Can I read Open-Set RF Fingerprinting via Improved Prototype Learning on EtoBox?

Open-Set RF Fingerprinting via Improved Prototype Learning by Wang, Weidong; Liao, Hongshu; Gan, Lu is a scholarly article available to read on EtoBox.

What is Open-Set RF Fingerprinting via Improved Prototype Learning about?

Deep learning has been widely used in radio frequency (RF) fingerprinting. Despite its excellent performance, most existing methods only consider a closed-set assumption, which cannot effectively tackle signals emitted from those unknown devices that have never been seen during training. In this letter, we exploit prototype learning for open-set RF fingerprinting and propose two improvements, including consistency-based regularization and online label smoothing, which aim to learn a more robust feature space. Experimental results on a real-world RF dataset demonstrate that our proposed measures can significantly improve prototype learning to achieve promising open-set recognition performance for RF fingerprinting.

Author

Wang, Weidong; Liao, Hongshu; Gan, Lu

Published

2023

Language

EN