标题： 面向人工智能原生无线接入网：6G第一天标准化的运营商视角 显示英文标题

标题： Towards AI-Native RAN: An Operator's Perspective of 6G Day 1 Standardization

摘要： 人工智能/机器学习（AI/ML）已成为6G移动网络最确定和显著的特征。 与5G不同，其中AI/ML并未原生集成，而是作为现有架构上的附加功能，6G将在一开始就整合AI，以应对其复杂性并支持无处不在的AI应用。 基于我们从2G到5G的广泛移动网络运营和标准化经验，本文探讨了6G AI原生无线接入网络（RAN）的设计和标准化原则，特别关注其关键的Day 1架构、功能和能力。 我们研究了AI原生RAN的框架，并提出了其三个基本能力，以阐明标准化方向；即，由AI驱动的RAN处理/优化/自动化、可靠的AI生命周期管理（LCM）以及AI即服务（AIaaS）供应。 AI原生RAN的标准化，特别是Day 1特性，包括AI原生6G RAN架构，已被提出。 为了验证，已构建了一个包含超过5000个5G-A基站的大规模现场试验，并通过所提出的架构和支持的AI功能，在平均空中接口延迟、根本原因识别和网络能耗方面取得了显著改进。 本文旨在为6G AI原生RAN的标准化设计提供一个Day 1框架，在技术创新与实际部署之间取得平衡。 显示英文摘要

摘要： Artificial Intelligence/Machine Learning (AI/ML) has become the most certain and prominent feature of 6G mobile networks. Unlike 5G, where AI/ML was not natively integrated but rather an add-on feature over existing architecture, 6G shall incorporate AI from the onset to address its complexity and support ubiquitous AI applications. Based on our extensive mobile network operation and standardization experience from 2G to 5G, this paper explores the design and standardization principles of AI-Native radio access networks (RAN) for 6G, with a particular focus on its critical Day 1 architecture, functionalities and capabilities. We investigate the framework of AI-Native RAN and present its three essential capabilities to shed some light on the standardization direction; namely, AI-driven RAN processing/optimization/automation, reliable AI lifecycle management (LCM), and AI-as-a-Service (AIaaS) provisioning. The standardization of AI-Native RAN, in particular the Day 1 features, including an AI-Native 6G RAN architecture, were proposed. For validation, a large-scale field trial with over 5000 5G-A base stations have been built and delivered significant improvements in average air interface latency, root cause identification, and network energy consumption with the proposed architecture and the supporting AI functions. This paper aims to provide a Day 1 framework for 6G AI-Native RAN standardization design, balancing technical innovation with practical deployment.