Zeng, Y, Al-Quzweeni, A, Elgorashi, TEH et al. (1 more author) (2019) Energy Efficient virtualization framework for 5G F-RAN. In: Proceedings of the 21st International Conference on Transparent Optical Networks (ICTON 2019). 21st International Conference on Transparent Optical Networks (ICTON 2019), 09-13 Jul 2019, Angers, France. IEEE ISBN 9781728127798
Abstract
Fog radio access network (F-RAN) and virtualisation are promising technologies for 5G networks. In F-RAN, the fog and cloud computing are integrated where the conventional C-RAN functions are diverged to the edge devices of radio access networks. F-RAN is adopted to mitigate the burden of front-haul and improve the end to end (E2E) latency. On other hand, virtualization and network function virtualization (NFV) are IT techniques that aim to convert the functions from hardware to software based functions. Many merits could be brought by the employment of NFV in mobile networks including a high degree of reliability, flexibility and energy efficiency. In this paper, a virtualization framework is introduced for F-RAN to improve the energy efficiency in 5G networks. In this framework, a gigabit passive optical network (GPON) is leveraged as a backbone network for the proposed F-RAN architecture where it connects several evolved nodes B (eNodeBs) via fibre cables. The energy-efficiency of the proposed F-RAN architecture has been investigated and compared with the conventional C-RAN architecture in two different scenarios using mixed integer linear programming (MILP) models. The MILP results indicate that on average a 30% power saving can be achieved by the F-RAN architecture compared with the C-RAN architecture.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | ©2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Funding Information: | Funder Grant number EPSRC EP/H040536/1 EPSRC EP/K016873/1 EPSRC EP/S016570/1 EPSRC EP/K503836/1 EPSRC EP/R511717/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 09 May 2019 12:46 |
Last Modified: | 29 Oct 2019 15:57 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/ICTON.2019.8840170 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:145832 |