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Artificial Intelligence--Based Data Path Control in LEO Satellites--Driven Optical Communications
  • Andrea Wrona,
  • Andrea Tantucci
Andrea Wrona
Universita degli Studi di Roma La Sapienza Dipartimento di Ingegneria informatica automatica e gestionale

Corresponding Author:wrona@diag.uniroma1.it

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Andrea Tantucci
Universita degli Studi di Roma La Sapienza Dipartimento di Ingegneria informatica automatica e gestionale
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Abstract

Free Space Optical Communication has emerged as a promising technology for high-speed and secure data transmission between ground stations on Earth and orbiting satellites. However, this communication technology suffers from signal attenuation due to atmospheric turbulence and beam alignment precision. Low Earth Orbit satellites play a pivotal role in optical communication due to their low altitude over the Earth surface, which mitigates the atmospheric precipitation effects. This paper introduces a novel data path control law for satellite optical communication exploiting Artificial Intelligence-based predictive weather forecasting and a node selection mechanism based on Reinforcement Learning. Extensive simulations on three case studies demonstrate that the proposed control technique achieves remarkable gains in terms of link availability with respect to other state-of-the-art solutions.
16 Oct 2023Submitted to International Journal of Satellite Communications and Networking
16 Oct 2023Submission Checks Completed
16 Oct 2023Assigned to Editor
19 Oct 2023Reviewer(s) Assigned
09 May 20241st Revision Received
10 May 2024Submission Checks Completed
10 May 2024Assigned to Editor