Technique for Cross-layer Vertical Handover Prediction in 4G Wireless Networks

With the increasing deployment of a variety of wireless access networks, wireless devices face the challenge of selecting the most suitable network from a set of available access networks. Some of the weighty issues in 4G wireless networks are fastness and seamlessness in handover process. This paper therefore, proposes a handover technique based on movement prediction in wireless mobile (WiMAX and LTE - Advanced) environment. The technique enables the system to predict signal quality between the mobile User Equipment (UE) and eNodeB stations/access points (APs) in two different networks. Prediction is achieved using dynamic regressive integrated moving average (DRIMA) model by keeping track of the signal strength of mobile users. With the help of the prediction, layer-3 handover activities are able to occur prior to layer-2 handover, and therefore, total handover latency can be reduced. This demonstrates that the proposed method predicts the future signal level accurately and reduces the total handover latency.