Managing mobility in wireless cellular networks: A profile based approach

The mobile user equipment profile establishment is critical to achieve effective mobility management mechanisms in the rapidly expanding mobile networks. The management of profiles for mobile user equipment induces a network overhead in maintenance. To overcome this drawback an Adaptive Resonance Theory Based Mobile User Equipment Profile Predictability Framework for mobility management is introduced in this paper. The framework proposed is capable of both service prediction and location estimation of the mobile terminals considered in the cellular network. The cell location estimation is simplified by the introduction of a geographical clustering technique. A neural network based on the Generalized Adaptive Resonance Theory is used to achieve service predictions in the proposed framework. The proposed framework is compared with the existing ISI-41/ GSM-MAP mobility management techniques. The simulation results discussed prove the effectiveness of the proposed mobility management framework.