Autonomous network management for 6G communication: A comprehensive survey

  • Inam Ullah
  • , Ali Arishi
  • , Sushil Kumar Singh
  • , Faisal Alharbi
  • , Anwar Hassan Ibrahim
  • , Muhammad Islam
  • , Yousef Ibrahim Daradkeh
  • , Chang Choi

Research output: Contribution to journalArticlepeer-review

Abstract

The rapid advancement of 6G communication networks presents both considerable problems and opportunities in network management, necessitating sophisticated solutions that extend beyond conventional methods. This study seeks to investigate and evaluate autonomous network management solutions designed for 6G communication networks, highlighting their technical advantages and potential implications. We examine the role of Artificial Intelligence (AI), Machine Learning (ML), and network automation in facilitating self-organization, optimization, and decision-making within critical network domains, including spectrum management, traffic load balancing, fault detection, and security and privacy. We examine the integration of edge computing and Distributed Ledger Technologies (DLT), specifically blockchain, to improve trust, transparency, and security in autonomous networks. This study provides a comprehensive understanding of the technological developments driving fully autonomous, efficient, and resilient 6G network infrastructures by methodically analyzing existing methodologies, identifying significant research gaps, and exploring potential prospects. The results offer significant insights for researchers, engineers, and industry experts involved in the development and deployment of advanced autonomous network management systems.

Original languageEnglish
Pages (from-to)1917-1940
Number of pages24
JournalDigital Communications and Networks
Volume11
Issue number6
DOIs
StatePublished - Dec 2025

Keywords

  • 6G communication
  • AI
  • Autonomous network management
  • Machine learning
  • NFV
  • Networks
  • SDN

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