Intelligent SON Coordination in the 5G-and-beyond era

Self-Organizing Networks (SON) was proposed as a concept to improve network management via automating certain operations. The evolution of wireless systems to the fifth generation (5G) and beyond era (B5G) poses demands for a new design approach for SON functions as well as their efficient coordination towards avoiding conflicts and mis-configuration of network resources. Machine Learning (ML) is considered as a key solution for empowering SON platforms in order to configure and optimize 5G and B5G network functions in an automated way so as to achieve full Radio Access Network (RAN) automation. In this sense, we elaborated our previous contribution on a validated SON-coordination scheme towards incorporating ML-capabilities so as to address 5G SON requirements.