Learning Emergent Random Access Protocol for LEO Satellite Networks

Ju Hyung Lee, Hyowoon Seo, Jihong Park, Mehdi Bennis, Young Chai Ko

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


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 <italic>emergent random access channel protocol (eRACH)</italic>. 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&#x2019;s fairness index.

Original languageEnglish
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Wireless Communications
Publication statusAccepted/In press - 2022


  • 6G
  • Access protocols
  • Computational modeling
  • LEO satellite network
  • Low earth orbit satellites
  • Orbits
  • Satellites
  • Training
  • Wireless communication
  • emergent protocol learning
  • multi-agent deep reinforcement learning
  • random access

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics


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