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.
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References
Kalil, M., Shami, A., Ye, Y.: Wireless resources virtualization in LTE systems. In: Proceedings of IEEE INFOCOM Workshops 2014, Toronto, Ontario, Canada, pp. 363–368, April 2014
Kamel, M.I., Le, L.B., Girard, A.: LTE wireless network virtualization: dynamic slicing via flexible scheduling. In: Proceedings of IEEE VTC Fall 2014, Vancouver, British Columbia, Canada, pp. 1–5, September 2014
Kamel, M.I., Le, L.B., Girard, A.: LTE multi-cell dynamic resource allocation for wireless network virtualization. In: Proceedings of IEEE WCNC 2015, New Orleans, Louisiana, USA, pp. 966–971, March 2015
Kokku, R., Mahindra, R., Zhang, H., Rangarajan, S.: NVS: a substrate for virtualizing wireless resources in cellular networks. IEEE/ACM Trans. Netw. 20(5), 1333–1346 (2012)
Parsaeefard, S., Jumba, V., Derakhshani, M., Le-Ngoc, T.: Joint resource provisioning and admission control in wireless virtualized networks. In: Proceedings of IEEE WCNC 2015, New Orleans, Louisiana, USA, pp. 2020–2025, March 2015
Liu, G., Yu, F.R., Ji, H., Leung, V.C.M.: Distributed resource allocation in virtualized full-duplex relaying networks. IEEE Trans. Veh. Technol. 65(10), 8444–8460 (2016)
Palomar, D.P., Chiang, M.: A tutorial on decomposition methods for network utility maximization. IEEE J. Sel. Areas Commun. 24(8), 1439–1451 (2006)
Yu, W., Lui, R.: Dual methods for nonconvex spectrum optimization of multicarrier systems. IEEE Trans. Commun. 54(7), 1310–1322 (2006)
Palomar, D.P., Chiang, M.: Alternative decompositions for distributed maximization of network utility: framework and applications. In: Proceedings of IEEE INFOCOM 2006, Barcelona, Spain, pp. 1–13, April 2006
Zou, J., Xi, Q., Zhang, Q., He, C., Jiang, L., Ding, J.: QoS-aware energy-efficient radio resource allocation in heterogeneous wireless networks. In: Proceedings of IEEE ICCW 2015, London, UK, pp. 2781–2786, June 2015
Acknowledgement
The authors would like to thank DOCOMO Beijing Communications Laboratories Co., Ltd. for their support in this work. This work was supported in part by the National High Technology Research and Development Program (863 Program) of China under Grant No. 2014AA01A707.
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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Chen, L., Hu, C., Li, Y., Wang, W. (2018). A Utility-Based Resource Allocation in Virtualized Cloud Radio Access Network. In: Long, K., Leung, V., Zhang, H., Feng, Z., Li, Y., Zhang, Z. (eds) 5G for Future Wireless Networks. 5GWN 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-319-72823-0_28
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DOI: https://doi.org/10.1007/978-3-319-72823-0_28
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