RCQCC: A Channel-Resilient Radio Frequency Fingerprinting Scheme for WiFi Device

Radio Frequency Fingerprint (RFF) technology provides secure identification of wireless communication devices by capturing physical characteristics resulting from differences in hardware manufacturing. However, time-varying channels pose a serious challenge to the robustness of RFF extraction. Therefore, this letter proposes a novel channel-robust RFF extraction method called Radio Constant Q Cepstrum Coefficient (RCQCC). The core idea draws inspiration from the Constant Q Cepstrum Coefficient (CQCC) method used in speaker recognition. Specifically, the scheme includes two steps: First, an adaptive octave partitioning strategy is designed based on the difference of the frequency domain between radio signal and speech signal, and constant Q transform is used to extract the response from the signal’s frequency domain. Then, RFF and channel interference are effectively separated by cepstrum analysis. In the experiment, data were collected from different positions in two different environments using 7 WiFi devices. The results show that the average identification accuracy of the proposed method is 99.13% in the single environment and 94.00% in the cross environment.