Editorial SI on Advances in AI for 6G Networks

被引:0
|
作者
Chergui, Hatim [1 ]
Tourki, Kamel [2 ]
Wu, Jun [3 ]
机构
[1] i2CAT Foundation, Software Networks, Barcelona,08034, Spain
[2] Airbus Defence and Space, Tceaf Digital, Élancourt,78990, France
[3] Shanghai Jiao Tong University, School of Electronic Information and Electrical Engineering, Shanghai,200240, China
来源
IEEE Networking Letters | 2024年 / 6卷 / 04期
关键词
5G mobile communication systems - Reinforcement learning;
D O I
10.1109/LNET.2024.3519937
中图分类号
学科分类号
摘要
The advent of 6G networks heralds a new era of telecommunications characterized by unparalleled connectivity, ultra-low latency, and immersive applications such as holographic communication and Industry 5.0. However, these advancements also introduce significant complexities in network management and service orchestration. This Special Issue of IEEE Networking Letters explores cutting-edge research on Artificial Intelligence (AI)-driven automation techniques designed to address these challenges. The selected works span a diverse array of AI paradigms - ranging from generative AI (GenAI) and reinforcement learning to multi-agent systems and federated learning - showcasing their applications across various 6G technological domains. By highlighting these innovations, this issue aims to provide valuable insights into the pivotal role of AI in shaping the future of 6G networks. © 2019 IEEE.
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页码:215 / 216
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