LoRa radio frequency fingerprint identification based on frequency offset characteristics and optimized LoRaWAN access technology

As an important technology in the development of the Internet of Things, LoRa technology is a Low-Power Wide-Area Network (LPWAN) technology, which has the advantages of low power consumption, long communication distance, anti-interference, and low cost, has been widely used in the current Internet of Things. This paper mainly studies the radio frequency fingerprint technology based on LoRa frequency offset characteristics. First, analyze the LoRa modulation technology, and study the main characteristics of the LoRa modulation technology based on the chirp spread spectrum technology and the physical meaning of several key parameters in the LoRa modulation scheme. Then based on the radio frequency fingerprint technology, the inherent differences between the hardware of different LoRa transmitter modules are studied, the LoRa signal is collected by the USRP device, and the original sampled signal is preprocessed, and the frequency offset is extracted as the radio frequency fingerprint feature of the LoRa terminal device. Features identify different devices. This article uses the radio frequency fingerprint extraction based on the frequency offset LoRa signal. According to the extracted radio frequency fingerprint, the difference between different devices can be well represented. Simulation tests were carried out in different SNR environments, and it was confirmed that the radio frequency fingerprint feature can distinguish different LoRa terminal devices under a lower SNR, and has certain anti-noise performance. This paper also studies the access security mechanism of LoRaWAN, combined with LoRa radio frequency fingerprint identification technology, and proposes an optimized LoRaWAN access security mechanism, which improves the access security performance of LoRaWAN.