This LTE_RFFI project sets up an LTE device radio frequency fingerprint identification system using deep learning techniques. The LTE uplink signals are collected from ten different LTE devices using a USRP N210 in different locations. The sampling rate of the USRP is 25 MHz. The received signal is resampled to 30.72 MHz in Matlab. Then, the signals are processed and saved in the MAT file form. More details about the datasets can be found in the README document.
Please visit https://github.com/eexuanyang/LTE_RFFI to get more details. Please cite the paper ‘LED-RFF: LTE DMRS Based Channel Robust Radio Frequency Fingerprint Identification Scheme’, IEEE Trans. Inf. Forensics Secur. (Under Review), 2023.
Please refer to the attached README documentation or visit https://github.com/eexuanyang/LTE_RFFI for more details.