@inproceedings{743873b4f58840c9b013771ea024bfe2,
title = "Attentional Cross-layer Fusion Network for Enhanced Spectrum Sensing",
abstract = "Recently, spectrum sensing algorithms based on convolutional neural networks have achieved excellent performance. However, most existing algorithms rely only on features from the highest convolutional layer, potentially limiting further performance improvements. To address this, this paper proposes an attention cross-layer fusion network for enhanced spectrum sensing. The designed fusion module adaptively combines multilayer features via attention mechanisms, effectively preserving critical details while leveraging high-level semantic information. Simulation results show that the proposed algorithm outperforms classical spectrum sensing algorithms. Notably, the proposed algorithm achieves a detection probability of 98.2\% with a false alarm probability of 10\% at SNR = -18dB.",
keywords = "Cognitive radio, convolutional neural network, feature fusion, spectrum sensing",
author = "Junnan Zhao and Xi Yang and Kejun Lei and Siyu Wang and Yinhang Zhang and Renwei Wang",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 5th International Conference on Advances in Electrical, Electronics and Computing Technology, EECT 2025 ; Conference date: 21-03-2025 Through 23-03-2025",
year = "2025",
doi = "10.1109/EECT64505.2025.10967005",
language = "英语",
series = "EECT 2025 - 2025 5th International Conference on Advances in Electrical, Electronics and Computing Technology, Proceeding",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
editor = "Jizhong Zhu and Tseng, \{King Jet\}",
booktitle = "EECT 2025 - 2025 5th International Conference on Advances in Electrical, Electronics and Computing Technology, Proceeding",
address = "美国",
}