Markov Chain based Predictive Model for Efficient handover Management in Vehicle-to-Infrastructure Communications

The vehicular ad-hoc networks (VANET) has attracted the attention of both the industry and the academia researcher over the last decade. The concept of connecting vehicles to the Internet using the already deployed cellular network architecture has opened many avenues for research and development that are contributing significantly towards the Intelligent Transportation Systems (ITS). Almost every vehicle requires a seamless connectivity to the Internet without interruption. However, with the emergence of the 5G network and the Vehicle-to-infrastructure(V2I) concept, the design of efficient mobility management techniques that can handle the real-world mobility constraints in VANET becomes a critical task. In this paper, we propose a new handover algorithm that uses a Markov chain predictor to determine when and where a handover will be needed. The aim of the proposed solution is to reduce the number of unnecessary handover by maintaining the vehicle connectivity to the 5G base station as long as possible without degrading the network performance. Simulation studies were conducted to evaluate the performance of the proposed scheme. Our results show that the proposed handover algorithm greatly outperforms the conventional 3GPP handover algorithms.