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Energy-Efficient Cloud Radio Access Networks by Cloud Based Workload Consolidation for 5G
Sigwele, Tshiamo Alam, Atm S. Pillai, Prashant Hu, Yim Fun
Sigwele, Tshiamo
Alam, Atm S.
Pillai, Prashant
Hu, Yim Fun
Publication Date
2017-01-15
End of Embargo
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© 2017 Elsevier. Reproduced in accordance with the publisher's self-archiving policy. This manuscript version is made available under the CC-BY-NC-ND 4.0 license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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Yes
Open Access status
openAccess
Accepted for publication
2016-11-07
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Abstract
Next-generation cellular systems like fth generation (5G) is are expected to experience tremendous tra c growth. To accommodate such tra c demand, there is a need to increase the network capacity that eventually requires the
deployment of more base stations (BSs). Nevertheless, BSs are very expensive and consume a lot of energy. With growing complexity of signal processing, baseband units are now consuming a signi cant amount of energy.
As a result, cloud radio access networks (C-RAN) have been proposed as anenergy e cient (EE) architecture that leverages cloud computing technology where baseband processing is performed in the cloud. This paper proposes an energy reduction technique based on baseband workload consolidation using virtualized general purpose processors (GPPs) in the cloud. The rationale for the cloud based workload consolidation technique model is to switch o idle
baseband units (BBUs) to reduce the overall network energy consumption. The power consumption model for C-RAN is also formulated with considering radio side, fronthaul and BS cloud power consumption. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution (LTE) RAN system. The proposed scheme saves up to 80% of energy during low tra c periods and 12% during peak tra c periods compared to baseline LTE system. Moreover, the proposed scheme saves 38% of energy compared to the baseline system on a daily average.
Version
Accepted manuscript
Citation
Sigwele T, Alam AS, Pillai P and Hu YF (2017) Energy-efficient cloud radio access networks by cloud based workload consolidation for 5G. Journal of Network and Computer Applications. 78: 1-8.
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Article