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Green concerns in federated learning over 6G

  • Published:2022-03 Issue:3 Volume:19 Page:50-69
  • ISSN:1673-5447
  • Container-title:China Communications
  • language:
  • Short-container-title:China Commun.

Author:

Zhao Borui1,Cui Qimei1,Liang Shengyuan1,Zhai Jinli1,Hou Yanzhao1,Huang Xueqing2,Pan Miao3,Tao Xiaofeng1

Affiliation:

1. National Engineering Laboratory for Mobile Network Technologies, Beijing University of Posts and Telecommunications, Beijing, 100876, China

2. Department of Computer Science, New York Institute of Technology, Old Westbury, NY, 11568, USA

3. Department of Electrical and Computer Engineering, University of Houston, Houston, TX, 77204, USA

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications

Cited by 9 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. Multi-Layer Collaborative Federated Learning architecture for 6G Open RAN;Wireless Networks;2024-09-05

2. A survey of energy-efficient strategies for federated learning inmobile edge computing;Frontiers of Information Technology & Electronic Engineering;2024-05

3. Green 6G: Energy Awareness in Design;2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS);2024-01-03

4. Distributed Multi-Agent Interference Coordination in Native AI Enabled Multi-Cell Networks for 6G;2023 26th International Symposium on Wireless Personal Multimedia Communications (WPMC);2023-11-19

5. Joint Latency-Oriented, Energy Consumption, and Carbon Emission for a Space–Air–Ground Integrated Network with Newly Designed Power Technology;Electronics;2023-08-22
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