IEICE TRANSACTIONS on Fundamentals
Radiometric Identification Based on Parameters Estimation of Transmitter Imperfections
Summary :
Radio signals show small characteristic differences between radio transmitters resulted from their idiosyncratic hardware properties. Based on the parameters estimation of transmitter imperfections, a novel radiometric identification method is presented in this letter. The fingerprint features of the radio are extracted from the mismatches of the modulator and the nonlinearity of the power amplifier, and used to train a support vector machine classifier to identify the class label of a new data. Experiments on real data sets demonstrate the validation of this method.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E103-A No.2 pp.563-566
- Publication Date
- 2020/02/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.2019EAL2084
- Type of Manuscript
- LETTER
- Category
- Communication Theory and Signals
Authors
You Zhu LI
Sichuan University,Sichuan Normal University
Yong Qiang JIA
the Southwest Electronics and Telecommunication Technology Research Institute
Hong Shu LIAO
University of Electronic Science and Technology of China
Keyword
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You Zhu LI, Yong Qiang JIA, Hong Shu LIAO, "Radiometric Identification Based on Parameters Estimation of Transmitter Imperfections" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 2, pp. 563-566, February 2020, doi: 10.1587/transfun.2019EAL2084.
Abstract: Radio signals show small characteristic differences between radio transmitters resulted from their idiosyncratic hardware properties. Based on the parameters estimation of transmitter imperfections, a novel radiometric identification method is presented in this letter. The fingerprint features of the radio are extracted from the mismatches of the modulator and the nonlinearity of the power amplifier, and used to train a support vector machine classifier to identify the class label of a new data. Experiments on real data sets demonstrate the validation of this method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019EAL2084/_p
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@ARTICLE{e103-a_2_563,
author={You Zhu LI, Yong Qiang JIA, Hong Shu LIAO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Radiometric Identification Based on Parameters Estimation of Transmitter Imperfections},
year={2020},
volume={E103-A},
number={2},
pages={563-566},
abstract={Radio signals show small characteristic differences between radio transmitters resulted from their idiosyncratic hardware properties. Based on the parameters estimation of transmitter imperfections, a novel radiometric identification method is presented in this letter. The fingerprint features of the radio are extracted from the mismatches of the modulator and the nonlinearity of the power amplifier, and used to train a support vector machine classifier to identify the class label of a new data. Experiments on real data sets demonstrate the validation of this method.},
keywords={},
doi={10.1587/transfun.2019EAL2084},
ISSN={1745-1337},
month={February},}
Copy
TY - JOUR
TI - Radiometric Identification Based on Parameters Estimation of Transmitter Imperfections
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 563
EP - 566
AU - You Zhu LI
AU - Yong Qiang JIA
AU - Hong Shu LIAO
PY - 2020
DO - 10.1587/transfun.2019EAL2084
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 2
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - February 2020
AB - Radio signals show small characteristic differences between radio transmitters resulted from their idiosyncratic hardware properties. Based on the parameters estimation of transmitter imperfections, a novel radiometric identification method is presented in this letter. The fingerprint features of the radio are extracted from the mismatches of the modulator and the nonlinearity of the power amplifier, and used to train a support vector machine classifier to identify the class label of a new data. Experiments on real data sets demonstrate the validation of this method.
ER -
English
