High-Efficient Resource Virtualization Management Technology For Heterogeneous Cellular Network

LTE wireless communication network is widely used in the international areas. The demand of users for mobility and traffic loads increased significantly. As shown from surveys that the majority of wireless services take place indoors, however, the wireless signal was severely obstructed by the building and the quality of services indoors is difficult to be guaranteed. While the investigation and development of Home-Node Bs is a good solution to solve the problem of poor indoor coverage and weakness signal, which can satisfy the users' communication requirements. In recent years, Home-Node Bs has developed fast and become occupying the market due to its features of low volume and low cost.Due to the random deployment of small cells, the network topology is changing randomly. Interferences management in heterogeneous network becomes more complex, especially when the base stations of every cell use the static spectrum allocation scheme to manage their own traffic loads respectively. In order to satisfy users' traffic demand, all the base stations may increase their transmission power by themselves without cooperation, which will lead to severe interference among each base station and great energy consumption. The dynamic spectrum management is too local to optimize resource. It is emergent to adopt novel resource management approaches to deal with these problems. In recent years, resource virtualization has been proposed as an effective resource management scheme to optimize network throughput and energy efficiency performance and decrease the interference in a more dynamic fashion.Actually, resource virtualization is considered as a more agile mode to make the mobile network providers manage the physical resource in a global way. This paper presents a joint time-frequency-power resource virtualization mapping and management scheme for heterogeneous cellular networks. The overall scheme involves the following two major processes: firstly, to virtualize wireless resources as logical resources in clouds; secondly, to carry out logical resource allocation and optimization in a global way for the sake of energy efficiency increasement and solidify the logical resources into the actual physical resources for resource allocation. As a result, the resources are of high efficient utilization, at the same time, the rate requirement of each user is guaranteed. From the perspective of energy saving, we propose a resource virtualization mapping and optimization scheme to solve the problem of the great energy consumption in current network. The simulation results show that the aforementioned goals of the proposed scheme have been achieved.