Mobility Load Balancing with Handover Minimization for 5G Small Cell Networks

Mobility load balancing (MLB) in small cell networks transfers the load from an overloaded small cell to under-loaded neighbouring small cells by adjusting the mobility parameters. Consequently, a greater number of handovers is required. This is one of the costs for the MLB operation that may affect the network performance severely. Furthermore, frequent handovers may occur if the handed over user equipment (UE) is moving fast across the small cell network. The traditional MLB considers only the edge-UEs (Edge-UEs) for the offloading process. In this paper, we presented a Utility-based Mobility Load Balancing algorithm with Handover minimization (UMLB-HO) by considering not only the edge-UEs but also the non-edge- UEs for overloaded small cells. The overloaded cells determine the fast-moving non-edge-UEs and transfer them to the underloaded Macrocell. Moreover, the small cells determine the fast-, slow or very slow-moving edge-UEs during the MLB and transfer them to either under loaded neighbour small cell or Macrocell. Four terms are defined to determine whether the UE is fast-, slow or very slow-moving to determine the best handover decisions for each UE. Simulation results show that the proposed UMLB-HO algorithm has the minimum number of handovers for a minimum standard deviation with an enhanced level of throughput.