Wang, Min, Peng, Linning, Xie, Lingnan, Zhang, Junqing 
ORCID: 0000-0002-3502-2926, Liu, Ming and Fu, Hua
(2024)
Design of Noise Robust Open-Set Radio Frequency Fingerprint Identification Method.
In: INFOCOM DeepWireless Workshop, 2024-5-20 - 2024-5-23, Vancouver, Canada.
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INFOCOM DeepWireless Workshop 2024 RFFI.pdf - Author Accepted Manuscript Download (1MB) | Preview |
Abstract
Radio frequency fingerprint (RFF) identification (RFFI) is a promising technique for device authentication at the physical layer of the communication stacks. However, practical challenges, particularly in low signal-to-noise ratio (SNR) scenarios, and the lack of comprehensive studies on open-set recognition hinder the widespread application of RFFI. This paper presents an unsupervised open-set RFF identification algorithm designed to address the robustness challenges associated with low SNR. Our approach integrates the Noise2Noise method for denoising, drawing inspiration from its successful applications in image and speech processing. The proposed framework utilizes an image- based autoencoder (AE) to extract features from the differential constellation trace figure (DCTF) of the signals after Noise2Noise denoising. The open-set recognition task is performed by cosine distance measurement. We carried out extensive experimental evaluation involving 18 ZigBee devices and a USRP software-defined radio platform. Our proposed method can achieve a gain up to 25% under low SNRs
| Item Type: | Conference or Workshop Item (Unspecified) |
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| Divisions: | Faculty of Science and Engineering > School of Electrical Engineering, Electronics and Computer Science |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 26 Feb 2024 09:29 |
| Last Modified: | 26 Feb 2024 09:29 |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3178859 |
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