Power Amplifier enabled RF Fingerprint Identification

Yuepei Li, Yuan Ding, George Goussetis, Junqing Zhang

Research output: Contribution to conferencePaperpeer-review

Abstract

Radio frequency fingerprint (RFF) identification technique was developed with the aim of identifying and classifying wireless devices by exploiting their unique radio frequency (RF) features. This paper proposes a wireless device RFF identification scheme, which relies on the non-linear memory effect resulting from the concatenation of two matched root-raised cosine (RRC) filters with a non-linear power amplifier (PA) inserted in-between. This unique feature can be extracted from the distorted constellation diagrams, which is processed into density trace figure. Classification algorithm is based on image recognition methods developed to exploit the non-linear memory effect from the density trace figure. Simulation setup is carefully designed, and the results validated the effectiveness of our proposed RFF feature classification approach. In the range of SNR 1 dB to 25 dB, the overall identification accuracy is as high as 99%.
Original languageEnglish
Publication statusAccepted/In press - 13 Apr 2021
Event2021 IEEE Texas Symposium on Wireless and Microwave Circuits and Systems - , United States
Duration: 18 May 202120 May 2021
https://texassymposium.org/

Conference

Conference2021 IEEE Texas Symposium on Wireless and Microwave Circuits and Systems
CountryUnited States
Period18/05/2120/05/21
Internet address

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