Stable Nonlinear and IQ Imbalance RF Fingerprint for Wireless OFDM Devices

TL;DR

This paper introduces a novel RF fingerprinting method for wireless OFDM devices that leverages hardware-induced nonlinearities and IQ imbalance, providing stable and high-accuracy device authentication despite wireless channel effects.

Contribution

It proposes a new RF fingerprinting approach based on physical hardware properties, using a Hammerstein system and a searching algorithm for IQ imbalance, enhancing device authentication stability.

Findings

The method effectively eliminates wireless channel effects.

It accurately classifies devices with subtle differences.

Numerical experiments confirm stability and high accuracy.

Abstract

An estimation method of Radio Frequency fingerprint (RFF) based on the physical hardware properties of the nonlinearity and in-phase and quadrature (IQ) imbalance of the transmitter is proposed for the authentication of wireless orthogonal frequency division multiplexing (OFDM) devices. Firstly, the parameters of the nonlinearity of the transmitter and finite impulse response (FIR) of the wireless multipath channel are estimated with a Hammerstein system parameter separation technique. Secondly, the best IQ imbalance parameter combination estimation is obtained with a searching algorithm and the applied conjugate anti-symmetric pilots. Thirdly, the estimations of the nonlinear coefficients and IQ imbalance parameter combination are considered as a novel RFF, the features are extracted from the novel RFF, and a k-Nearest Neighbor (k-NN) classifier is used to classify the communication devices with the features. It is demonstrated with the numerical experiments of five transmitters that the novel RFF eliminates the adverse effect of the wireless channel and is therefore stable. The proposed RF fingerprinting method is helpful for the high-strength authentication of the OFDM communication devices with subtle differences from the same model and same series.