This LoRa-RFFI project builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techniques. The RF signals are collected from 60 commercial-off-the-shelf LoRa devices. The packet preamble part and device labels are provided. The dataset consists of 19 sub-datasets and please refer to the README document for more detailed collection settings for all the sub-datasets.
More details are available at https://github.com/gxhen/LoRa_RFFI. Please cite the paper 'Towards Scalable and Channel-Robust Radio Frequency Fingerprint Identification for LoRa', IEEE Trans. Inf. Forensics Security (TIFS), 2022.
Please refer to the README documentation or https://github.com/gxhen/LoRa_RFFI.