LoRa_RFFI_dataset

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. 本LoRa-RFFI项目构建了一套基于深度学习技术的LoRa射频指纹识别（Radio Frequency Fingerprint Identification, RFFI）系统。该数据集的射频信号采集自60台商用现货LoRa设备，数据包前导码与设备标签均已提供。本数据集共包含19个子数据集，所有子数据集的详细采集设置请参阅README文档。更多相关细节可访问：https://github.com/gxhen/LoRa_RFFI。引用该研究工作时，请遵循2022年发表于《IEEE信息取证与安全汇刊（TIFS）》的论文《面向LoRa的可扩展且信道鲁棒射频指纹识别》。

搜集汇总

背景与挑战

背景概述

LoRa_RFFI_dataset是一个用于射频指纹识别的数据集，包含60个商用LoRa设备的RF信号，分为19个子数据集。该数据集支持基于深度学习的设备认证研究，适用于物联网和安全领域的应用。