Auto-tuning in LTE networks using joint RRM optimization

Abstract

Auto-tuning or Self-optimization in mobile networks is under continuous evolution in current era. Self optimization means the process where UE (user equipment) and eNB (enhanced Node B) performance measurements are used to auto-tune the network Radio Resource Management (RRM) parameters (in order to achieve optimal network performance. With the growth in the size and complexity of the mobile wireless networks self-optimization is important, in order to reduce the operational cost of the network. Research on auto-tuning has already been reported for GSM networks. Many contributions on RRM auto-tuning in 3G networks have been reported. Although there were important industrial and academic efforts, auto-tuning was unable to get its place in the UMTS standard. The ambitious targets for the LTE system have given Self Organizing Networks (SON) functionalities a place in the standard including self-configuration, self-optimization and self healing. Different RRM parameters have been used for auto tuning such as Inter-Cell Interference Coordination (ICIC) and load balancing using handover parameter optimization. In this research, we will specially investigate the joint optimization of more than one RRM parameters i.e. Mobility and Inter-Cell Interference Co-ordination (ICIC) to achieve the network optimization objective. It was expected that joint optimization of two RRM parameters will yield better network performance in terms of KPIs (Key Performance Indicators) as compared to the case when single RRM parameters is optimized. The performance of proposed auto tuning algorithm has been evaluated. Simulation results have shown better network performance in terms of KPIs with joint optimization.