Research On Mobility Management In Heterogeneous Cellular Networks

In order to meet the requirement of faster data rates and higher coverate quality in the development of wireless communicaition, some key LTE-Advanced techniques launched by Third Generation Partnership Project(3GPP) have been investigated intensely, such as Carrier Aggregation(CA), Coordinated Multipoint Transmission and Reception(CoMP), Relay and Heterogeneous Cellular Networks(HCN). Among all these techniques, HCN could improve system capacity as well as coverage efficiency by deploying additional small cellular base stations under the coverage area of traditional macro cellular network.Mobility, as an important indicator of user experience, is the main research area of HCN. Due to the change of network architecture, the types and complexity of handover increase, causing a large amount of handover signal overheads and unnecessary handovers. At the same time, the mobility and random distribution of users intensify the load imbalancing, which reduce the resource utilization of system.In this paper, on the issue of mobility management, the concept and key technologies of HCN are introduced in the first place and the research status of handover and mobility load balancing algorithms is analyzed and summarized. After that, the asymmetrical handover algorithm and mobility load balancing scheme based on cell priority are proposed. Then the two algorithms are verified by system level simulation.In the matter of heterogeneous cellular handover, an asymmetrical handover algorithm is proposed in this paper, which adopts the asymmetrical design between different types of cells, and then carries out handover by setting the handover activity. System simulation results show that the proposed scheme improves system performance in terms of decreasing Ping-Pong effects and maximizing resources utilization. In the matter of mobility load balancing, considering the impact of different users’ mobile speed and cell coverage radius of HCN, we define a handover tolerance as the indicator of cell selection algorithm. And the allocation mechanism of overlapping cells is deployed to overcome potential Ping-Pong problem. Simulation results show that the proposed MLB scheme has better performance than the original MLB scheme in the aspect of system throughput and the numbers of unsatisfied users.