Transfer Learning-Based Radio Frequency Fingerprint Identification Using ConvMixer Network

Globecom, pp. 4722–4727

Abstract

Radio frequency fingerprint (RFF) identification is an emerging physical layer security technique, which provokes many promising applications in the internet of things (IoT). However, traditional machine learning-based RFF identification methods rely on complex manual feature extraction, while it is difficult for methods based on deep learning to deal with RFF identification under different channel environments. To solve these problems, we propose three different transfer learning-based RFF identification methods based on ConvMixer network, which is a mixture of different convolutional layers, using pre-trained model in the previous channel environment to assist in training under the new channel environment. Experimental results show that, compared with the previous retraining method, our proposed method reduces the number of training parameters and improves the identification performance at low SNR. Moreover, the proposed method can still have a certain performance guarantee with less training data.

Authors 6

1. Yu Wang

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, NJUPT,Nanjing,China

   College of Telecommunications and Information Engineering, NJUPT, Nanjing, China

2. Heng Dong

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, NJUPT,Nanjing,China

   College of Telecommunications and Information Engineering, NJUPT, Nanjing, China

3. Yang Peng

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, NJUPT,Nanjing,China

   College of Telecommunications and Information Engineering, NJUPT, Nanjing, China

4. Yun Lin

   Harbin Engineering University

   Affiliation as printed

   College of Information and Communication Engineering, Harbin Engineering University,Harbin,China

   College of Information and Communication Engineering, Harbin Engineering University, Harbin, China

5. Guan Gui

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, NJUPT,Nanjing,China

   College of Telecommunications and Information Engineering, NJUPT, Nanjing, China

6. Haris Gacanin Aachen Institute for Communication Technologies and Embedded Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Communication Technologies and Embedded Systems, RWTH Aachen University,Aachen,Germany

   Institute for Communication Technologies and Embedded Systems, RWTH Aachen University, Aachen, Germany