构建分布式AI平台，支撑6G无线接入网智能演进
Distributed AI Platform for the 6G RAN
- 提出专为6G RAN设计的分布式AI架构
- 解决现有AI方案在部署与扩展上的不足
- 适合研究6G智能网络的工程师与学者
蜂窝无线接入网（RAN）正快速向6G演进，以降低运营成本并为运营商和企业创造新收入。在此背景下，人工智能成为解决跨管理与应用领域复杂问题的关键使能技术。然而，尽管AI潜力巨大，实际部署仍面临诸多挑战，阻碍其在RAN中的广泛应用。本文分析了这些挑战，指出现有方法难以实现真正的AI原生6G网络愿景。为此，我们提出一种面向AI原生RAN的分布式AI平台架构，以应对未来6G网络的需求。
原文摘要 · Abstract (English)
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.
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