Collaborative and Incremental Learning for Modulation Classification with Heterogeneous Local Dataset in Cognitive IoT-Reference-Cited by-同舟云学术

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Collaborative and Incremental Learning for Modulation Classification with Heterogeneous Local Dataset in Cognitive IoT

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:

Qi Peihan¹^ORCID,Zhou Xiaoyu¹^ORCID,Ding Yuanlei¹,Zheng Shilian²^ORCID,Jiang Tao³^ORCID,Li Zan¹^ORCID

Affiliation:

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

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

3. School of Cyber Engineering, Xidian University, Xi’an, China

Funder

National Natural Science Foundation for Distinguished Young Scholar

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/7511293/7557027/09810510.pdf?arnumber=9810510

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Vehicular Intelligence at the Edge: A Decentralized Federated Learning Approach for Technology Recognition;2024 IEEE Vehicular Networking Conference (VNC);2024-05-29

2. FedBKD: Heterogenous Federated Learning via Bidirectional Knowledge Distillation for Modulation Classification in IoT-Edge System;IEEE Journal of Selected Topics in Signal Processing;2023-01

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