Handoff Algorithm Based on Location Prediction in Ultra-dense Heterogeneous Wireless Network

Abstract

In the ultra-dense heterogeneous wireless network composed of heterogeneous cellular networks and wireless local area networks, vehicle terminals with variable speeds will face more frequent handovers, resulting in the deterioration of user’s Quality of Service (QoS). For the above problems, firstly, the Gauss Markov mobility model is used to predict the position of the vehicle terminal at the next moment, and the candidate network set that meets the terminal service quality is selected to make the intersection with the current candidate network set. Secondly, if the current access network is not in the intersection, the variable-step firefly algorithm is used to find the best network. Thirdly, the terminal that fails to switch due to the prediction error is migrated to the macro cellular to ensure the continuity of communication. Simulation results show that the proposed algorithm can reduce the frequent handoff phenomenon, such as ping pong handoff in the ultra-dense heterogeneous wireless network. Meanwhile, it can improve the user service quality and network throughput.