Distributed AI Platform for the 6G RAN

Fuente: arXiv
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Hauptverfasser: Ananthanarayanan, Ganesh, Balkwill, Matthew, Foukas, Xenofon, Lai, Zhihua, Radunovic, Bozidar, Settle, Connor, Zhang, Yongguang
Format: Preprint
Veröffentlicht: 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