua Hong, Lin Cao, Yuan Peng, Jie Qi

引用次数: 0

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STF-GCN：一种基于自适应相关的多域图卷积网络调制识别方法

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来源期刊

IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence

CiteScore

15.50

自引率

7.00%

发文量

108

期刊介绍： The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.