Optimal Access Points Selection Based on Mobility Prediction in Heterogeneous Small Cell Networks

Abstract

While increasing access points(APs) densification is considered as a useful solution to cater for the explosive growth of throughput demands, its impact on the handover needs to be carefully handled. In order to reduce unnecessary handover and improve the users’ experience, this paper proposes an optimal AP selection algorithm for the mobile user based on mobility prediction. According to the historical data of the mobile user, we use a semi-Markov model with finite conditions to predict the user’s next possible location. Then, according to the user’s demand for network resources, the most suitable AP is selected based on the proposed optimization model in the expected location. The proposed handover scheme selects the best AP connectivity, by skipping handover of some APs along the moving trajectory. Simulation results show that the proposed scheme achieves a better performance compared with existing schemes in terms of the prediction accuracy.