Research On Lte Mobile Terminal Identification Based On Radio Frequency Fingerprint

Nowadays,Long-Term Evolution(LTE)has been widely deployed all over the world.It occupies a leading position in the global mobile communication market.Though LTE has encryption and higher-level protocol based security mechanisms,its physical layer is still subject to attacks.Radio frequency fingerprint(RFF)identification technique has drawn great attention to wireless terminal authentication.RFF-based LTE terminal identifications can prevent the potential impersonation or denial of service(Do S)attacks in the physical layer.In this thesis,differential constellation trace figure(DCTF)is extracted from the random access preamble of the physical random access channel(PRACH).The scheme for LTE terminal identification and authentication is proposed.The proposed scheme is evaluated in the hardware experimental system consisting of the LTE e Node B implemented on the software-defined radio(SDR)platform and LTE mobile phones.The main work of this thesis is as follows:1)An RFF extraction method based on DCTF of random access preamble in PRACH is proposed according to the distribution of LTE uplink physical channel and the details of random access process.The DCTF generation mechanism of LTE preamble signal is deduced theoretically,and the stability of DCTF characteristics of different preambles under the same root sequence is studied.According to the expression degree difference between the transient and modulation parts of LTE preamble signal on DCTF,an idea of extracting the DCTF characteristics considering transient and modulation parts separately is proposed.2)A scheme for LTE terminal identification and authentication based on multi-channel convolutional neural network(MCCNN)is proposed according to the idea of segmented DCTF extraction.Experimental results show that that the classification accuracy can reach 98.96%for six LTE phones at the SNR level of 30 d B with the line-of-sight(LOS)scenarios.More specifically,the classification accuracy can reach 96.01% for six LTE phones of the same model.When six legal mobile phones are known,the equal error rate(EER)of authenticating four unknown illegal mobile phones of the same model as the legal mobile phones is 8.74%.3)A linear dimensionality reduction scheme for LTE terminal identification and authentication based on principal components analysis(PCA)combined linear discriminant analysis(LDA)is proposed.Experimental results show that that the classification accuracy can reach98.72% for six LTE phones at the SNR level of 30 d B with the LOS scenarios.When six legal mobile phones are known,the EER of authenticating four unknown illegal mobile phones of the same model as the legal mobile phones is 8.16%.4)A complete set of LTE mobile terminal identification and authentication system combining software and hardware is designed.The experimental platform is built and the feasibility of the proposed scheme is verified.The effects of different channel environments on the identification performance of the proposed scheme are analyzed.It is proved that the two proposed LTE mobile terminal identification schemes have long-term stability.