Spectrum prediction based on GAN and deep transfer learning: A cross-band data augmentation framework

This paper investigates the problem of data scarcity in spectrum prediction. A cognitive radio equipment may frequently switch the target frequency as the electromagnetic environment changes. The previously trained model for prediction often cannot maintain a good performance when facing small amoun...

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Veröffentlicht in:	China communications 2021-01, Vol.18 (1), p.18-32
Hauptverfasser:	Lin, Fandi, Chen, Jin, Ding, Guoru, Jiao, Yutao, Sun, Jiachen, Wang, Haichao
Format:	Artikel
Sprache:	eng
Schlagworte:	cognitive radio cross-band data augmentation framework cross-band spectrum prediction Data models deep transfer learning generative adversarial network Generative adversarial networks Hidden Markov models Predictive models Time-frequency analysis Training Transfer learning
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