Power Amplifier enabled RF Fingerprint Identification
Yuepei Li, Yuan Ding, George Goussetis, Junqing Zhang · 2021
The development of radio frequency fingerprint (RFF) identification technique aims to identify and classify 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 based on image recognition method is 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 rate exceeds 99%.