Optimal Forwarding Probability for Vehicular Location Prediction Handover Algorithm

Existing wireless networks aim to provide communication service between vehicle by enabling the vehicular networks to support wide range applications for enhancing the efficiency of road transportation. As the vehicle moves between the different cell with higher speed than the regular mobile node, a handover process is needed to change its point of attachment to the predicted next cell. When a vehicle moves, the path loss and shadow fading contribute to the large scale variation of reference symbols received quality (RSRQ), especially in an urban area where small cells are located. Since traditional handover decision based on RSRQ induce the ping-pong effect, it is a pressing need to develop an intelligent approach to predict the handover decision process, thus yielding seamless handovers. This paper proposes a Vehicular Location Prediction Handover Algorithm (VLPHA) approach to predict the handover decision and utilize the optimization method by using optimal forwarding probability. The vehicle location and target cell RSRQ are considered as inputs to the handover algorithm to predict the handover decision, hence switching to the best preferable access point. The VLPHA approach has implemented in NS-3 to find the best optimal forwarding probability value. The result shows that the proposed method able to reduce the number of unnecessary handovers as well as ping-pong effect from 35% to 0%.