An Adaptive Handover Trigger Strategy Based On 5G Networks

Fifth-generation(5G)networks,which has been considered as a new direction in the research of future cellular networks.5G control/user(C/U)plane split heterogeneous network may cause more serious handover problems than traditional networks,especially for the intermacrocell handover.In addition,the mobility behavior of mobile node(MN)may also has a negative impact on the accuracy of handover trigger.In this paper,an adaptive handover trigger strategy(AHTS)is proposed to predict the received signal strength indicator(RSSI),to guarantee that handover trigger is accurate and timely when the MN is moving.First,the fast dynamic time warping(FastDTW)algorithm as well as the density-based spatial clustering of applications with noise(DBSCAN)algorithm are used for clustering trajectories to discover the mobility patterns of MN.Secondly,the hidden states is obtained by segmenting the trajectory sets,the observation states is obtained by transforming the trajectories into grid sequences,and a hidden Markov(HMM)model is trained according to the obtained hidden states and observation states.Finally,according to the HMM model which is selected based on the similarity between test trajectory and each cluster center,an adaptive RSSI predication(ARP)algorithm is implemented to predict the values of the RSSI.Simulation results show that compared with the traditional handover strategies,the proposed strategy can effectively ensure that the predicted received signal strength value error is within0.1,and the handover accuracy is effectively guaranteed.In summary,in order to address the handover trigger problem in the process of moving,this paper proposes a handover strategy which can adapt to the mobile behavior of mobile users.This strategy can help the mobile node to choose the best handover trigger time for the 5G network in the process of random mobile,and provide a reference about achieve seamless handover in 5G networks.