arXiv:2605.21395cs.AIcs.LG2026-05KDD

6G将用AI原生架构实现自愈自优,告别人工运维

Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G

  • 用基础模型+多智能体系统统一管理网络
  • 支持边缘设备的轻量化部署与自主修复
  • 适合研究智能通信与未来网络架构者

新兴应用如自动驾驶和沉浸式体验对蜂窝网络提出更高要求,不仅需要更快的速度,更需具备根本性的韧性和自治能力。本文提出一种蓝海愿景:人工智能将被原生融入6G,实现从‘为AI服务的网络’到‘为网络服务的AI’的范式转变。与5G中分散、临时训练的单一任务模型不同,6G时代的原生AI将以基础模型为核心,通过协作式多智能体系统进行编排,将网络管理视为统一的多模态、多任务优化问题。基于此愿景,本文提出两大变革方向:一是构建6G基础模型作为统一骨干,将特定任务知识蒸馏为适配多样边缘部署的轻量模型;二是发展能自主诊断、维护与恢复网络的多智能体系统,实现最小人工干预。这些方向勾勒出6G向智能、自维持通信基础设施演进的路线图。

原文摘要 · Abstract (English)

The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster, but fundamentally more resilient and autonomous. This paper presents a BlueSky vision on how Artificial Intelligence will be natively integrated into 6G, shifting the paradigm from \underline{Network for AI} to \underline{AI for Network}. We envision that, unlike 5G's reliance on scattered, ad-hoc models each trained for a single task, native AI in the 6G era will be anchored by a foundation model and and orchestrated via collaborative multi-agent systems, framing network management as a unified, multi-modal, multi-task optimization problem. Built on this vision, we outline two transformative directions. The first focuses on developing a 6G foundation model as a unified backbone, with task-specific knowledge distilled into compact models suited for diverse edge deployments. The second advances multi-agent systems designed to autonomously diagnose, maintain, and recover networks with minimal human intervention. These directions chart a roadmap for 6G to evolve into an intelligent, self-sustaining communication infrastructure.

6GAI原生多智能体自愈网络

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