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Radio frequency fingerprint identification method based on sample multi-view learning

A technology of radio frequency fingerprint and identification method, which is applied in the field of radio frequency fingerprint identification based on multi-view learning, can solve the problems of easy cracking of keys and invalid protection mechanism, and achieves high identification accuracy, high data feature extraction efficiency and high identification performance. strong effect

Pending Publication Date: 2022-03-22
GUILIN UNIV OF ELECTRONIC TECH
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AI Technical Summary

Problems solved by technology

In the foreseeable future, when quantum computing matures, the key will be easily cracked, and the protection mechanism will be invalid

Method used

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  • Radio frequency fingerprint identification method based on sample multi-view learning
  • Radio frequency fingerprint identification method based on sample multi-view learning
  • Radio frequency fingerprint identification method based on sample multi-view learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0060] refer to figure 1 , a radio frequency fingerprint identification method based on sample multi-view learning, different from the prior art, includes the following steps:

[0061] 1) Collect the signal of the device to be identified: collect the band-pass signal of each transmitter to be identified, set the time sequence of the band-pass signal as s(n), and perform down-conversion processing to convert it into a complex baseband time sequence Among them, the in-phase In-Phase component x(n) and the quadrature Quadrature component y(n) are expressed as formula (1):

[0062]

[0063] In formula (1) is the Hilbert transform of the signal s(n), f 0 is the carrier frequency of the signal;

[0064] 2) Data processing and adding noise: the data collected in step 1) is used for energy normalization processing, and then the awgn function of MATLAB software is used to manually add Gaussian white noise with different signal-to-noise ratios and save them separately;

[0065]...

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PUM

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Abstract

The invention discloses a radio frequency fingerprint identification method based on multi-view learning. The radio frequency fingerprint identification method is characterized by comprising the following steps: 1) acquiring a radio frequency signal of each wireless device to be identified; 2) processing data and adding noise; 3) segmenting the data and making a data set I, a data set II and a data set III; 4) designing a complex numerical neural network sub-assembly and constructing a complex numerical neural network; 5) building a sub-neural network I; 6) building a two-dimensional convolutional neural network II and a two-dimensional convolutional neural network III; according to the method, sample data can be utilized, a computer can automatically extract signal fingerprint features, the requirement for the number of samples is lowered, meanwhile, the recognition precision at the low signal-to-noise ratio can be improved, the data feature extraction efficiency is high, and the recognition precision is high.

Description

technical field [0001] The invention relates to the technical field of wireless communication physical layer security, in particular to a radio frequency fingerprint identification method based on multi-view learning. Background technique [0002] With the development of wireless local area network (WLAN) and mobile communication technologies, a large number of wireless communication devices such as routers, Internet of Things devices, certification and control of civilian rotor drones, and the identification of fake communication base station signals that appear constantly, etc., these With the development of wireless communication, equipment security and information security issues have been paid more and more attention. Most wireless local area network protocols have security risks, and a single fraudulent illegal device or hacked device mixed into the system may endanger the security of the entire network. At present, the authentication method of WLAN mainly adopts the ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F2218/08G06F2218/12G06F18/2415G06F18/253
Inventor 谢跃雷邓涵方许强肖潇曾浩南梁文斌王胜谢星丽蒋俊正欧阳缮
Owner GUILIN UNIV OF ELECTRONIC TECH
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