6G is envisioned to offer higher data rate, improved reliability, ubiquitous AI services, and support massive scale of connected devices. As a consequence, 6G will be much more complex than its predecessors. The growth of the system scale and complexity as well as the coexistence with the legacy networks and the diversified service requirements will inevitably incur huge maintenance cost and efforts for future 6G networks. Network Root Cause Analysis (Net-RCA) plays a critical role in identifying root causes of network faults. In this article, we first give an introduction about the envisioned 6G networks. Next, we discuss the challenges and potential solutions of 6G network operation and management, and comprehensively survey existing RCA methods. Then we propose an artificial intelligence (AI)-empowered Net-RCA framework for 6G. Performance comparisons on both synthetic and real-world network data are carried out to demonstrate that the proposed method outperforms the existing method considerably.

翻译：6G设想提供更高的数据率、更高的可靠性、无处不在的AI服务,并支持大规模连接装置。因此,6G将比其前身复杂得多。系统规模和复杂性的扩大,以及与遗留网络的共存以及多种服务要求的共存将不可避免地为今后的6G网络带来巨大的维护费用和努力。网络根源分析(Net-RCA)在查明网络缺陷的根源方面发挥着关键作用。在本篇文章中,我们首先介绍设想的6G网络。接下来,我们讨论6G网络运行和管理的挑战和潜在解决方案,并全面调查现有的RCA方法。然后,我们提议为6G建立一个人工智能(AI)驱动的网络RCA框架。对合成和现实世界网络数据进行绩效比较,以证明拟议的方法大大优于现有方法。