AI-based Self-healing Solutions Applied to Cellular Networks: An Overview
This is an incremental overview article for network management in cellular systems.
The paper provides an overview of machine learning methods, including classical and deep variants, used for self-healing in cellular networks to detect and compensate for cell outages autonomously, aiming to reduce operational costs in 4G, 5G, and emerging 6G networks.
In this article, we provide an overview of machine learning (ML) methods, both classical and deep variants, that are used to implement self-healing for cell outages in cellular networks. Self-healing is a promising approach to network management, which aims to detect and compensate for cell outages in an autonomous way. This technology aims to decrease the expenses associated with the installation and maintenance of existing 4G and 5G, i.e. emerging 6G networks by simplifying operational tasks through its ability to heal itself. We provide an overview of the basic concepts and taxonomy for SON, self-healing, and ML techniques, in network management. Moreover, we review the state-of-the-art in literature for cell outages, with a particular emphasis on ML-based approaches.