Radio Frequency Fingerprint Collaborative Intelligent Blind Identification for Green Radios-Reference-Cited by-同舟云学术

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Radio Frequency Fingerprint Collaborative Intelligent Blind Identification for Green Radios

Published:2022 Issue: Volume: Page:1-1
ISSN:2473-2400
Container-title:IEEE Transactions on Green Communications and Networking
language:
Short-container-title:IEEE Trans. on Green Commun. Netw.

Author:

Liu Mingqian¹^ORCID,Liu Chunheng¹,Chen Yunfei²^ORCID,Yan Zhiwen¹,Zhao Nan³^ORCID

Affiliation:

1. State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, China

2. School of Engineering, University of Warwick, Coventry, U.K.

3. School of Information and Communication Engineering, Dalian University of Technology, Dalian, P. R. China

Funder

National Natural Science Foundation of China

Aeronautical Science Foundation of China

Higher Education Discipline Innovation Project

Fundamental Research Funds for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Renewable Energy, Sustainability and the Environment

Link

http://xplorestaging.ieee.org/ielx7/7511293/7557027/09802686.pdf?arnumber=9802686

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1. Mitigating Receiver Impact on Radio Frequency Fingerprint Identification via Domain Adaptation;IEEE Internet of Things Journal;2024-07-01

2. Adversarial Attack and Defense on Deep Learning for Air Transportation Communication Jamming;IEEE Transactions on Intelligent Transportation Systems;2024-01

3. Spatial Distribution Feature Extraction Network for Open Set Recognition of Electromagnetic Signal;Computer Modeling in Engineering & Sciences;2024

4. Dynamic Adaptation RFF Identification Method Leveraging Cognitive Representation Learning;IEEE Transactions on Information Forensics and Security;2024

5. Modulation recognition with frequency offset and phase offset over multipath channels;China Communications;2023-10

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