LTE_DATASET

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.

本LTE_RFFI项目基于深度学习技术，构建了一套LTE设备射频指纹识别系统。项目通过在不同位置使用USRP N210采集了来自十个不同LTE设备的上行链路信号。USRP的采样率为25 MHz。接收到的信号在Matlab中重采样至30.72 MHz，并以MAT文件格式保存。数据集中包含了相应的处理后的信号。更多关于数据集的详细信息可在README文档中找到。请访问https://github.com/eexuanyang/LTE_RFFI获取更多详情。如需引用，请参考论文《LED-RFF：基于LTE DMRS的信道鲁棒射频指纹识别方案》，IEEE信息取证与安全期刊（待审稿），2023年。