The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
무선 신호는 특유의 하드웨어 속성으로 인해 무선 송신기 간에 작은 특성 차이를 보여줍니다. 송신기 결함의 매개변수 추정을 기반으로 하는 새로운 방사성 식별 방법이 이 편지에 제시되어 있습니다. 무선의 지문 특징은 변조기의 불일치와 전력 증폭기의 비선형성에서 추출되며, 새 데이터의 클래스 레이블을 식별하기 위해 지원 벡터 머신 분류기를 훈련하는 데 사용됩니다. 실제 데이터 세트에 대한 실험은 이 방법의 유효성을 보여줍니다.
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
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부
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
부
@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},}
부
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 -