LAUSR

In recent years, a new concept of network architecture with control/data plane separation is introduced to the future network, which can effectively improve the mobility robustness and reduce the handover failure by providing the data plane services under the umbrella of a macro cell coverage layer. However, in the ultra dense network, frequent data plane handovers would still introduce huge signaling exchanges and latencies. In this paper, we propose a universal predictive mobility management scheme for urban ultra-dense networks to speed up the data plane handover process. We utilize the probability suffix tree model to save and analyze the transition relationships between small cells in terms of variable markov chains, and pre-configure a cluster of small cells with larger handover probabilities for the users. To accommodate different versions of the users, a compatible network-controlled predictive mobility management procedure and an advanced user-autonomous predictive mobility management procedure are proposed to support the proposed predictive mobility management scheme. The simulation results show that the proposed scheme can significantly improve the prediction accuracy with a lower redundant configuration cost and can effectively speed up the data plane handover process compared with the traditional mobility management.