Radio frequency fingerprint (RF fingerprint) extraction is a technology that can identify the unique radio transmitter at the physical level, using only external feature measurements to match the feature library. RF fingerprint is the reflection of differences between hardware components of transmitters, and it contains rich nonlinear characteristics of internal components within transmitter. RF fingerprint technique has been widely applied to enhance the security of radio frequency communication. In this paper, we propose a new RF fingerprint method based on multidimension permutation entropy. We analyze the generation mechanism of RF fingerprint according to physical structure of radio transmitter. A signal acquisition system is designed to capture the signals to evaluate our method, where signals are generated from the same three Anykey AKDS700 radios. The proposed method can achieve higher classification accuracy than that of the other two steady-state methods, and its performance under different SNR is evaluated from experimental data. The results demonstrate the effectiveness of the proposal.

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In the same way that a biological fingerprint operates, radiometric fingerprinting can be used to designate the unique transmitter of a given signal to improve the security and privacy of wireless communication, using only external feature measurements to match with the feature library. Fingerprinting reflects the unintentional modulation of radio, and it contains rich non-ideal characteristics of internal components within emitter. Our previous research work on finding out effective fingerprintings to establish the unique identity of a transmitter. However, in practical use we find that the change of intentional modulation parameters will affect the working status of internal components, to further affect radiometric fingerprinting. This paper uses information dimension and box dimension of fractal dimension theory to extract the signals fingerprinting to identify three different radios. A signal acquisition system is designed to capture the signals to analyze the effect of modulation parameters on the fingerprinting, where signals are generated under three different modulation modes, signal bandwidths and transmission frequencies. The experimental results show that, firstly, the distribution of radio's fractal dimension feature is different under different modulation modes, secondly, signal bandwidth has little influence on the feature, thirdly, the change of transmission frequency will result in a great degree of drift on the feature.