WU Jiawei,HE Jie,TANG Yulin.Recognition of Wireless Radio Signal Modulation Methods based on Artificial Intelligence[J].Journal of Chengdu University of Information Technology,2024,39(04):430-435.[doi:10.16836/j.cnki.jcuit.2024.04.006]
基于人工智能的无线电信号调制方式识别
- Title:
- Recognition of Wireless Radio Signal Modulation Methods based on Artificial Intelligence
- 文章编号:
- 2096-1618(2024)04-0430-06
- 分类号:
- TP301.6
- 文献标志码:
- A
- 摘要:
- 近年来越来越多无线电业务和机构的出现,加剧了无线电电磁环境的恶化,因此对无线电信号调制方式的识别是一个重要的研究方向。提出一种基于人工智能的无线电信号调制方式的识别方法,通过利用不同的无线电信号在时频分析图上的特征差异,使用ResNet50深度学习模型完成对无线电信号调制方式的识别分类,在测试集上的识别准确率达95%。通过对比此前基于传统神经网络的无线电调制方式的识别方法,验证了识别结果的准确性和可靠性。实验结果表明,该方法对于无线电信号调制方式的识别具有重要的参考意义。
- Abstract:
- In recent years, the proliferation of wireless radio businesses and organizations has exacerbated the degradation of the electromagnetic environment. Therefore, the identification of modulation methods for wireless radio signals has become a crucial research focus. This paper proposes an AI-based method for recognizing modulation methods of wireless radio signals. By leveraging the distinctive features of different wireless radio signals in time-frequency analysis plots, the ResNet50 deep learning model is employed for the classification of modulation methods. The recognition accuracy on the test set reaches 95%. Comparative analysis with traditional neural network methods validate the accuracy and reliability of the proposed approach. Experimental results indicate the significance of this method in the recognition of wireless radio signal modulation methods.
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备注/Memo
收稿日期:2023-12-21