Improving Vertical Handoffs Using Mobility Prediction

The recent advances in wireless communications require integration of multiple network technologies in order to satisfy the increasing demand of mobile users. Mobility in such a heterogeneous environment entails that users keep moving between the coverage regions of different networks, which means that a non-trivial vertical handoff scheme is required in order to maintain a seamless transition from one network technology to another. A good vertical handoff scheme must provide the users with the best possible connection while keeping connection dropping probability to the minimum. In this paper, we propose a handoff scheme which employs the Markov model to predict the users’ future locations in order to make better handoff decisions with reduced connection dropping probability and number of unnecessary handoffs. Through simulation, the proposed scheme is compared with the SINR-based scheme, which was shown to outperform other vertical handoff schemes. The experiments show that the proposed scheme achieves significant improvements over the SINR-based scheme that can reach 51% in terms of the number of failed handoffs and 44% in terms of the number of handoffs. Keywords—Heterogeneous wireless networks, Vertical handoff, Markov model, Artificial intelligence, Mobility management.