Self-Optimization of LTE Networks Utilizing Celnet Xplorer

: In order to meet demanding performance objectives in Long-Term Evolution (LTE) networks, it is mandatory to implement highly-efficient, autonomic self-optimization and configuration processes. Selfoptimization processes have already been studied in 2G and 3G networks typically with the objective of improving radio coverage and channel capacity. The 3GPP standard for LTE-Self Organization of Networks (SON) gives guidelines on Self Configuration of Physical Cell ID and Neighbor Relation Function and Self Optimization for Mobility Robustness, Load balancing and Inter-Cell Interference Reduction. While these are very important from an optimization perspective of local phenomenon (i.e., eNodeB's interaction with its neighbors), it is also essential to architect control algorithms to optimize the network as a whole. In this paper, we propose Celnet Xplorer based SON architecture that allows detailed analysis of network performance combined with a SON control engine to optimize the LTE network. The network performance data is obtained in two stages. In the first stage, data is gotten from intelligent nonintrusive monitoring of the standard interfaces of the E-UTRAN and EPC coupled with reports from a software client running in the eNodeBs. In the second stage, powerful data analysis is performed on this data, which is then utilized as input for the SON Engine. Use cases involving Tracking Area Optimization, Dynamic Bearer profile reconfiguration and tuning of network wide coverage and capacity parameters are presented.