Radio Frequency Fingerprint Identification Based on Slice Integration Cooperation and Heat Constellation Trace Figure

IEEE Wireless Communications Letters, vol. 11, pp. 543–547

Abstract

Radio frequency fingerprint (RFF) identification is a popular topic in the field of physical layer security. However, machine learning based RFF identification methods require complicated feature extraction manually while deep learning based methods are hard to achieve robust identification performance. To solve these problems, we propose a novel RFF identification method based on heat constellation trace figure (HCTF) and slice integration cooperation (SIC). HCTF is utilized to avoid the manual feature extraction and SIC is adopted to extract more features automatically in RF signals. Experimental results show that our proposed HCTF-SIC identification method can achieve higher accuracy than the existing RFF methods. The identification accuracy achieves 91.07% when SNR$\pmb {=}$0 dB and it is even higher than 99.64% when the SNR$\pmb {\ge }$5 dB.

Authors 6

1. Yang Peng

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

2. Pengfei Liu

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

3. Yu Wang

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

4. Guan Gui

   Nanjing University of Posts and Telecommunications

   Affiliation as printed

   College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing, China

5. Bamidele Adebisi

   Manchester Metropolitan University

   Affiliation as printed

   Department of Engineering, Faculty of Science and Engineering, Manchester Metropolitan University, Manchester, U.K

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