Parameter Optimization for LTE Handover Using an Advanced SOM Algorithm

A novel approach to enhance the robustness of handovers in LTE femtocells is presented. A modified Self Organizing Map is used to allow femtocells to learn about their specific indoor environment including the locations that have prompted handover requests. Optimized handover parameter values are then used that are specific to these locations. This approach reduces both the number of handover failures and the occurrence of ping-pong handovers. It also improves network efficiency by reducing the signaling overhead. The application of machine learning to this task complies with the plug-and-play functionality that is a requirement of Self Organizing Networks in LTE systems.