Learning Emergent Random Access Protocol for LEO Satellite Networks

A mega-constellation of low-altitude earth orbit (LEO) satellites (SATs) are envisaged to provide a global coverage SAT network in beyond fifth-generation (5G) cellular systems. LEO SAT networks exhibit extremely long link distances of many users under time-varying SAT network topology. This makes e...

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Bibliographic Details
Published in:IEEE transactions on wireless communications 2023-01, Vol.22 (1), p.257-269
Main Authors: Lee, Ju-Hyung, Seo, Hyowoon, Park, Jihong, Bennis, Mehdi, Ko, Young-Chai
Format: Article
Language:English
Subjects:
Access protocols
Cellular communication
Computational modeling
Deep learning
emergent protocol learning
LEO satellite network
Low altitude
Low earth orbit satellites
Low earth orbits
Machine learning
multi-agent deep reinforcement learning
Multiagent systems
Network topologies
Orbits
Protocol
Random access
Satellite constellations
Satellite networks
Satellites
Training
Wireless communication
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Summary:A mega-constellation of low-altitude earth orbit (LEO) satellites (SATs) are envisaged to provide a global coverage SAT network in beyond fifth-generation (5G) cellular systems. LEO SAT networks exhibit extremely long link distances of many users under time-varying SAT network topology. This makes existing multiple access protocols, such as random access channel (RACH) based cellular protocol designed for fixed terrestrial network topology, ill-suited. To overcome this issue, in this paper, we propose a novel contention-based random access solution for LEO SAT networks, dubbed emergent random access channel protocol (eRACH). In stark contrast to existing model-based and standardized protocols, eRACH is a model-free approach that emerges through interaction with the non-stationary network environment, using multi-agent deep reinforcement learning (MADRL). Furthermore, by exploiting known SAT orbiting patterns, eRACH does not require central coordination or additional communication across users, while training convergence is stabilized through the regular orbiting patterns. Compared to RACH, we show from various simulations that our proposed eRACH yields 54.6% higher average network throughput with around two times lower average access delay while achieving 0.989 Jain's fairness index.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2022.3192365