  Satellite communication offers the prospect of service continuity over
uncovered and under-covered areas, service ubiquity, and service scalability.
However, several challenges must first be addressed to realize these benefits,
as the resource management, network control, network security, spectrum
management, and energy usage of satellite networks are more challenging than
that of terrestrial networks. Meanwhile, artificial intelligence (AI),
including machine learning, deep learning, and reinforcement learning, has been
steadily growing as a research field and has shown successful results in
diverse applications, including wireless communication. In particular, the
application of AI to a wide variety of satellite communication aspects have
demonstrated excellent potential, including beam-hopping, anti-jamming, network
traffic forecasting, channel modeling, telemetry mining, ionospheric
scintillation detecting, interference managing, remote sensing, behavior
modeling, space-air-ground integrating, and energy managing. This work thus
provides a general overview of AI, its diverse sub-fields, and its
state-of-the-art algorithms. Several challenges facing diverse aspects of
satellite communication systems are then discussed, and their proposed and
potential AI-based solutions are presented. Finally, an outlook of field is
drawn, and future steps are suggested.
