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Energy Efficiency of Backhauling Options for Future Heterogeneous Networks

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Part of the book series: Green Energy and Technology ((GREEN))

Abstract

Deployment of heterogeneous networks (HetNets) is a veritable solution to the challenges of coverage and capacity in meeting the unprecedented future mobile data traffic. However, the high density of small base stations (SBS) in future HetNets may increase the complexity of backhauling with higher capital expenditure (CAPEX), operating expenditure (OPEX), and energy cost. In this paper, a comprehensive review of various backhauling options for future HetNet is provided. For a HetNet system of seven SBS scenario, the efficiencies of the backhauling technologies are evaluated based on power consumption analysis. The implementation of energy-efficient microwave communication links is also considered based on realistic power consumption. Findings show that massive MIMO (M-MIMO) backhauling system consumes the highest power at maximum load. Power consumption in M-MIMO tends to rise as the number of transmitting antennas increases. In the same vein, power consumption in self-backhauling is relatively high when compared with conventional backhauling systems such as the microwave point-to-point (P2P) and point-to-multipoint (P2MP). On the other hand, total power consumed by satellite hub site, fiber optics, and cloud radio access network (CRAN) technologies are found to be relatively low (271.0571, 96.8083 and 90.1920 W, respectively). Fiber optics, CRAN, satellite hub site, and P2MP backhauling options proved to be more energy efficient in a decreasing order, when coverage and capacity are considered. The contribution of this work will help mobile network operators (MNO) in better decision making toward achieving a sustainable backhauling in future HetNet deployments.

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Correspondence to Nasir Faruk .

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Faruk, N., Abdulkarim, A., Surajudeen-Bakinde, N.T., Popoola, S.I. (2019). Energy Efficiency of Backhauling Options for Future Heterogeneous Networks. In: Herawan, T., Chiroma, H., Abawajy, J. (eds) Advances on Computational Intelligence in Energy. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-69889-2_9

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  • DOI: https://doi.org/10.1007/978-3-319-69889-2_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69888-5

  • Online ISBN: 978-3-319-69889-2

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