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Radio Transmitter Identification Based on Collaborative Representation

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Abstract

Benefiting from the correlation among the samples, a method of radio transmitter identification based on collaborative representation is put forward in this paper. Firstly, we extract the square integral bispectra features to characterise the nuances of radio transmitters in the feature space. Secondly, based on collaborative representation, the sparse coefficient is obtained easily. At last, benefiting from the discrimination information of coefficients, a classifier is constructed for the final radio transmitter identification. On the actual collected dataset from ten FM radios which belong to the same model and manufacturer, the robust identification performances verify the effectiveness of our method.

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Acknowledgements

This work is supported by the grants of the National Science Foundation of China, Nos. 61272333, 61171170 and 61473237, the National Defense Foundation of China under Grants Nos. 9140C130502140C13068 and 9140A33030114JB39470, and the Anhui Provincial Natural Science Foundation under Grants Nos. 1308085QF99 and 1408085MF129. The authors would like to thank all the guest editors and anonymous reviewers for their constructive advices.

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Authors and Affiliations

  1. Electronic Engineering Institute, Hefei, 230037, Anhui, China

    Zhe Tang & Ying-Ke Lei

  2. Science and Technology on Communication Information Security Control Laboratory, Jiaxing, 314000, Zhejiang, China

    Zhe Tang & Ying-Ke Lei

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  1. Zhe Tang
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  2. Ying-Ke Lei
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Correspondence to Ying-Ke Lei.

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Tang, Z., Lei, YK. Radio Transmitter Identification Based on Collaborative Representation. Wireless Pers Commun 96, 1377–1391 (2017). https://doi.org/10.1007/s11277-017-4242-z

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