TY - JOUR
T1 - Autonomous network management for 6G communication
T2 - A comprehensive survey
AU - Ullah, Inam
AU - Arishi, Ali
AU - Singh, Sushil Kumar
AU - Alharbi, Faisal
AU - Ibrahim, Anwar Hassan
AU - Islam, Muhammad
AU - Daradkeh, Yousef Ibrahim
AU - Choi, Chang
N1 - Publisher Copyright:
© 2025 Chongqing University of Posts and Telecommunications.
PY - 2025/12
Y1 - 2025/12
N2 - 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.
AB - 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.
KW - 6G communication
KW - AI
KW - Autonomous network management
KW - Machine learning
KW - NFV
KW - Networks
KW - SDN
UR - https://www.scopus.com/pages/publications/105025353880
U2 - 10.1016/j.dcan.2025.07.001
DO - 10.1016/j.dcan.2025.07.001
M3 - Article
AN - SCOPUS:105025353880
SN - 2468-5925
VL - 11
SP - 1917
EP - 1940
JO - Digital Communications and Networks
JF - Digital Communications and Networks
IS - 6
ER -