Fault diagnosis is turning out to be an intense challenge due to the increasing complexity of
the emerging cellular networks. The root-cause analysis of coverage-related network …

Diminishing viability of manual fault diagnosis in the increasingly complex emerging cellular
network has motivated research towards artificial intelligence (AI)-based fault diagnosis …

With the rapid development of mobile communication network and intelligent terminal,
network operators have to pay more attention on network operation and maintenance to …

The capability for a network to self heal itself is a promising feature for future cellular
networks. An essential function to achieve self healing is the ability to determine when a …

Handling faults in a running cellular network can impair the performance and dissatisfy the
end users. It is important to design an automatic self-healing procedure to not only detect the …

For enabling automatic deployment and management of cellular networks, the concept of
self-organizing network (SON) was introduced. SON capabilities can enhance network …

Data-driven machine learning is considered a means to address the paramount challenge of
timely fault diagnosis in modern and futuristic ultra-dense and highly complex mobile …

Self-Healing is one of the key important functionalities in self-organizing mobile
communication networks. Despite its importance, self-healing has yet to receive a deserving …

Mobile cellular network operators spend nearly a quarter of their revenue on network
maintenance and management. A significant portion of that budget is spent on resolving …

This paper presents an artificial intelligence enabled self-healing framework for cell outage
detection and compensation in radio access networks. The developed framework consists of …