Development of an SDN-based network segment model for 5G standard

DOI: 10.34759/trd-2021-117-07


Bakhtin A. A.1*, Volkov A. S.1**, Solodkov A. V.1***, Baskakov A. E.2***

1. National Research University of Electronic Technology, Bld. 1, Shokin Square, Zelenograd, Moscow, Russia, 124498
2. National Research University of Electronic Technology, 1, sq. Shokina, Moscow, Zelenograd, 124498, Russia



The main effort of the scientific community in the field of telecommunications at present is focused on the development of the fifth generation mobile communication networks, which feature is an increased data rate up to 10 Gbit/s.

An important requirement for the fifth generation mobile networks consists in ensuring flexibility of their architecture for various kinds of applications functioning, of which realization is also possible by employing technologies of software-defined network (SDN) and network functions virtualization (NFV).

The article proposes a model for a network segment organizing under the OpenFLow protocol control, and packages format with account for the possibilities for data transmission level control. The delay and throughput characteristics of the modeled nework segment, demonstrating the SDN networks advantages when employing the proposed format of the control packages, were obtained.

The 5G standard envisages wireless communications with the encreased wireless data rate and throughput; enhanced coverage area; significantly diminished total delay and reduced energy consumption. Data transfer rate should reach the values from 1 to 10 Gbit/s in real networks which is ten times higher than the theoretical peak data transfer rate in the LTE network, i.e. 150 Mbit/s. The symmetrical delay herewith was originally being planned at the level not more than 1 ms, i.e. nearly ten times less than for the 4G. Other key tenets of the 5G development are high throughput in terms of the unit of coverage area and a huge number of connected devices.

With high requirements for the delay and limited bandwidth, a new paradigm for organizing a cell and a base station as a whole is being introduced. The increase in demand for wireless infrastructure capacity has changed the way the networks are designed, and shifted the focus to multiple small cells as opposed to the original hexagonal of the large areas coverage

Changes in architecture and radio interface put emphasis on the development of the 5G standard for smaller cell sizes and an increased number of antennas. Configuring and maintaining numerous network equipment, servers and routers with such a dense of the deployed 5G network is a daunting task. The Software Design Network offers a simplified solution to this complex problem. The fundamental principle of the SDN is the separation of the network between the layers of control and data transmission, which ensures speed and flexibility in 5G networks, as well as employing the existed network architecture and reducing the requirements for computing power of the network equipment. The SDN concept decouples data and manages layers by the software components. The software components are responsible for the management layer, reducing thereby the hardware requirements for the network equipment. Interaction between the two layers is being achieved through the open interfaces, the most popular of which is Open Flow.

The article considered the requirements of the 5G standard for the network infrastructure. It demonstrated the general tendency to reducing the cell size, moving digital processing to the core network level, and locating on sites only radio transceivers, operating on the SDR technology. It was determined at the network architecture level that the software-defined network ensusres the greatest convergence, reuse of current network resources and the easiest scaling and standard changing in the future.

The article shows that the most successful solution to preserve the existing network infrastructure is the OEPC protocol. It presnts the of service messages formats, as well as proposes a frame format with fields that support GTP tunnels.

The simulation results allowed establishing that the SDN-consept based network ensures low delays and, with the selected packages format application, uniform balancing of the network loading. It allows employing the suggested modification of the packages fields to create new algorithms for the communication means control.


mobile communication, software-defined network, 5G, SND, C-RAN, OpenFlow, OEPC, NG network


  1. Andrews J.G. et al., What will 5G be? IEEE Journal of Selected Areas in Communication, 2014, vol. 32, no. 6, pp. 1065 – 1082. DOI: 10.1109/JSAC.2014.2328098

  2. Rappaport T.S., Roh W., Cheun K. Wireless engineers long considered high frequencies worthless for cellular systems. They couldn’t be more wrong, IEEE Spectrum, 2014, vol. 51, no. 9, pp. 34 – 58. DOI: 10.1109/MSPEC.2014.6882985

  3. Borodin V.V., Petrakov A.M., Shevtsov V.A. Elektrosvyaz', 2016, no. 11, pp. 41 - 45.

  4. Borodin V.V., Petrakov A.M., Shevtsov V.A. Trudy MAI, 2015, no. 81. URL:

  5. Borodin V.V., Petrakov A.M., Shevtsov V.A. Trudy MAI, 2018, no. 100. URL:

  6. GSMA Intelligence, Understanding 5G: Perspectives on future technological advancements in mobile, White paper, 2014. URL:

  7. Lara A., Kolasani A., Ramamurthy B. Network innovation using openflow: A survey, IEEE Communication Survey Tuts, 2013, vol. 16, no. 1, pp. 493 - 512. DOI: 10.1109/SURV.2013.081313.00105

  8. Cho H.H., Lai C.F., Shih T.K., Chao H.C. Integration of SDR and SDN for 5G, IEEE Access, 2014, vol. 2, pp. 1196 - 1204. DOI: 10.1109/ACCESS.2014.2357435

  9. Arslan M., Sundaresan K., Rangarajan S. Software-defined networking in cellular radio access networks: Potential and challenges, IEEE Communication Magazine, 2015, vol. 53, no. 1, pp. 150 – 156. DOI: 10.1109/MCOM.2015.7010528

  10. Pirinen P. A Brief overview of 5G research activities, 1st International Conference on 5G for Ubiquitous Connectivity (5GU), Levi, Finland, 2014, pp. 17 – 22. DOI: 10.4108/icst.5gu.2014.258061

  11. Checko A. et al. Cloud RAN for mobile networks-a technology overview, IEEE Communication Survey Tuts, 2015, vol. 17, no. 1, pp. 405 – 426. DOI: 10.1109/COMST.2014.2355255

  12. Chen K., Duan R. C-RAN: The road towards green RAN, China Mobile Research Institute, Beijing, White paper, 2012.

  13. Liu C., Wang J., Cheng L., Zhu M., Chang G.K. Key microwave photonics technologies for next-generation cloud-based radio access networks, Journal of Lightwave Technology, 2014, vol. 32, no. 20, pp. 3452 – 3460. DOI: 10.1109/JLT.2014.2338854

  14. Baskakov A.E. et al. Development of a Mathematical Model of Software-defined Network Segment, 2020 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering (EIConRus), IEEE, 2020, pp. 1689 - 1693. DOI: 10.1109/EIConRus49466.2020.9039461

  15. Baskakov A.E., Volkov A.S. Trudy MAI, 2020, no. 115. URL: DOI: 10.34759/trd-2020-115-06

  16. Cvijetic N. Optical network evolution for 5G mobile applications and SDN-based control, Proceeding of International Telecommunication Network Strategy Planning Symposium, 2014, pp. 1–5. DOI: 10.1109/NETWKS.2014.6958537

  17. Liu C., Wang J., Cheng L., Zhu M., Chang G.K. Key microwave photonics technologies for next-generation cloud-based radio access networks, Journal of Lightwave Technology, 2014, vol. 32, no. 20, pp. 3452 - 3460. DOI: 10.1109/JLT.2014.2338854

  18. Pashkov V., Shalimov A., Smeliansky R. Controller Failover for Enterprise SDN, Proceedings of the Modern Networking Technologies (MoNeTec’2014), IEEE, 2014, pp. 27 - 29. DOI: 10.1109/MoNeTeC.2014.6995594

  19. Rybalko A.A., Naumov A.V. Trudy MAI, 2017, no. 97. URL:

  20. Fang L. et al. Hierarchical SDN for the hyper-scale, hyper-elastic data center and cloud, Proceedings of the 1st ACM SIGCOMM Symposium on Software Defined Networking Research, ACM, 2015. DOI: 10.1145/2774993.2775009

  21. Morzhov S.V., Alekseev I.V., Nikitinskii M.A. Organizatsiya mul'tikontrollernogo vzaimodeistviya v programmno-konfiguriruemykh setyakh, Modelirovanie i analiz informatsionnykh system, 2018, vol. 25, no. 2, pp. 207 - 216.

  22. Voellmy A. et al. Maple: Simplifying SDN programming using algorithmic policies, ACM SIGCOMM Computer Communication Review, ACM, 2013, vol. 43, no. 4, pp. 87 – 98. DOI: 10.1145/2534169.2486030

  23. Cui L., Yu F.R., Yan Q. When big data meets software-defined networking: SDN for big data and big data for SDN, IEEE network, 2016, vol. 30, no. 1, pp. 58 - 65. DOI: 10.1109/MNET.2016.7389832

  24. Dixit A. et al. Towards an elastic distributed SDN controller, ACM SIGCOMM computer communication review, 2013, vol. 43, no. 4, pp. 7 - 12. DOI: 10.1145/2534169.2491193

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