Overview of Using Signaling Data from Radio Interface with Machine Learning Approaches

Mobile networks technologies are evolving rapidly in parallel with smart mobile devices wide spreading. On other hand, utilization of Artificial Intelligence in mobile networks has been increasing widely. It starts from mobile phones applications to mobile network operations, planning, optimization, etc. In this paper, an overview of using signalling data from radio interface in cooperation with machine learning techniques is introduced. The main machine learning types and models are summarized, as well as some of previous related works mainly depended on applying Machine learning on radio signalling. Benefits of those Machine learning-Signaling combinations vary from enhancing network key performance indicators to predicting user's specifications as trajectory, location, work, gender, etc. Moreover, mobile network planning, coverage evaluation, path loss prediction and channel modeling can be enhanced by using machine learning.