Terrestrial networks form the fundamental infrastructure of modern communication systems, serving more than 4 billion users globally. However, terrestrial networks are facing a wide range of challenges, from coverage and reliability to interference and congestion. As the demands of the 6G era are expected to be much higher, it is crucial to address these challenges to ensure a robust and efficient communication infrastructure for the future. To address these problems, Non-terrestrial Network (NTN) has emerged to be a promising solution. NTNs are communication networks that leverage airborne (e.g., unmanned aerial vehicles) and spaceborne vehicles (e.g., satellites) to facilitate ultra-reliable communications and connectivity with high data rates and low latency over expansive regions. This article aims to provide a comprehensive survey on the utilization of network slicing, Artificial Intelligence/Machine Learning (AI/ML), and Open Radio Access Network (ORAN) to address diverse challenges of NTNs from the perspectives of both academia and industry. Particularly, we first provide an in-depth tutorial on NTN and the key enabling technologies including network slicing, AI/ML, and ORAN. Then, we provide a comprehensive survey on how network slicing and AI/ML have been leveraged to overcome the challenges that NTNs are facing. Moreover, we present how ORAN can be utilized for NTNs. Finally, we highlight important challenges, open issues, and future research directions of NTN in the 6G era.

翻译：地面网络构成现代通信系统的基础设施，为全球超过40亿用户提供服务。然而，地面网络正面临从覆盖与可靠性到干扰与拥塞等广泛挑战。由于6G时代的需求预计将大幅提升，解决这些挑战以确保未来通信基础设施的稳健与高效至关重要。为解决这些问题，非地面网络（NTN）已成为一种有前景的解决方案。NTN是利用空中平台（如无人机）和太空平台（如卫星）的通信网络，旨在在大范围区域实现高数据速率、低延迟的超可靠通信与连接。本文旨在从学术界和工业界双重视角，全面综述网络切片、人工智能/机器学习（AI/ML）及开放无线接入网（ORAN）在应对NTN多样化挑战中的应用。具体而言，我们首先对NTN及其关键使能技术（包括网络切片、AI/ML和ORAN）进行深度教程式介绍。继而系统阐述如何利用网络切片与AI/ML克服NTN面临的挑战，并进一步探讨ORAN在NTN中的应用。最后，我们重点总结了NTN在6G时代的重要挑战、未解决问题及未来研究方向。