  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.
