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Recent Advances in Machine Learning for Network Automation in the O-RAN.

Mutasem Q Hamdan1, Haeyoung Lee2, Dionysia Triantafyllopoulou3

  • 1Samsung Electronics R&D Institute, Staines TW18 4QE, UK.

Sensors (Basel, Switzerland)
|November 14, 2023
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Summary
This summary is machine-generated.

Machine learning (ML) is key to automating Open Radio Access Networks (O-RAN). This survey explores ML applications, challenges, and opportunities for intelligent, automated O-RAN management.

Keywords:
artificial intelligencemachine learningopen radio access networks

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Area of Science:

  • Telecommunications Engineering
  • Computer Science
  • Artificial Intelligence

Background:

  • The telecommunications industry is shifting towards open and intelligent network architectures.
  • Open Radio Access Network (O-RAN) architecture offers disaggregation and virtualization for multi-vendor interoperability.
  • Managing and automating the complex O-RAN ecosystem poses significant challenges.

Purpose of the Study:

  • To provide a comprehensive survey of current research on network automation using Machine Learning (ML) in O-RAN.
  • To highlight the need for automation within the O-RAN architecture.
  • To explore O-RAN's support for ML techniques and identify research opportunities.

Main Methods:

  • Overview of the O-RAN architecture and its components.
  • Analysis of O-RAN's inherent support for ML techniques.
  • Exploration of challenges in applying ML for O-RAN automation.
  • Review of existing research on ML algorithms and frameworks for O-RAN automation.

Main Results:

  • Identified ML as a promising solution for automating complex O-RAN environments.
  • Detailed current research efforts, including ML algorithms and frameworks applied to O-RAN.
  • Highlighted key challenges and opportunities for ML-driven network automation in O-RAN.

Conclusions:

  • ML techniques are crucial for addressing the complexities of O-RAN network automation.
  • The survey provides a roadmap for future research in leveraging ML for intelligent O-RAN management.
  • Further research can unlock significant benefits by applying ML to various aspects of O-RAN.