Wireless and Satellite Systems. 8th International Conference, WiSATS 2016, Cardiff, UK, September 19-20, 2016, Proceedings

Research Article

On the Energy Minimization of Heterogeneous Cloud Radio Access Networks

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  • @INPROCEEDINGS{10.1007/978-3-319-53850-1_22,
        author={Tshiamo Sigwele and Atm Alam and Prashant Pillai and Yim Hu},
        title={On the Energy Minimization of Heterogeneous Cloud Radio Access Networks},
        proceedings={Wireless and Satellite Systems. 8th International Conference, WiSATS 2016, Cardiff, UK, September 19-20, 2016, Proceedings},
        proceedings_a={WISATS},
        year={2017},
        month={6},
        keywords={Base station sleep Bin packing Cloud computing C-RAN Energy efficiency HetNets Virtualization},
        doi={10.1007/978-3-319-53850-1_22}
    }
    
  • Tshiamo Sigwele
    Atm Alam
    Prashant Pillai
    Yim Hu
    Year: 2017
    On the Energy Minimization of Heterogeneous Cloud Radio Access Networks
    WISATS
    Springer
    DOI: 10.1007/978-3-319-53850-1_22
Tshiamo Sigwele1,*, Atm Alam1,*, Prashant Pillai1,*, Yim Hu1,*
  • 1: University of Bradford
*Contact email: t.sigwele@bradford.ac.uk, a.s.alam5@bradford.ac.uk, p.pillai@bradford.ac.uk, y.f.hu@bradford.ac.uk

Abstract

Next-generation 5G networks is the future of information networks and it will experience a tremendous growth in traffic. To meet such traffic demands, there is a necessity to increase the network capacity, which requires the deployment of ultra dense heterogeneous base stations (BSs). Nevertheless, BSs are very expensive and consume a significant amount of energy. Meanwhile, cloud radio access networks (C-RAN) has been proposed as an energy-efficient architecture that leverages the cloud computing technology where baseband processing is performed in the cloud. In addition, the BS sleeping is considered as a promising solution to conserving the network energy. This paper integrates the cloud technology and the BS sleeping approach. It also proposes an energy-efficient scheme for reducing energy consumption by switching off remote radio heads (RRHs) and idle BBUs using a greedy and first fit decreasing (FFD) bin packing algorithms, respectively. The number of RRHs and BBUs are minimized by matching the right amount of baseband computing load with traffic load. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution advanced (LTE-A) system.