Mobility Prediction Assisted Call Admission Control Model for Mobile Heterogeneous Cellular Network

Abstract

The exponential rise in mobile wireless networks and allied demands has revitalised academia-industries to achieve more efficient and quality of service (QoS) centric communication systems. On the other hand, high pace up surge of mobile communication and internet services have alarmed industries to ensure seamless QoS provision to the mobile user's (MUs) irrespective of geographical locations and movement pattern. However, majority of conventional approaches apply either received signal strength or bandwidth availability to make CAC decision, which seems limited especially under mobile user scenario. In this paper a highly robust mobility prediction assisted (QoS demand centric) handoff management model is developed for call admission control in heterogeneous cellular network. Our proposed method employs Levenberg-Marquardt artificial neural network (LM-ANN)-based mobility prediction, target cell prioritisation and optimal selection for QoS centric CAC decision. Simulation results have shown low handoff and reduced call blocking probability over that makes it suitable for HCNs with constrained network conditions.