Abstract
This letter proposes a transfer learning model for automatic modulation recognition (AMR) with only a few modulated signal samples. The transfer model is trained with the audio signal UrbanSound8K as the source domain, and then fine-tuned with a few modulated signal samples as the target domain. For improving the classification performance, the signal-to-noise ratio (SNR) is utilized as a feature to facilitate the classification of signals. Simulation results indicate that the transfer model has a significant superiority in terms of classification accuracy.
Original language | English |
---|---|
Pages (from-to) | 12391-12395 |
Number of pages | 5 |
Journal | IEEE Transactions on Vehicular Technology |
Volume | 72 |
Issue number | 9 |
DOIs | |
State | Published - 1 Sep 2023 |
Keywords
- automatic modulation recognition
- convolutional neural network
- deep learning
- few-shot learning
- Transfer learning