Clustering Techniques Applied to Profile Creation on 5G Radio Access Networks Datasets
Clustering Techniques; 5G Radio Access Networks; Performance Management.
The Internet arising and the Information and Communication Technologies development expanded the volume and diversification of data sources, thus opening up new opportunities in the industry and academic fields for Machine Learning Techiniques and Big Data related applications. In the same perspective is the extensive amount of data generated by mobile networks infrastructures worldwide. The Radio Access Networks (RAN), crucial for the telecommunications infrastructure, work as a really important layer for the wireless communications and produce a significant data volume due to the network counters measurements which stand as the enablers for the monitoring and visibility on network performance indicators and service quality. The present work consists of applying clustering algorithms to create profiles on datasets related to 5G Radio Access Network Indicators regarding traffic, volume and channel quality so the labeled data can get used on classification problems and as a support tool for identifying improvements, performance management and operational efficiency of Radio Access Networks.