Adaptive SON management using KPI measurements

Self-Organising Network (SON) represent an approach to automate dedicated tasks for Operation, Administration and Maintenance (OAM) in mobile radio networks. With SON management, a multitude of simultaneously operating SON function closed control loops can be configured according to network context specific and weighted targets (objectives) for Key Performance Indicators (KPIs) by using different input models. These are the operator-defined Context and Objective Model, and the SON vendor provided SON Function Model (SFM). This SON management approach enables the SON system to work optimally regarding the achievement of the defined KPI targets. However, in current approaches, the vendor provided SFMs are static and don't adapt to the actual network environment. This may lead to non-optimal operation of the SON system and hence to non-optimal network performance. In this paper an approach is introduced to make SFMs adaptive to the actual network environment. By analysing KPI measurements from the network and creating a Network Measurement Pool (NMP), the actual influence of the current SON function configuration on the network performance is determined, and the SFMs are enhanced in such way that the contribution of the corresponding SON functions towards achieving the technical objectives is improved. The approach is evaluated using a realistic network scenario including more than 200 cells and about 5000 users.