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Conference paper

Energy Consumption Modelling of Next Generation Mobile Crosshaul Networks

In Proceedings of 2021 Ieee Congress on Cybermatics: 14th Ieee International Conferences on Internet of Things, Ithings 2021, 17th Ieee International Conference on Green Computing and Communications, Greencom 2021, 2021 Ieee International Conference on Cyber Physical and Social Computing, Cpscom 2021 and 7th Ieee International Conference on Smart Data, Smartdata 2021 — 2021, pp. 153-160
From

Department of Electrical and Photonics Engineering, Technical University of Denmark1

Networks Technology and Service Platforms, Department of Electrical and Photonics Engineering, Technical University of Denmark2

TDC NET A/S3

Cloud-Radio Access Network (C-RAN) is seen as a key enabler of energy efficient mobile networks, as it limits the energy consumption at the cell site and provides capacity sharing for multiple cells. C-RAN splits the traditional mobile base station's functional composition into three units, connected by a fronthaul and midhaul network, which together with the backhaul network forms the crosshaul network.

This work investigates the crosshaul network energy consumption by the use of network simulations. Network simulations are used to model a realistic user behavior, and provide information about network energy consumption in different scenarios. This work presents results from the simulation of a model implemented by different C-RAN functional compositions.

The simulation results can predict the energy consumption in the crosshaul network under realistic application loads. Results illustrate that when scaling up the network, it is more energy efficient to use a functional composition with much processing before transmission on the cross haul network. Results show a 40 times variation in energy consumption among possible scenarios and thus, this work enlighten the importance of choosing the right functional split.

Language: English
Publisher: IEEE
Year: 2021
Pages: 153-160
Proceedings: 17<sup>th</sup> IEEE International Conference on Green Computing and Communications
ISBN: 1665417625 and 9781665417624
Types: Conference paper
DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData-Cybermatics53846.2021.00036
ORCIDs: Larsen, Line M.P. , Ruepp, Sarah and Berger, Michael S.

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