Volume 38, Number 5, October 2020
|Page(s)||1074 - 1083|
|Published online||08 December 2020|
A Few-Shot Modulation Recognition Method Based on Pseudo-Label Semi-Supervised Learning
Institute of Information & Navigation, Air Force Engineering University, Xi'an 710077, China
In order to solve the problem of insufficient labeled samples in modulation recognition, this paper proposes a few-shot modulation recognition algorithm based on pseudo-label semi-supervised learning (pseudo-label algorithm). First of all, high quality artificial feature, excellent classifier and data-labeling method are used to build efficient pseudo label system, and then the pseudo label system is combined with signal classification method based on the deep learning to realize the modulation classification under the condition of a small number of labeled samples and a large number of unlabeled samples. The simulation results show that the pseudo-label algorithm can improve the model recognition performance by 5%-10% when the six kinds of digital signals are classified and identified and its SNR is greater than 5 dB. At the same time, the algorithm has a simple network design and is of great application value.
Key words: modulation recognition / pseudo-label algorithm / semi-supervised learning / simulation
关键字 : 调制识别 / 伪标签 / 半监督学习
© 2020 Journal of Northwestern Polytechnical University. All rights reserved.
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