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Towards Green and Sustainable AI-Native RAN:From Prediction to Live Testbed Deployment

Chenyuan Feng Shuaishuai Guo Mao Van Ngo Zihan Chen Howard H.Yang Tony Q.S.Quek

通信与信息网络学报（英文）2025，Vol.10Issue(4)：326-339,14.

Towards Green and Sustainable AI-Native RAN:From Prediction to Live Testbed Deployment

Chenyuan Feng ¹Shuaishuai Guo ²Mao Van Ngo ³Zihan Chen ³Howard H.Yang ⁴Tony Q.S.Quek³

作者信息

1. Department of Computer Science,University of Exeter,EX4 4QF Exeter,U.K.
2. School of Control Science and Engineering,Shandong Univer-sity,Jinan 250061,China
3. Singapore University of Technology and Design,Singapore
4. ZJU-UIUC Institute,Zhejiang University,Haining 314400,China
折叠

摘要

关键词

AI-native RAN/non-real-time RIC(Non-RT RIC)/programmable RAN/RAN application(rApp)/energy efficiency

Key words

AI-native RAN/non-real-time RIC(Non-RT RIC)/programmable RAN/RAN application(rApp)/energy efficiency

引用本文复制引用

Chenyuan Feng,Shuaishuai Guo,Mao Van Ngo,Zihan Chen,Howard H.Yang,Tony Q.S.Quek..Towards Green and Sustainable AI-Native RAN:From Prediction to Live Testbed Deployment[J].通信与信息网络学报（英文）,2025,10(4):326-339,14.

基金项目

This work was funded in part by Start-up Funding for the 2025 National High-End Talent Frontier Project(01)with Grant 70012501A01,in part by the National Natural Science Foundation of China under Grant 62301328,by the National Research Foundation,Singapore,and Infocomm Media Development Authority under its Future Communications Research&Development Programme,and in part by the SNS JU project 6G-GOALS un-der the EU's Horizon program Grant Agreement 101139232. （01）

通信与信息网络学报（英文）

ISSN：2096-1081

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