Distributed AI Platform for the 6G RAN
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arXiv
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| Format: | Preprint |
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2024
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| author | Ananthanarayanan, Ganesh Balkwill, Matthew Foukas, Xenofon Lai, Zhihua Radunovic, Bozidar Settle, Connor Zhang, Yongguang |
| author_facet | Ananthanarayanan, Ganesh Balkwill, Matthew Foukas, Xenofon Lai, Zhihua Radunovic, Bozidar Settle, Connor Zhang, Yongguang |
| contents | Cellular Radio Access Networks (RANs) are rapidly evolving towards 6G, driven by the need to reduce costs and introduce new revenue streams for operators and enterprises. In this context, AI emerges as a key enabler in solving complex RAN problems spanning both the management and application domains. Unfortunately, and despite the undeniable promise of AI, several practical challenges still remain, hindering the widespread adoption of AI applications in the RAN space. In this work, we attempt to shed light to these challenges and argue that existing approaches in addressing them are inadequate for realizing the vision of a truly AI-native 6G network. We propose a distributed AI platform architecture, tailored to the needs of an AI-native RAN. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_03747 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Distributed AI Platform for the 6G RAN Ananthanarayanan, Ganesh Balkwill, Matthew Foukas, Xenofon Lai, Zhihua Radunovic, Bozidar Settle, Connor Zhang, Yongguang Networking and Internet Architecture Artificial Intelligence Cellular Radio Access Networks (RANs) are rapidly evolving towards 6G, driven by the need to reduce costs and introduce new revenue streams for operators and enterprises. In this context, AI emerges as a key enabler in solving complex RAN problems spanning both the management and application domains. Unfortunately, and despite the undeniable promise of AI, several practical challenges still remain, hindering the widespread adoption of AI applications in the RAN space. In this work, we attempt to shed light to these challenges and argue that existing approaches in addressing them are inadequate for realizing the vision of a truly AI-native 6G network. We propose a distributed AI platform architecture, tailored to the needs of an AI-native RAN. |
| title | Distributed AI Platform for the 6G RAN |
| topic | Networking and Internet Architecture Artificial Intelligence |
| url | https://arxiv.org/abs/2410.03747 |