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Conference paper

Deployment Guidelines for Cloud-RAN in Future Mobile Networks

From

Department of Electrical and Photonics Engineering, Technical University of Denmark1

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

Networks Technology and Service Platforms, Department of Electrical and Photonics Engineering, Technical University of Denmark3

This work identifies and addresses current challenges and shortcomings arising in deployment and expansions of today’s mobile networks, in order to determine the future of the Cloud-Radio Access Network (C-RAN) architecture. C-RAN proposes a three-fold RAN architecture, improving the flexibility, energy efficiency and performance of the RAN.

On the other hand, C-RAN requires a division of the base station functionalities resulting in very high requirements to the interconnecting transport network, the xhaul. C-RAN has been promoted as the network architecture for 5G and future mobile networks; however, it has not yet been adopted by the majority of network operators.

This work studies existing deployment scenarios and evaluates deployment opportunities for green- and brownfield installations in rural, urban, high mobility and latency sensitive areas. The studies are backed up by examinations of real-life network traffic, predicting that in a group of cells covering multiple different areas, C-RAN will improve network resource utilisation by a factor > 2.

The outcome of this work results in a set of concrete deployment guidelines for the introduction of C-RAN in brownfield network installations and future greenfield installations. The deployment guidelines include functional divisions of the RAN, functional placement scenarios and xhaul network requirements.

Language: English
Publisher: IEEE
Year: 2022
Pages: 141-149
Proceedings: 11<sup>th</sup> IEEE International Conference on Cloud Networking
ISBN: 1665486287 , 9781665486286 , 1665486279 and 9781665486279
ISSN: 27715663
Types: Conference paper
DOI: 10.1109/CloudNet55617.2022.9978902
ORCIDs: Larsen, Line M. P. , Christiansen, Henrik L. , Ruepp, Sarah and Berger, Michael S.

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