Research On Resource Allocation Algorithm Based On Wireless Resource Virtualization For Femtocell Networks

As long as LTE is widely used in the international arena as well as the popularity of a variety of intelligent terminals, users’ demand for mobile services increased significantly. Survey data shows that majority of voice and data services take place indoors. However, the wireless signal severely attenuated due to the building so that the quality of services indoors is difficult to be guaranteed. Femtocell can provide well indoor coverage for users’ high Qo S requirements. With the development in recent years, Femtocell has become a hot technology because of its features of low power, low cost and good indoor coverage.However, along with the system gain Femtocell also brings a number of technical challenges. Dou to the random deployment model, large-scale introduction of Femtocell make the existing network topology changed greatly. Interference environments become more complex following the challenges of network optimization. It is emergent to adopt a new resource allocation strategy to deal with these problems, otherwise the overall performance of the network may not increase or even worse than traditional cellular network. Therefore, the effective management of wireless resource to optimize network performance is very important. At the same time, research on the Wireless Resource Virtualization gradually appears in researchers’ vision, due to its characteristics of enabling the overall optimization and on-demand allocation of resource.This paper firstly analyzes the interference existing in Femtocell network. On this basis, an resource allocation algorithm is proposed based on Wireless Resource Virtualization. As the perspective of mapping, unified management and allocation, we map wireless resource so that the wireless resource can be subdivided into virtual wireless resource and managed centrally. Finally base stations allocate the actual spectrum resource according to the allocation results of the virtual resource. The proposed algorithm compromises spectrum reuse and spectrum interference well, also accomplishes the overall optimization and on-demand allocation of resource.Simulation results show that the proposed algorithm can effectively deal with interference in network and tidal effects of traffic caused by uneven distribution in spatial and temporal of service requirements, improve the performance of network successfully.