Self-Healing in Emerging Cellular Networks: Review, Challenges, and Research Directions

Abstract

Mobile cellular network operators spend nearly a quarter of their revenue on network management and maintenance. Incidentally, a significant proportion of that budget is spent on resolving outages that degrade or disrupt cellular services. Historically, operators mainly rely on human expertise to identify, diagnose, and resolve such outages. However, with growing cell density and diversifying cell types, this approach is becoming less and less viable, both technically and financially. To cope with this problem, research on self-healing solutions has gained significant momentum in recent years. Self-healing solutions either assist in resolving these outages or carry out the task autonomously without human intervention, thus reducing costs while improving mobile cellular network reliability. However, despite their growing popularity, to this date no survey has been undertaken for self-healing solutions in mobile cellular networks. This paper aims to bridge this gap by providing a comprehensive survey of self-healing solutions proposed in the domain of mobile cellular networks, along with an analysis of the techniques and methodologies employed in those solutions. This paper begins by providing a quantitative analysis to highlight why in emerging mobile cellular network self-healing will become a necessity instead of a luxury. Building on this motivation, this paper provides a review and taxonomy of existing literature on self-healing. Challenges and prospective research directions for developing self-healing solutions for emerging and future mobile cellular networks are also discussed in detail. Particularly, we identify that the most demanding challenges from self-healing perspective are the difficulty of meeting 5G low latency and the high quality of experience requirement.