Mobile stations KPI before and after RET optimization

The dataset is intended to cover core issues pertaining to the area of a traffic optimization via RET motors inside the antenna on the mobile base station system (BSS). The principle of RET operation was already known to scientists; however, the use of a machine learning and big data provides the possibility of creation an autonomous system, which control RET system. The goal of the proposed research is to establish a new base to automatically remotely control RET for the BSS, by means of using machine learning, that as result permit to increase average speed in downlink for 1 user equipment (UE). As for the functionality, it focuses on the following three aspects: firstly, upload KPI from the main station (where occurs the change electrical angle) and from her neighboring, secondly, upload records after changing electrical angel, finally, collated records establish basis for new research and combined in one table. However, the proposed dataset contains records only LTE. The obtained results will serve as a basis for future works in the traffic optimization by dint of RET, insofar as the decreasing electrical tilt of antenna, we reduce serving are BSS, reduce the number of UE's and eventually increase average speed in DL for 1 UE's.