Research On Individual Identification Of Wireless Devices Based On Signal'S Energy Distribution

With the rapid development of new technologies, such as cognitive communication, cloud computing, quantum computing and big data, the security of the wireless network is being confronted with a series of new threats and challenges. The radio frequency fingerprinting (RFF) extracting from radio signals is a physical-layer method for wireless network security. In this paper, a novel feature extraction method based on the signal's energy distribution is proposed, an experiment under the real wireless device environments has evaluated validation. The experiment results indicate that the identification rate is higher than 95% at SNR > 25 dB, which proved that the method is well-suited for wireless device identification tasks, and promising for a wide variety of related security problems.