电讯技术2024，Vol.64Issue(1)：22-28,7.DOI:10.20079/j.issn.1001-893x.220529001
基于时频融合的深度学习调制识别算法
A Deep Learning Modulation Recognition Algorithm Based on Time-Frequency Fusion
摘要
Abstract
Automatic modulation recognition(AMR)can identify the modulation type of the received signal without a priori information,and plays a vital role in non-cooperative communication.In order to improve the accuracy of modulation recognition,a deep learning modulation recognition algorithm based on time-frequency fusion is proposed.The algorithm takes the time-frequency diagram of the modulated signal as the input of the network,uses one-dimensional convolution to extract the time-frequency characteristics of the signal respectively,and highlights the important time-frequency information by calculating the weight in the time-frequency dimension,so that the network can learn more differentiated time-frequency features.In order to make full use of the complementarity and correlation between time-frequency features,a time-frequency feature fusion strategy based on Squeeze-and-Excitation Network(SENet)is used.Using this network,11 modulation types are recognized,and the recognition accuracy is up to 92.5%.Above 0 dB,the average recognition accuracy reaches 90.87%,which is better than that of other deep learning algorithms.关键词
非合作通信/自动调制识别/深度学习/时频融合Key words
non-cooperative communication/automatic modulation recognition/deep learning/time-frequency fusion分类
信息技术与安全科学引用本文复制引用
李辉,龚晓峰,雒瑞森..基于时频融合的深度学习调制识别算法[J].电讯技术,2024,64(1):22-28,7.基金项目
四川省重点研发计划项目(2020YFG0051) （2020YFG0051）
校企合作项目(19H1121,21H1445) （19H1121,21H1445）
