Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation (6G) networks, providing ubiquitous, continuous, and scalable services. Satellites emerge as the primary enabler for NTN, leveraging their extensive coverage, stable orbits, scalability, and adherence to international regulations. However, satellite-based NTN presents unique challenges, including long propagation delay, high Doppler shift, frequent handovers, spectrum sharing complexities, and intricate beam and resource allocation, among others. The integration of NTNs into existing terrestrial networks in 6G introduces a range of novel challenges, including task offloading, network routing, network slicing, and many more. To tackle all these obstacles, this paper proposes Artificial Intelligence (AI) as a promising solution, harnessing its ability to capture intricate correlations among diverse network parameters. We begin by providing a comprehensive background on NTN and AI, highlighting the potential of AI techniques in addressing various NTN challenges. Next, we present an overview of existing works, emphasizing AI as an enabling tool for satellite-based NTN, and explore potential research directions. Furthermore, we discuss ongoing research efforts that aim to enable AI in satellite-based NTN through software-defined implementations, while also discussing the associated challenges. Finally, we conclude by providing insights and recommendations for enabling AI-driven satellite-based NTN in future 6G networks.

翻译：非地面网络（NTN）预计将成为第六代（6G）网络的关键组成部分，提供泛在、连续且可扩展的服务。卫星凭借其广覆盖、稳定轨道、可扩展性及对国际法规的遵循，成为实现非地面网络的主要载体。然而，基于卫星的非地面网络面临独特挑战，包括长传播延迟、高多普勒频移、频繁切换、频谱共享复杂性，以及复杂的波束与资源分配等问题。将非地面网络集成至现有6G地面网络会引发一系列新挑战，涉及任务卸载、网络路由、网络切片等诸多方向。为应对这些障碍，本文提出将人工智能（AI）作为有前景的解决方案，利用其捕捉网络参数间复杂关联的能力。我们首先提供非地面网络与人工智能的全面背景知识，突出AI技术在解决各类非地面网络挑战中的潜力。随后，我们综述现有工作，强调AI作为基于卫星的非地面网络使能工具的作用，并探索潜在研究方向。更进一步，我们讨论通过软件定义实现来推动AI在卫星非地面网络中应用的现有研究努力，同时分析相关挑战。最后，我们总结并提出在6G网络中实现AI驱动卫星非地面网络的见解与建议。