
Research Article
Joint VBS Association and Resource Allocation for Wireless Network Virtualization-enabled Heterogeneous Integrated Networks
@INPROCEEDINGS{10.4108/eai.13-7-2017.2270670, author={Njai Gibril and Zhangfeng Ma and Mingxue Chen and Rong Chai}, title={Joint VBS Association and Resource Allocation for Wireless Network Virtualization-enabled Heterogeneous Integrated Networks}, proceedings={10th EAI International Conference on Mobile Multimedia Communications}, publisher={EAI}, proceedings_a={MOBIMEDIA}, year={2017}, month={12}, keywords={heterogeneous integrated network vbs association resource allocation energy efficiency}, doi={10.4108/eai.13-7-2017.2270670} }
- Njai Gibril
Zhangfeng Ma
Mingxue Chen
Rong Chai
Year: 2017
Joint VBS Association and Resource Allocation for Wireless Network Virtualization-enabled Heterogeneous Integrated Networks
MOBIMEDIA
EAI
DOI: 10.4108/eai.13-7-2017.2270670
Abstract
In this paper, we consider a heterogeneous integrated net- work scenario where a number of heterogeneous radio access technologies are integrated to offer data transmission service to user equipments (UEs). We assume that wireless network virtualization is applied to the networks and the physical base stations (PBSs) of the access networks are virtualized into a number of virtual base stations (VBSs). We jointly study VBS association and resource allocation problem in the networks. To achieve joint performance optimization of all the UEs within the network, we formulate thejoint VBS association and resource allocation problem as an optimiza- tion problem which aims at achieving the maximumenergy efficiency of the networks. As the formulated optimization problem is aNP hard problem, which cannot be solved di- rectly, we propose a heuristic algorithm, which starts from a complete matching between user pairs and VBSs, and then- for each matching pair, the original power allocation and VB- S association and resource allocation problemcan be trans- formed into resource allocation subproblem and VBS asso- ciation subproblemequivalently. The two subproblems are solved, respectively, through applying Lagrange dual method and the Kuhn-Munkres (K-M) algorithm. Numerical results demonstrate the efficiency of the proposed algorithm.