A Survey on Machine Learning for Space-Air-Ground Integrated Network: Key Technologies and Challenges

In the realm of advanced mobile communications, the integration of space, air, and ground networks, referred to as space-air-ground integrated network (SAGIN), is expected to be an essential ingredient of the sixth generation (6G) mobile communication systems. Moreover, given the increasing significance of artificial intelligence (AI) applications, it is imperative to establish SAGIN with a service-oriented framework that leverages machine learning. Motivated by this fact, in this paper, we introduce the applications of machine learning technologies to address the multifaceted challenges encountered in SAGIN.