Artificial Intelligence Techniques for Next-Generation Mega Satellite Networks
Bassel Al Homssi, Kosta Dakic, Ke Wang, Tansu Alpcan, Ben Allen,, Russell Boyce, Sithamparanathan Kandeepan, Akram Al-Hourani, and Walid Saad

TL;DR
This paper explores how artificial intelligence can be applied to manage and optimize next-generation massive satellite networks, addressing their unique dynamic features and integration challenges.
Contribution
It introduces AI techniques tailored for satellite network management, covering forecasting, spectrum sensing, signal detection, and security, with insights into practical implementation.
Findings
AI enables proactive adjustment to dynamic satellite link conditions.
Enhanced spectrum sensing and signal processing through AI techniques.
Frameworks for integrating AI into satellite network infrastructure.
Abstract
Space communications, particularly massive satellite networks, re-emerged as an appealing candidate for next generation networks due to major advances in space launching, electronics, processing power, and miniaturization. However, massive satellite networks rely on numerous underlying and intertwined processes that cannot be truly captured using conventionally used models, due to their dynamic and unique features such as orbital speed, inter-satellite links, short pass time, and satellite footprint, among others. Hence, new approaches are needed to enable the network to proactively adjust to the rapidly varying conditions associated within the link. Artificial intelligence (AI) provides a pathway to capture these processes, analyze their behavior, and model their effect on the network. This article introduces the application of AI techniques for integrated terrestrial satellite…
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Taxonomy
TopicsSatellite Communication Systems
