Position-prediction-based motion classification assisted strategy in mobility management

Handover and access network selection are two important issues for mobility management in future heterogeneous networks. Current solutions for these two mechanisms are not very efficient because they do not consider motion scenarios, and cannot predict next location for mobile node in motion. In our paper, we proposed a motion classification assisted strategy (MCAS) based on global positioning system. Making use of information such as location coordinates and moving velocity, MCAS can predict the next location where MN will move to, and classify different motion scenarios. MCAS will assist existing handover mechanism and ANS strategy to make more reasonable decision, and achieve better performance.