Exploiting UAV for Air–Ground Integrated Federated Learning: A Joint UAV Location and Resource Optimization Approach-Reference-Cited by-同舟云学术

Exploiting UAV for Air–Ground Integrated Federated Learning: A Joint UAV Location and Resource Optimization Approach

Published:2023-09 Issue:3 Volume:7 Page:1420-1433
ISSN:2473-2400
Container-title:IEEE Transactions on Green Communications and Networking
language:
Short-container-title:IEEE Trans. on Green Commun. Netw.

Author:

Jing Yuqian¹^ORCID,Qu Yuben¹^ORCID,Dong Chao¹^ORCID,Ren Weiqing¹,Shen Yun¹^ORCID,Wu Qihui¹,Guo Song²^ORCID

Affiliation:

1. Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology and the College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China

2. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

Funder

Jiangsu Provincial Key Research and Development Program

National Natural Science Foundation of China

Hong Kong RGC Research Impact Fund

General Research Fund

Shenzhen Science and Technology Innovation Commission

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

http://xplorestaging.ieee.org/ielx7/7511293/10224556/10039717.pdf?arnumber=10039717

Reference57 articles.

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2. The Regression of MNIST Dataset Based on Convolutional Neural Network

3. HFEL: Joint Edge Association and Resource Allocation for Cost-Efficient Hierarchical Federated Edge Learning

4. Hybrid Quantum Network for classification of finance and MNIST data

5. Energy-Efficient Radio Resource Allocation for Federated Edge Learning

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