The New Algorithm for The Blind Extraction of The Radio Frequency Fingerprint Using the Specific Features of High-Power Amplifier and Local Oscillator

Recently, the radio frequency fingerprint (RFF) has received attention in applications such as specific emiiter identification, detection of deception in navigation signals and detection of intrusion in wireless networks. The RFF is caused by the non-ideal manufacturing of the transmitter components. This effect appears as unintentional modulation in the output of the transmitter and its extraction can be considered as a solution of mentioned applications; Therefore, it is important to provide a method for extracting the RFF, using realistic modeling of the transmitter components. For this purpose, in this article, the combined effects of the power amplifier and local oscillator are considered as the fingerprint of the transmitter. Then, two blind algorithms based on the transmitter output signal are presented to extract the amplifier phase characteristic and the local oscillator phase noise. In the first algorithm, the phase function of the power amplifier in the presence of phase noise is estimated using the M’th order moment of the transmitter output signal. Then the power characteristic of the transmitter's local oscillator noise phase is obtained by blind estimation of its autocorrelation function. At the end, the results of the performance of the algorithms in the simulations are examined and it is shown that only for 1.5dB difference in power amplifier saturation power and 2dB difference in phase noise amount, two transmitters with the same modulations and frequencies can be separated with 98% accuracy in signal-to-noise ratio(SNR) equal to 10dB, where this precision is achievable in the recent works at 20dB SNR.