LTE_DATASET

Citation Author(s):
Xuan
Yang
Southeast University
Submitted by:
Xuan Yang
Last updated:
Mon, 10/30/2023 - 11:59
DOI:
10.21227/2var-7p97
Data Format:
**.mat
License:
Creative Commons Attribution
312 Views
Categories:
Artificial Intelligence
Signal Processing
IoT
Security
Keywords:
LTE, Radio Frequency Fingerprint Identification, Deep Learning
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Abstract 

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 and is saved in the MAT file form. The corresponding processed signals are included in the dataset. 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.

Instructions: 

Please refer to the attached README documentation or visit https://github.com/eexuanyang/LTE_RFFI for more details.

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