CONFERENCE PROCEEDINGS
Advanced Search
Home > Proceedings > Volume 12246 > Article
Paper
9 October 2022 LSRGAN: an RFF denoising recognition network based on adversarial autoencoder
Yilin Wang, Caidan Zhao
Author Affiliations +
Proceedings Volume 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022); 122462D (2022) https://doi.org/10.1117/12.2643691
Event: 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 2022, Qingdao, China
Abstract
The development of mobile communication technology promotes the intercommunication of heterogeneous networks, and the identity authentication of wireless devices is essential to protect communication security of heterogeneous networks. The uniqueness and non-forgery of radio frequency fingerprints (RFFs) originate from the hardware tolerance of wireless devices used by physical layer-based authentication schemes to realize authentication between devices during communication. At this stage, demands for long-distance communication between devices are rising, such as walkie-talkies and drones. In addition, due to the complex and changeable characteristics of the wireless communication environment, noises easily lead to problems of signal feature offset and feature ambiguity, becoming essential factors that affect the accuracy results of device authentication. This paper takes data enhancement as a starting point to study individual identity authentication of wireless devices in the case of low signal to noise ratios (SNRs). Based on adversarial autoencoder (AAE), we propose our low-SNRs signal recognition generative adversarial network (LSRGAN), which reconstructs disturbed and poor-quality wireless signals, and improves recognition performances of signals with low SNRs. Experimental results show that when the SNR is -5dB, the average recognition rate of devices can still reach 95.00%.
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Citation Download Citation
Yilin Wang and Caidan Zhao "LSRGAN: an RFF denoising recognition network based on adversarial autoencoder", Proc. SPIE 12246, 2nd International Conference on Signal Image Processing and Communication (ICSIPC 2022), 122462D (9 October 2022); https://doi.org/10.1117/12.2643691
ACCESS THE FULL ARTICLE
ORGANIZATIONAL
Sign in with credentials provided by your organization.
INSTITUTIONAL
Select your institution to access the SPIE Digital Library.
SELECT YOUR INSTITUTION
PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.
PERSONAL SIGN IN
No SPIE Account? Create one
PURCHASE THIS CONTENT
SUBSCRIBE TO DIGITAL LIBRARY
50 downloads per 1-year subscription
Members: $195
Non-members: $335 ADD TO CART
25 downloads per 1 - year subscription
Members: $145
Non-members: $250 ADD TO CART
PURCHASE SINGLE ARTICLE
Includes PDF, HTML & Video, when available
Members: $17.00
Non-members: $21.00 ADD TO CART
PROCEEDINGS
 8 PAGES
DOWNLOAD PAPER SAVE TO MY LIBRARY
GET CITATION
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Signal to noise ratio
Denoising
Interference (communication)
Detection and tracking algorithms
Signal generators
Wireless communications
Signal processing
RELATED CONTENT
Subscribe to Digital Library
Receive Erratum Email Alert
Back to Top