Wireless Physical-Layer Identification: Modeling and Validation

The imperfections in the RF frontend of different transmitters can be used to distinguish them. This process is called transmitter identification using RF fingerprints. The nonlinearity in the power amplifier of the RF frontend is a significant cause of the discrepancy in RF fingerprints, which enables transmitter identification. In this work, we use deep learning to identify different transmitters using their nonlinear characteristics. By developing a nonlinear model generator based on extensive measurements, we were able to extend the evaluation of transmitter identification to include a larger number of transmitters beyond what exists in the literature. We were also able to study the impact of transmitter variability on identification accuracy. Additionally, many other factors were considered including modulation type, length of data used for identification, and type of data being transmitted whether identical or random under a realistic channel model. Simulation results were compared with experiments which confirmed similar trends.

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“…where α and β are the model parameters 1 . The fit was performed using the least squares equations from [7].…”

Section: A Measurements and Fittingmentioning

confidence: 99%

“…The imperfections that enable this differentiation between transmitters arise from clock jitter, digital to analog converters, sampling errors, mixers or local frequency synthesizers, power amplifiers' non-linearity, device antennas, etc. The power amplifier's non-linearity is considered as the most significant source of differences [1].…”

Section: Introductionmentioning

confidence: 99%

Deep Learning Based Transmitter Identification using Power Amplifier Nonlinearity

Hanna

Čabrić

2019

2019 International Conference on Computing, Networking and Communications (ICNC)

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Wireless Physical-Layer Identification: Modeling and Validation

Cited by 1 publication

References 9 publications

Deep Learning Based Transmitter Identification using Power Amplifier Nonlinearity

Deep Learning Based Transmitter Identification using Power Amplifier Nonlinearity

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