Distributed AI Platform for the 6G RAN

• URL: http://arxiv.org/abs/2410.03747v1
• Date: Tue, 1 Oct 2024 18:35:25 GMT
• Title: Distributed AI Platform for the 6G RAN
• Authors: Ganesh Ananthanarayanan, Xenofon Foukas, Bozidar Radunovic, Yongguang Zhang,
• Abstract summary: AI emerges as a key enabler in solving complex RAN problems. Existing approaches in addressing these challenges are inadequate for realizing the vision of a truly AI-native 6G network. Motivated by this lack of solutions, it proposes a generic distributed AI platform architecture.
• Score: 3.1924413019103692
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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. This article attempts to shed light to these challenges and argues that existing approaches in addressing them are inadequate for realizing the vision of a truly AI-native 6G network. Motivated by this lack of solutions, it proposes a generic distributed AI platform architecture, tailored to the needs of an AI-native RAN and discusses its alignment with ongoing standardization efforts.

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