Skip to main content
Log in

Cloud RAN challenges and solutions

  • Published:
Annals of Telecommunications Aims and scope Submit manuscript

Abstract

In this paper, we take an overall look at key technical challenges in the evolution of the radio access network (RAN) architecture towards Cloud RAN and solutions to overcome them. To address fronthaul limitations, we examine the implications and tradeoffs enabled by functional splits on fronthaul needs, system performance, and centralization scale. We examine the architecture of algorithms for multi-cell coordination and implications in a Cloud RAN environment. To maximize the use of general-purpose processors (GPP) and operating systems such as Linux for Cloud RAN, we propose methods of achieving real-time performance suitable for RAN functions. To enable right-sizing the amount of compute used for various RAN functions based on the workload, we propose methods of pooling and elastic scaling for RAN functions that exploit the fact that certain RAN functions perform per-user operations while others perform per-cell operations. Cloud RAN also aims to use cloud management technologies such as virtualized infrastructure management (VIM) and orchestration for automating the instantiation and scaling of RAN functions. We identify special needs for RAN arising from real-time constraints and a mix of GPP and non-GPP hardware. In the evolution towards 5G, we propose the use of Cloud-RAN-based multi-connectivity anchoring to address processing bottlenecks in a scalable manner. We identify opportunities for optimization across RAN and other network layers enabled by the distributed edge cloud architecture.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16

Similar content being viewed by others

References

  1. Cisco, “Cisco VNI Global Mobile Data Traffic Forecast 2014–2019,” Online at http://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white_paper_c11-520862.html

  2. Checko A et al (2015) "Cloud RAN for Mobile Networks - A Technology Overview,” IEEE Comm. Surveys and Tutorials, Vol. 17, No. 1, First Quarter

  3. Rost P et al (2014) Cloud Technologies for Flexible 5G radio access networks. IEEE Comm Mag 52(5):68–76

    Article  Google Scholar 

  4. CPRI, “Common Public Radio Interface (CPRI): Interface Specification,” version 6.1, July 2014. Online at http://www.cpri.info

  5. OBSAI, “Reference Point 3 Specification,” version 4.2. Online at http://www.obsai.com

  6. NGMN Alliance, "Further Studies on Critical C-RAN Technologies," Version 1.0, March 2015. Online at https://www.ngmn.org/uploads/media/NGMN_RANEV_D2_Further_Study_on_Critical_C-RAN_Technologes_v1.0.pdf

  7. Gulati S et al (2016) "Performance Analysis of Centralized RAN Deployment with Non-ideal fronthaul in LTE-Advanced Networks," in Proc. IEEE VTC-Spring

  8. Agrawal R et al (2016) “Architecture Principles for Cloud RAN,” in Proc. IEEE VTC-Spring

  9. 3GPP, “Coordinated Multi-Point Operation for LTE Physical Layer Aspects (Release 11),” TR36.819, v11.2.0, Sept. 2013

  10. Lee D et al (2012) “Coordinated Multipoint Transmission and Reception in LTE-Advanced: Deployment Scenarios and Operational Challenges,” IEEE Comm. Mag., pp. 148–155

  11. Gulati S et al (2015) “Performance Analysis of Distributed Multi-cell Coordinated Scheduler,” in Proc. IEEE VTC-Fall

  12. Pengoria D et al (2015) “Performance of Co-Operative Uplink Reception with Non-Ideal Backhaul,” in Proc. IEEE VTC Spring

  13. Agrawal R et al (2014) “Dynamic Point Selection for LTE-Advanced: Algorithms and Performance,” in Proc. IEEE WCNC

  14. 3GPP, “X2 Application Protocol (X2-AP) Release 12,” TS 36.423, v12.7.0, Sept. 2015

  15. Agrawal R et al (2014) “Centralized and Decentralized Coordinated Scheduling with Muting,” in Proc. IEEE VTC Spring

  16. Open Event Machine Development Team, “Open Event Machine: An event driven processing runtime for multicore,” Online at http://sourceforge.net/projects/eventmachine

  17. DPDK development team, “Data Plane Development Kit,” Online at http://www.dpdk.org

  18. ETSI, “Network Functions Virtualization (NFV): Architectural Framework,” ETSI GS NFV 002 v1.1.1, Oct. 2013. Online at http://www.etsi.org/deliver/etsi_gs/nfv/001_099/002/01.01.01_60/gs_nfv002v010101p.pdf

  19. 3GPP, “E-UTRAN: Overall Description; Stage 2 (Release 13),” TS36.300, v13.4.0, June 2016

  20. Michalopoulos D et al (2016) “User-plane multi-connectivity aspects in 5G,” in Proc. 23rd Int. Conf. Telecom. (ICT)

  21. Intel, “Intel Advanced Encryption Standard Instructions (AES-NI),” Available online at https://software.intel.com/en-us/articles/intel-advanced-encryption-standard-instructions-aes-ni

  22. ETSI, “Mobile Edge Computing (MEC): Framework and Reference Architecture,” ETSI GS MEC 003, v1.1.1, March 2016

Download references

Acknowledgments

The authors would like to acknowledge detailed technical discussions with many colleagues in Nokia, as well as with wireless network operators in several countries.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anand Bedekar.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Agrawal, R., Bedekar, A., Kolding, T. et al. Cloud RAN challenges and solutions. Ann. Telecommun. 72, 387–400 (2017). https://doi.org/10.1007/s12243-017-0584-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12243-017-0584-5

Keywords

Navigation