The pressure to achieve greater data rates from limited radio spectrum while reducing
latency in 5G and soon 6G has resulted in the introduction of new and complex features into …

This paper surveys the literature relating to the application of machine learning to fault
management in cellular networks from an operational perspective. We summarise the main …

Cellular networks are one of the most impactful technologies of today's ICT industry. They
provide wireless access to internet and services with very high availability and effectiveness …

The mobile telecommunication industry has experienced a very rapid growth in the recent
past. This has resulted in significant technological and architectural evolution in the wireless …

Machine learning and deep learning algorithms have the potential to revolutionize network
data analytics in 5G cellular networks. With the increase in the number of connected devices …

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 …

In complex radio environments like cellular mobile networks, the quality of the radio channel
strongly affects the service quality experienced by users. Degraded channel quality makes …

As the complexity of commercial cellular networks grows, there is an increasing need for
automated methods detecting and diagnosing cells not only in complete outage but with …

Maintaining and managing ever more complex telecommunication networks is an
increasingly difficult task, which often challenges the capabilities of human experts. There is …

The management and troubleshooting of faults in mobile radio networks are challenging as
the complexity of radio networks is increasing. A proactive approach to system failures is …