The application provides a LoRa device
radio frequency fingerprint identification method and device based on a conditional
diffusion model, and the method comprises the following steps: acquiring
radio frequency signals of different LoRa devices; pre-
processing the
radio frequency signals to obtain a training
data set; constructing a conditional
diffusion model, and training the conditional
diffusion model by using the training
data set; in the training process, introducing
Rayleigh fading multiplicative interference and additive
Gaussian noise to simulate the multipath
fading characteristics of real LoRa device communication; generating a radio frequency
fading signal by using the trained conditional diffusion model, and adding the generated radio frequency
fading signal to the training
data set to obtain an enhanced data set; training a pre-constructed radio frequency
fingerprint identification model by using the enhanced data set; and identifying the radio frequency fading
signal of a LoRa device to be identified by using the trained radio frequency
fingerprint identification model, so as to obtain the category corresponding to the LoRa device to be identified; thereby improving the device identification accuracy under a multipath channel.