Towards a Cloud-Native Radio Access Network

Nikaein, Navid; Schiller, Eryk Jerzy; Favraud, Romain; Knopp, Raymond; Alyafawi, Islam Fayez Abd; Braun, Torsten (2016). Towards a Cloud-Native Radio Access Network. In: Mavromoustakis, Constandinos X.; Mastorakis, George; Dobre, Ciprian (eds.) Advances in Mobile Cloud Computing and Big Data in the 5G Era. Studies in Big Data: Vol. 22 (pp. 171-202). Springer International Publishing 10.1007/978-3-319-45145-9_8

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Commoditization and virtualization of wireless networks are changing the economics of mobile networks to help network providers, e.g. Mobile Network Operator (MNO), Mobile Virtual Network Operator (MVNO), move from proprietary and bespoke hardware and software platforms towards an open, cost-effective, and flexible cellular ecosystem. In addition, rich and innovative local services can be efficiently materialized through cloudification by leveraging the existing infrastructure. In this work, we present a Radio Access Network as a Service (RANaaS), in which a Cloudified Centralized Radio Access Network (C-RAN) is delivered as a service. RANaaS describes the service life-cycle of an on-demand, elastic, and pay as you go RAN instantiated on top of the cloud infrastructure. Due to short deadlines in many examples of RAN, the fluctuations of processing time, introduced by the virtualization framework, have a deep impact on the C-RAN performance. While in typical cloud environments, the deadlines of processing time cannot be guaranteed, the cloudification of C-RAN, in which signal processing runs on general purpose processors inside Virtual Machines (VMs), is a challenging subject. We describe an example of real-time cloudified LTE network deployment using the OpenAirInterface (OAI) LTE implementation and OpenStack running on commodity hardware. We also show the flexibility and performance of the platform developed. Finally, we draw general conclusions on the RANaaS provisioning problem in future 5G networks.

Item Type:

Book Section (Book Chapter)


08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)
08 Faculty of Science > Institute of Computer Science (INF)

UniBE Contributor:

Schiller, Eryk Jerzy; Alyafawi, Islam Fayez Abd and Braun, Torsten


000 Computer science, knowledge & systems
500 Science > 510 Mathematics






Studies in Big Data


Springer International Publishing




Dimitrios Xenakis

Date Deposited:

23 Nov 2016 16:25

Last Modified:

01 May 2020 10:47

Publisher DOI:





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