5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings

Research Article

A Utility-Based Resource Allocation in Virtualized Cloud Radio Access Network

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  • @INPROCEEDINGS{10.1007/978-3-319-72823-0_28,
        author={Linna Chen and Chunjing Hu and Yong Li and Wenbo Wang},
        title={A Utility-Based Resource Allocation in Virtualized Cloud Radio Access Network},
        proceedings={5G for Future Wireless Networks. First International Conference, 5GWN 2017, Beijing, China, April 21-23, 2017, Proceedings},
        proceedings_a={5GWN},
        year={2018},
        month={1},
        keywords={Network slicing Virtualization Utility Trade-off},
        doi={10.1007/978-3-319-72823-0_28}
    }
    
  • Linna Chen
    Chunjing Hu
    Yong Li
    Wenbo Wang
    Year: 2018
    A Utility-Based Resource Allocation in Virtualized Cloud Radio Access Network
    5GWN
    Springer
    DOI: 10.1007/978-3-319-72823-0_28
Linna Chen1,*, Chunjing Hu1, Yong Li1, Wenbo Wang1
  • 1: Beijing University of Posts and Telecommunications
*Contact email: chenlinna@bupt.edu.cn

Abstract

Network slicing is an emerging paradigm for 5G networks. Network slices are considered as different and independent virtualized end-to-end networks on a common physical infrastructure. Wireless resource virtualization is the key enabler to achieve high resource efficiency and meanwhile to isolate network slices from one another. In this paper, we propose a slice-specific utility-based resource allocation scheme in cloud radio access networks, where two sets of slices with different requirements are supported simultaneously. Every slice can determine its preference factor in utility function considering the trade-off between bandwidth gain and energy consumption. The objective is to maximize the sum utility of all slices taking the trade-off of all slices into account, which can be formulated as a mixed binary integer nonlinear programming problem. The Lagrange dual method is applied to solve the joint optimization problem. Finally, The performance of the proposed scheme is evaluated and the results show that the proposed scheme can meet different customized requirements of all slices, and enhance system performance when compared with other methods.