Incorporating Mobility Prediction in Handover Procedure for Frequent-Handover Mitigation in Small-Cell Networks

Abstract

Small cells are deployed in high-density environments to provide additional capacity and improve network coverage, supporting high-speed, high-quality mobile broadband services. However, the deployment of small cells increases the impact of user mobility on handover performance. Trends in the different movements of users at the edge of small cells lead to an excessive number of unnecessary handovers. Since user mobility is not purely random, and the overlapping coverage areas of small cells are very limited, handover management in small cells is direction-dependent. This paper proposes a handover algorithm incorporating user mobility information into the handover procedure to mitigate frequent handovers in a small-cell network. The proposed algorithm observes the pattern in the reference signal received power (RSRP) of a candidate target cell during the time to trigger to detect the change in the users' movements. Based on the RSRP pattern, the algorithm makes an optimal handover decision by selecting a target cell in the user's path. The proposed algorithm does not require information on users' previous movements because A3 event-based measurement reporting tracks user mobility. Via simulations, we show that the proposed algorithm reduces the number of handovers without sacrificing the network throughput in different network environments and performs satisfactorily in high-shadowing environments.