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PUBLICATIONS

Robust Measurements for RF Fingerprinting with Constellation Patterns of Radiated Waveforms

Published

Author(s)

Ameya Ramadurgakar, Jake Rezac, Lennart Heijnen, Kate Remley, Dylan Williams, MELINDA PIKET-MAY, Rob Horansky

Abstract

We introduce a type of RF fingerprint for nondestructive, cellular device identification. The new fingerprinting algorithm, termed Eigenphones, is a data-driven technique based on a singular value decomposition of a user equipment's symbol-constellation points. We explore the effectiveness of the fingerprint technique with a test set of real devices and show, experimentally, that this fingerprint metric is robust to device positioning errors and measurement noise.
Proceedings Title
2023 IEEE Physical Assurance and Inspection of Electronics (PAINE)
Conference Dates
October 25-27, 2023
Conference Location
Huntsville, AL, US
Pub Type
Conferences

Download Paper

https://doi.org/10.1109/PAINE58317.2023.10318021
Local Download

Keywords

RF Fingerprinting, Over the Air Measurements, Supply Chain Security
Wireless (RF) and Advanced communications

Citation

Ramadurgakar, A. , Rezac, J. , Heijnen, L. , Remley, K. , Williams, D. , Piket-May, M. and Horansky, R. (2023), Robust Measurements for RF Fingerprinting with Constellation Patterns of Radiated Waveforms, 2023 IEEE Physical Assurance and Inspection of Electronics (PAINE), Huntsville, AL, US, [online], https://doi.org/10.1109/PAINE58317.2023.10318021, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=956276 (Accessed October 17, 2025)

Issues

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Created November 20, 2023, Updated December 22, 2023
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