Artificial Intelligence for Satellite Communication: A Review

TL;DR

This paper reviews how artificial intelligence techniques are applied to satellite communication systems, addressing challenges and exploring future research directions for improved network management and security.

Contribution

It provides a comprehensive overview of AI applications in satellite communication, highlighting recent algorithms, challenges, and potential solutions.

Findings

AI enhances beam-hopping and anti-jamming techniques

AI improves network traffic forecasting and spectrum management

AI offers promising solutions for energy efficiency and security in satellite networks

Abstract

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.