User Motion Prediction Aided Vertical Handoff In HWNs

People demand for high-speed bandwidth Internet access anytime and anywhere,and this demand has shown unprecedented growth.However,any single network service cannot satisfy people's current demand.Then we proposed heterogeneous network convergence.The key technology to implement heterogeneous network convergence is vertical handover,which can realize real-time,fast,and efficient handover between networks and has important research significance for implementing.Many domestic and foreign scholars have put forward their own solutions to the vertical handover technology in heterogeneous wireless networks,but there is very little research on the vertical handover in denser heterogeneous networks.In addition,most of the existing solutions generally combine the process of handover timing decision with the process of network selection,and the process of network selection is network-centric.To satisfy the demand of vertical handover in denser heterogeneous networks,this dissertation proposes a user motion prediction aided vertical handoff method.This method divides the process of vertical handover into two sub-processes of switching timing decision and network selection,and the corresponding solutions to the problems during the two sub-processes are also provided.Firstly,for the timing decision algorithm based on the received signal intensity,there is a problem that user's high-speed movements cause the frequent handover request by invoking network selection algorithms.Then we propose a handover timing decision algorithm based on user motion prediction.The algorithm is based on the theory of fuzzy logic,and uses the signal intensity,the speed and the direction of movements as parameters,and calculates the degree of handover suitability by estimating the duration of the end user in the network.Then,taking into account the three factors of network,user and terminal,we propose a network selection algorithm based on Qo E for scenarios where the network coverage is dense.In order to improve the accuracy of the network selection and reduce the computational complexity,the network selection algorithm adaptively combines the ranking technology of approximating the ideal solution with the method of gray correlation analysis.The simulation experiments show that the evaluation results of the switching timing,WLAN utilization and unnecessary handover rate are better than algorithms based on the hysteresis decision after selecting the appropriate up switch threshold and down switch threshold.The network selection results of the network selection algorithm are consistent with the application requirements and user preferences.In the scenario with high network coverage density,the accuracy is guaranteed with a lower computational complexity.