Skip to main content
SpringerLink
Log in

A Comprehensive Study on 5G: RAN Architecture, Enabling Technologies, Challenges, and Deployment

  • Chapter
  • First Online:
A Glimpse Beyond 5G in Wireless Networks

Part of the book series: Signals and Communication Technology ((SCT))

  • 467 Accesses

Abstract

The fifth-generation (5G) technology promises to provide agile, scalable, and programmable network services in order to respond to the myriad of applications and connected devices of vertical industries. It aims to boost the network capacity, throughput, energy, and spectral efficiencies while reducing latency for sub-milliseconds. In order to fulfill the diverse requirements of industrial Internet of Things (IIoT) applications, drastic changes have been proposed by several telecommunication bodies for the radio access network (RAN) and core. In this chapter, we aim to study comprehensively the 5G architectural frameworks proposed by telecommunication bodies and standards for public and private 5G networks. Furthermore, this chapter provides an in-depth study on the key 5G enabling technologies such as software-defined network (SDN), network functions virtualization (NFV), network slicing, artificial intelligence/machine learning (AI/ML), and multi-access edge computing (MEC). Moreover, 5G simulators and projects are explored and compared considering features, advantages, and limitations.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Options 6 and 8 have been withdrawn of further study by 3GPP due to the various limitations on compatibility between the 5G RAN and the EPC.

  2. 2.

    L2 represents the MAC, radio link control (RLC), and packet data convergence protocol (PDCP). In addition, L3 represents the radio resource control (RRC).

  3. 3.

    Network densification concept increases the number of BSs in a given area.

  4. 4.

    The fronthaul and backhaul links are considered as Ethernet connection.

  5. 5.

    The CU might be deployed as a dedicated hardware or as part of the MEC.

  6. 6.

    The separation of CU-CP and CU-UP occurs via E1 interface.

  7. 7.

    ONF is the consortium for SDN standardization.

  8. 8.

    OpenFlow is the most popular SDN protocol that defines a standard API to separate logically the controller and network devices. It offers an API between the SDN controller and the network devices to communicate over TCP/IP stack for any network topology.

  9. 9.

    The northbound interface provides a network abstraction to the applications and the management systems. Various open-source projects have been proposed for the northbound APIs including RESTFul and Frenetic.

  10. 10.

    FAPI protocol is standardized by the small cell forum in [217].

  11. 11.

    nFAPI protocol is standardized by small cell forum in [219].

References

  1. A. Toskala, H. Holma, T. Nakamura, 5G Technology: 3GPP New Radio (John Wiley and Sons, Hoboken, 2020)

    Google Scholar 

  2. O-RAN Alliance, O-RAN use cases and deployment scenarios (2021). https://static1.squarespace.com/static/5ad774cce74940d7115044b0/t/5e95a0a306c6ab2d1cbca4d3/1586864301196/O-RAN+Use+Cases+and+Deployment+Scenarios+Whitepaper+February+2020.pdf. Accessed Jan 2021

  3. M.A. Habibi, M. Nasimi, B. Han, H.D. Schotten, A comprehensive survey of RAN architectures toward 5G mobile communication system. IEEE Access 7, 70371–70421 (2019)

    Article  Google Scholar 

  4. M.F. Hossain, A.U. Mahin, T. Debnath, F.B. Mosharrof, K.Z. Islam, Recent research in cloud radio access network (C-RAN) for 5G cellular systems – a survey. J. Netw. Comput. Appl. 139, 31–48 (2019)

    Article  Google Scholar 

  5. W. Ejaz, S.K. Sharma, S. Saadat, M. Naeem, A. Anpalagan, N.A. Chughtai, A comprehensive survey on resource allocation for CRAN in 5G and beyond networks. J. Netw. Comput. Appl. (2020). https://doi.org/10.1016/j.jnca.2020.102638

  6. F. Tian, P. Zhang, Z. Yan, A survey on C-RAN security. IEEE Access 5, 13372–13386 (2017)

    Article  Google Scholar 

  7. M. Agiwal, A. Roy, N. Saxena, Next generation 5G wireless networks: a comprehensive survey. IEEE Commun. Surv. Tutorials 18(3), 1617–1655 (2016)

    Article  Google Scholar 

  8. S.K. Sharma, X. Wang, Toward massive machine type communications in ultra-dense cellular IoT networks: current issues and machine learning-assisted solutions. IEEE Commun. Surv. Tutorials 22(1), 426–471 (2020)

    Article  Google Scholar 

  9. I.B.F. de Almeida, L.L. Mendes, J.J.P.C. Rodrigues, M.A.A. da Cruz, 5G waveforms for IoT applications. IEEE Commun. Surv. Tutorials 21(3), 2554–2567 (2019). Thirdquarter

    Google Scholar 

  10. L. Chettri, R. Bera, A comprehensive survey on internet of things (IoT) toward 5G wireless systems. IEEE Internet Things J. 7(1), 16–32 (2020)

    Article  Google Scholar 

  11. G.A. Akpakwu, B.J. Silva, G.P. Hancke, A.M. Abu-Mahfouz, A survey on 5G networks for the internet of things: communication technologies and challenges. IEEE Access 6, 3619–3647 (2018)

    Article  Google Scholar 

  12. J. Ding, M. Nemati, C. Ranaweera, J. Choi, IoT connectivity technologies and applications: a survey. IEEE Access 8, 67646–67673 (2020)

    Article  Google Scholar 

  13. F. Al-Turjman, E. Ever, H. Zahmatkesh, Small cells in the forthcoming 5G/IoT: traffic modelling and deployment overview. IEEE Commun. Surv. Tutorials 21(1), 28–65 (2019)

    Article  Google Scholar 

  14. M. Wazid, A.K. Das, S. Shetty, P. Gope, J.J.P.C. Rodrigues, Security in 5G-enabled internet of things communication: issues, challenges, and future research roadmap. IEEE Access 9, 4466–4489 (2021)

    Article  Google Scholar 

  15. F. Spinelli, V. Mancuso, Toward enabled industrial verticals in 5G: a survey on MEC-based approaches to provisioning and flexibility. IEEE Commun. Surv. Tutorials 23(1), 596–630 (2021)

    Article  Google Scholar 

  16. M. Shafi et al., 5G: a tutorial overview of standards, trials, challenges, deployment, and practice. IEEE J. Sel. Areas Commun. 35(6), 1201–1221 (2017)

    Article  Google Scholar 

  17. M.A. Adedoyin, O.E. Falowo, Combination of ultra-dense networks and other 5G enabling technologies: a survey. IEEE Access 8, 22893–22932 (2020)

    Article  Google Scholar 

  18. S. Chen, R. Ma, H. Chen, H. Zhang, W. Meng, J. Liu, Machine-to-machine communications in ultra-dense networks—a survey. IEEE Commun. Surv. Tutorials 19(3), 1478–1503 (2017)

    Article  Google Scholar 

  19. M. Kamel, W. Hamouda, A. Youssef, Ultra-dense networks: a survey. IEEE Commun. Surv. Tutorials 18(4), 2522–2545 (2016)

    Article  Google Scholar 

  20. A.C. Baktir, A. Ozgovde, C. Ersoy, How can edge computing benefit from software-defined networking: a survey, use cases, and future directions. IEEE Commun. Surv. Tutorials 19(4), 2359–2391 (2017)

    Article  Google Scholar 

  21. 3GPP TR38.913, Study on scenarios and requirements for next generation access technologies (2020). https://www.3gpp.org/ftp//Specs/archive/38_series/38.913/. Accessed Jan 2021

  22. M. Agiwal, H. Kwon, S. Park, H. Jin, A survey on 4G-5G dual connectivity: road to 5G implementation. IEEE Access 9, 16193–16210 (2021)

    Article  Google Scholar 

  23. D. Soldani, M. Shore, J. Mitchell, M. Gregory, The 4G to 5G network architecture evolution in Australia. J. Telecommun. Digit. Econ. 6, 1–30 (2018)

    Google Scholar 

  24. 3GPP TR 38.801, Technical Specification Group Radio Access Network; Study on new radio access technology: Radio access architecture and interfaces (2017)

    Google Scholar 

  25. Y. Lin et al., Wireless network cloud: architecture and system requirements. IBM J. Res. Develop. 54(1) (2010)

    Google Scholar 

  26. China Mobile Res. Inst., C-RAN the Road Towards Green RAN-White Paper. China Mobile Beijing (2011)

    Google Scholar 

  27. H. Venkataraman, R. Trestian, 5G Radio Access Networks: Centralized RAN, Cloud-RAN and Virtualization of Small Cells (CRC Press, Boca Raton, 2017)

    Book  Google Scholar 

  28. J. Wu, Z. Zhang, Y. Hong, Y. Wen, Cloud radio access network (C-RAN): a primer. IEEE Netw. 29(1), 35–41 (2015)

    Article  Google Scholar 

  29. O. Alamu, A. Gbenga-Ilori, M. Adelabu, A. Imoize, O. Ladipo, Energy efficiency techniques in ultra-dense wireless heterogeneous networks: an overview and outlook. Eng. Sci. Technol. Int. J. 23(6), 1308–1326 (2020)

    Google Scholar 

  30. M. Peng, Y. Li, J. Jiang, J. Li, C. Wang, Heterogeneous cloud radio access networks: a new perspective for enhancing spectral and energy efficiencies. IEEE Wirel. Commun. 21(6), 126–135 (2014)

    Article  Google Scholar 

  31. Y. Li, T. Jiang, K. Luo, S. Mao, Green heterogeneous cloud radio access networks: potential techniques, performance trade-offs, and challenges. IEEE Commun. Mag. 55(11), 33–39 (2017)

    Article  Google Scholar 

  32. M. Peng, Y. Li, Z. Zhao, C. Wang, System architecture and key technologies for 5G heterogeneous cloud radio access networks. IEEE Netw. 29(2), 6–14 (2015)

    Article  Google Scholar 

  33. 3GPP TR 36.932, Scenarios and requirements for small cell enhancements for E-UTRA and E-UTRAN (2020). https://www.3gpp.org/ftp/Specs/archive/36_series/36.932/. Accessed Nov 2021

  34. ETSI, Network function virtualization: use cases (2013). www.etsi.org. Accessed Nov 2021

  35. H. Hawilo, A. Shami, M. Mirahmadi, R. Asal, NFV: state of the art, challenges, and implementation in next generation mobile networks (vEPC). IEEE Netw. 28(6), 18–26 (2014)

    Article  Google Scholar 

  36. M. Arslan, K. Sundaresan, S. Rangarajan, Software-defined networking in cellular radio access networks: potential and challenges. IEEE Commun. Mag. 53(1), 150–156 (2015)

    Article  Google Scholar 

  37. X. Wang et al., Virtualized cloud radio access network for 5G transport. IEEE Commun. Mag. 55(9), 202–209 (2017)

    Article  Google Scholar 

  38. I.F. Akyildiz, P. Wang, S.-C. Lin, SoftAir: a software defined networking architecture for 5G wireless systems. Comput. Netw. 85, 1–18 (2015)

    Article  Google Scholar 

  39. E. Markakis, G. Mastorakis, C.X. Mavromoustakis, E. Pallis, Cloud and Fog Computing in 5G Mobile Networks: Emerging Advances and Applications (The Institution of Engineering and Technology, London, 2017)

    Google Scholar 

  40. M. Peng, S. Yan, K. Zhang, C. Wang, Fog-computing-based radio access networks: issues and challenges. IEEE Netw. 30(4), 46–53 (2016)

    Article  Google Scholar 

  41. M. Peng, Z. Zhao, Y. Sun, Fog Radio Access Networks (F-RAN) Architectures, Technologies, and Applications (Springer International Publishing, Berlin, 2020)

    Book  Google Scholar 

  42. O-RAN Alliance Technical Specifications, O-RAN Architecture Description v02.00 (2020). https://www.o-ran.org. Accessed Jan 2021

  43. O-RAN Alliance, https://www.o-ran.org. Accessed Jan 2021

  44. A. Garcia-Saavedra, X. Costa-Perez, O-RAN: disrupting the virtualized RAN ecosystem. IEEE Commun. Stand. Mag. (2021). https://doi.org/10.1109/MCOMSTD.101.2000014

  45. 5G PPP Architecture Working Group, View on 5G Architecture, Version 3.0 – February (2020)

    Google Scholar 

  46. 3GPP TS 23.501, TSG RAN, System architecture for the 5G System (5GS) Stage 2 v16.6.0 (2020)

    Google Scholar 

  47. Qualcomm, White Paper: Private 5G Mobile Networks for Industrial IoT (2019). www.qualcomm.com/media/documents/files/private-5g-networks-for-industrial-iot.pdf. Accessed Jan 2021

  48. 5G-ACIA, White Paper: 5G Non-Public Networks for Industrial Scenarios (2019). https://5g-acia.org/wp-content/uploads/2021/04/WP_5G_NPN_2019_01.pdf. Accessed Jan 2021

  49. 5G-Smart, D5.2: First Report on 5G Network Architecture Options and Assessments (2020). https://5gsmart.eu/wp-content/uploads/5G-SMART-D5.2-v1.0.pdf. Accessed Jan 2021

  50. A. Aijaz, Private 5G: the future of industrial wireless. IEEE Indust. Electron. Mag. 14(4), 136–145 (2020)

    Article  Google Scholar 

  51. MulteFire, Technical Paper: A New Way to Wireless (2021). www.multefire.org/wp-content/uploads/MulteFire-Release-1.0-whitepaper_FINAL.pdf. Accessed Nov 2021

  52. 3GPP TS 23.251, Network sharing; Architecture and functional description (2020). https://www.3gpp.org/ftp/Specs/archive/23_series/23.251/. Accessed Nov 2021

  53. Multefire, Cellular-based technology — LTE or 5G NR — operating in unlicensed or shared spectrum (2020). https://www.multefire.org/. Accessed Dec 2020

  54. 3GPP TR 23.734, Study on Enhancement of 5G System (5GS) for Vertical and Local Area Network (LAN) Services (Release 16) (2020). https://www.3gpp.org/ftp/Specs/archive/23series/23.734/. Accessed Dec 2020

  55. IDC, Worldwide Internet of Things Forecast Update 2020–2024 (2020). www.reportlinker.com/p05352129/Worldwide-Internet-of-Things-Forecast-Update.html. Accessed Dec 2021

  56. A.W. Dawson, M.K. Marina, F.J. Garcia, On the benefits of RAN virtualisation in C-RAN based mobile networks, in 2014 Third European Workshop on Software Defined Networks, London (2014), pp. 103–108

    Google Scholar 

  57. E.J. Kitindi, S. Fu, Y. Jia, A. Kabir, Y. Wang, Wireless network virtualization with SDN and C-RAN for 5G networks: requirements, opportunities, and challenges. IEEE Access 5, 19099–19115 (2017)

    Article  Google Scholar 

  58. T.Q. Duong, X. Chu, H.A. Suraweera, Ultra-Dense Networks for 5G and Beyond: Modelling, Analysis, and Applications (John Wiley & Sons Ltd., Hoboken, 2019)

    Book  Google Scholar 

  59. H. Zhang, Y. Dong, J. Cheng, M.J. Hossain, V.C.M. Leung, Fronthauling for 5G LTE-U ultra dense cloud small cell networks. IEEE Wirel. Commun. 23(6), 48–53 (2016)

    Article  Google Scholar 

  60. ETSI, NFV White paper: Network Functions Virtualisation, An Introduction, Benefits, Enablers, Challenges & Call for Action (2012). https://portal.etsi.org/NFV/NFV_White_Paper.pdf. Accessed Oct 2021

  61. M. Masoudi, S.S. Lisi, C. Cavdar, Cost-effective migration toward virtualized C-RAN with scalable fronthaul design. IEEE Syst. J. 14(4), 5100–5110 (2020)

    Article  Google Scholar 

  62. S. Su, X. Xu, Z. Tian, M. Zhao, W. Wang, 5G fronthaul design based on software-defined and virtualized radio access network, in 2019 28th Wireless and Optical Communications Conference (WOCC) (2019), pp. 1–5

    Google Scholar 

  63. S. Hung, H. Hsu, S. Lien, K. Chen, Architecture harmonization between cloud radio access networks and fog networks. IEEE Access 3, 3019–3034 (2015)

    Article  Google Scholar 

  64. M. De Donno, K. Tange, N. Dragoni, Foundations and evolution of modern computing paradigms: cloud, IoT, edge, and fog. IEEE Access 7, 150936–150948 (2019)

    Article  Google Scholar 

  65. S. Naveen, M.R. Kounte, Key technologies and challenges in IoT edge computing, in 2019 Third International Conference on I-SMAC (2019), pp. 61–65

    Google Scholar 

  66. D. Loghin, L. Ramapantulu, Y.M. Teo, On understanding time, energy and cost performance of wimpy heterogeneous systems for edge computing, in IEEE International Conference on Edge Computing (EDGE) (2017), pp. 1–8

    Google Scholar 

  67. H. El-Sayed et al., Edge of things: the big picture on the integration of edge, IoT and the cloud in a distributed computing environment. IEEE Access 6, 1706–1717 (2018)

    Google Scholar 

  68. Y. Liu, M. Peng, G. Shou, Y. Chen, S. Chen, Toward edge intelligence: multiaccess edge computing for 5G and internet of things. IEEE Internet of Things J. 7(8), 6722–6747 (2020)

    Article  Google Scholar 

  69. M. Caprolu, R. Di Pietro, F. Lombardi, S. Raponi, Edge computing perspectives: architectures, technologies, and open security issues, in 2019 IEEE International Conference on Edge Computing (EDGE) (2019), pp. 116–123

    Google Scholar 

  70. Cisco, Cisco delivers vision of fog computing to accelerate value from billions of connected devices (2020). http://newsroom.cisco.com/press-release-content?type=webcontent&articleId=1334100. Accessed May 2021

  71. J.S. Preden, K. Tammemäe, A. Jantsch, M. Leier, A. Riid, E. Calis, The benefits of self-awareness and attention in fog and mist computing. Computer 48(7), 37–45 (2015)

    Article  Google Scholar 

  72. OpenFog Consortium, https://www.openfogconsortium.org. Accessed July 2021

  73. M. Sapienza, E. Guardo, M. Cavallo, G. La Torre, G. Leombruno, O. Tomarchio, Solving critical events through mobile edge computing: an approach for smart cities, in 2016 IEEE International Conference on Smart Computing (SMARTCOMP) (2016), pp. 1–5

    Google Scholar 

  74. I. Badmus, M. Matinmikko-Blue, J.S. Walia, T. Taleb, Network slice instantiation for 5G micro-operator deployment scenarios, in 2019 European Conference on Networks and Communications (EuCNC) (2019), pp. 133–138

    Google Scholar 

  75. H. Li, G. Shou, Y. Hu, Z. Guo, Mobile edge computing: progress and challenges, in 2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud) (2016), pp. 83–84

    Google Scholar 

  76. S. Kukliński, L. Tomaszewski, R. Kołakowski, On O-RAN, MEC, SON and Network Slicing integration, in 2020 IEEE Globecom Workshops (GC Wkshps) (2020), pp. 1–6

    Google Scholar 

  77. M. Barahman, L.M. Correia, L.S. Ferreira, QoS-demand-aware computing resource management scheme in cloud-RAN. IEEE Open J. Commun. Soc. 1, 1850–1863 (2020)

    Article  Google Scholar 

  78. S.S. Arnob, I. Islam Shovon, T. Ahmed, M.S. Ullah, R. Shelim, Dual-order resource allocation in 5G H-CRAN using matching theory and ant colony optimization algorithm, in IECON 2020 The 46th Annual Conference of the IEEE Industrial (2020), pp. 2101–2107

    Google Scholar 

  79. Y. Ai, G. Qiu, C. Liu, Y. Sun, Joint resource allocation and admission control in sliced fog radio access networks. China Commun. 17(8), 14–30 (2020)

    Article  Google Scholar 

  80. F. Mungari, An RL approach for radio resource management in the O-RAN architecture, in 2021 18th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON) (2021), pp. 1–2

    Google Scholar 

  81. B. Xu, P. Zhu, J. Li, D. Wang, X. You, Joint long-term energy efficiency optimization in C-RAN with hybrid energy supply. IEEE Trans. Veh. Technol. 69(10), 11128–11138 (2020)

    Article  Google Scholar 

  82. L. Ferdouse, I. Woungang, A. Anpalagan, S. Erkucuk, Energy efficient downlink resource allocation in cellular IoT supported H-CRANs. IEEE Trans. Veh. Technol. 70(6), 5803–5816 (2021)

    Article  Google Scholar 

  83. T.H.L. Dinh, M. Kaneko, E.H. Fukuda, L. Boukhatem, Energy efficient resource allocation optimization in fog radio access networks with outdated channel knowledge. IEEE Trans. Green Commun. Netw. 5(1), 146–159 (2021)

    Article  Google Scholar 

  84. T. Pamuklu, S. Mollahasani, M. Erol-Kantarci, Energy-efficient and delay-guaranteed joint resource allocation and DU selection in O-RAN, in 2021 IEEE 4th 5G World Forum (5GWF) (2021), pp. 99–104

    Google Scholar 

  85. S. Park, O. Simeone, S. Shamai, Multi-tenant C-RAN with spectrum pooling: downlink optimization under privacy constraints. IEEE Trans. Veh. Technol. 67(11), 10492–10503 (2018)

    Article  Google Scholar 

  86. I. Al-Samman, R. Almesaeed, A. Doufexi, M. Beach, A. Nix, User weighted probability algorithm for heterogeneous C-RAN interference mitigation, in 2017 IEEE International Conference on Communications (ICC) (2017), pp. 1–7

    Google Scholar 

  87. Y. Yu, S. Liu, Z. Tian, S. Wang, A dynamic distributed spectrum allocation mechanism based on game model in fog radio access networks. China Commun. 16(3), 12–21 (2019)

    Google Scholar 

  88. D.S. Dong, K. Khatri, A. Gachhadar, Network coding based secure and efficient traffic flow in Heterogeneous Cloud Radio Access Network, in 2017 International Conference on Wireless Communications, Signal Processing and Networking (WiSPNET) (2017), pp. 584–589

    Google Scholar 

  89. D. Dik, M.S. Berger, Transport security considerations for the open-RAN fronthaul, in 2021 IEEE 4th 5G World Forum (5GWF) (2021), pp. 253–258

    Google Scholar 

  90. F. Tonini, C. Raffaelli, L. Wosinska, P. Monti, Cost-optimal deployment of a C-RAN with hybrid fiber/FSO fronthaul. J. Opt. Commun. Netw. 11(7), 397–408 (2019)

    Article  Google Scholar 

  91. K. Wang, K. Yang, X. Wang, C.S. Magurawalage, Cost-effective resource allocation in C-RAN with mobile cloud, in 2016 IEEE International Conference on Communications (ICC) (2016), pp. 1–6

    Google Scholar 

  92. D. Pliatsios, P. Sarigiannidis, I.D. Moscholios, A. Tsiakalos, Cost-efficient remote radio head deployment in 5G networks under minimum capacity requirements, in 2019 Panhellenic Conference on Electronics & Telecommunications (PACET) (2019), pp. 1–4

    Google Scholar 

  93. O. Chabbouh, S. Ben Rejeb, N. Nasser, N. Agoulmine, Z. Choukair, Novel cloud-RRH architecture with radio resource management and QoS strategies for 5G HetNets. IEEE Access 8, 164815–164832 (2020)

    Article  Google Scholar 

  94. 3GPP TS 22.104, Service requirements for cyber-physical control applications in vertical domains (2021). https://www.3gpp.org/ftp/Specs/archive/22_series/22.104/. Accessed June 2021

  95. C. Rosa, M. Kuusela, F. Frederiksen, K.I. Pedersen, Standalone LTE in unlicensed spectrum: radio challenges, solutions, and performance of multefire. IEEE Commun. Mag. 56(10), 170–177 (2018)

    Article  Google Scholar 

  96. Nokia, Industrial-grade Private Wireless (2021). https://www.nokia.com/networks/solutions/private-wireless/. Accessed Aug 2021

  97. GSMA, Spectrum Sharing (2021). www.gsma.com/spectrum/wp-content/uploads/2021/06/Spectrum-Sharing-Positions.pdf. Accessed Aug 2021

  98. LTE-U Forum, LTE-U Technical Report: Coexistence study for LTE-U SDL V1.0 (2015)

    Google Scholar 

  99. R. Zhang, M. Wang, L.X. Cai, Z. Zheng, X. Shen, L.-L. Xie, LTEunlicensed: the future of spectrum aggregation for cellular networks. IEEE Wirel. Commun. 22(3), 150–159 (2015)

    Article  Google Scholar 

  100. 3GPP TR 36.889, Study on Licensed Assisted Access to Unlicensed Spectrum (Release 13) (2015). https://www.3gpp.org/ftp/Specs/archive/36_series/36.889/. Accessed Aug 2021

  101. 3GPP TR 38.889, Study on NR-based access to unlicensed spectrum (Release 15) (2018). https://www.3gpp.org/ftp/Specs/archive/38_series/38.889/. Accessed Aug 2021

  102. 3GPP TSG-RAN 86, Document RP-193259: Study on Supporting NR From 52.6 GHz to 71 GHz (2019). https://www.3gpp.org/ftp/tsg_ran/WG1_RL1/TSGR1_101-e/Inbox/drafts. Accessed Aug 2021

  103. 3GPP TSG-RAN 86, Document RP-193229: Extending Current NR Operation to 71 GHz (2019). https://www.3gpp.org/ftp/tsg_ran/TSG_RAN/TSGR_90e/Inbox/Drafts/. Accessed Aug 2021

  104. S. Lagen et al., New radio beam-based access to unlicensed spectrum: design challenges and solutions. IEEE Communl Survl Tutorials 22(1), 8–37 (2020)

    Article  Google Scholar 

  105. F. Hu, Q. Hao, K. Bao, A survey on software-defined network and openflow: from concept to implementation. IEEE Commun. Surv. Tutorials 16(4), 2181–2206 (2014)

    Article  Google Scholar 

  106. S. Sezer et al., Are we ready for SDN? Implementation challenges for software-defined networks. IEEE Commun. Mag. 103(1), 14–76 (2015)

    Google Scholar 

  107. D. Kreutz, F.M.V. Ramos, P.E. Veríssimo, C.E. Rothenberg, S. Azodolmolky, S. Uhlig, Software-defined networking: a comprehensive survey. Proc. IEEE 103(1), 14–76 (2015)

    Article  Google Scholar 

  108. A. Mavromatis et al., A software-defined IoT device management framework for edge and cloud computing. IEEE Internet Things J. 7(3), 1718–1735 (2020)

    Article  Google Scholar 

  109. T. Taleb, K. Samdanis, B. Mada, H. Flinck, S. Dutta, D. Sabella, On multi-access edge computing: a survey of the emerging 5G network edge cloud architecture and orchestration. IEEE Commun. Surv. Tutorials 19(3), 1657–1681 (2017)

    Article  Google Scholar 

  110. S.D.A. Shah, M.A. Gregory, S. Li, R.D.R. Fontes, SDN enhanced multi-access edge computing (MEC) for E2E mobility and QoS management. IEEE Access 8, 77459–77469 (2020)

    Article  Google Scholar 

  111. J. Tourrilhes, P. Sharma, S. Banerjee, J. Pettit, SDN and OpenFlow evolution: a standards perspective. Computer 47(11), 22–29 (2014)

    Article  Google Scholar 

  112. P. Farzaneh, P. Marius, T.W. Lum, I. Jadwiga, Efficient topology discovery in software defined networks, in 8th International Conference on Signal Processing and Communication Systems (ICSPCS) (2014)

    Google Scholar 

  113. J.S. Choi, X. Li, Hierarchical distributed topology discovery protocol for multi-domain SDN networks. IEEE Commun. Lett. 21(4), 773–776 (2017)

    Article  Google Scholar 

  114. M. Obadia, M. Bouet, J. Leguay, K. Phemius, L. Iannone, Failover mechanisms for distributed SDN controllers, in International Conference and Workshop on the Network of the Future (NOF), Paris (2014), pp. 1–6

    Google Scholar 

  115. R. Hwang, Y. Tang, Fast failover mechanism for SDN-enabled data centers, in International Computer Symposium (ICS) (2016), pp. 171–176

    Google Scholar 

  116. K. Fang, K. Wang, J. Wang, A fast and load-aware controller failover mechanism for software-defined networks, in 10th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP) (2016), pp. 1–6

    Google Scholar 

  117. K.S. Sahoo, B. Sahoo, CAMD: a switch migration based load balancing framework for software defined networks. IET Netw. 8(4), 264–271 (2019)

    Article  Google Scholar 

  118. O. Adekoya, A. Aneiba, M. Patwary, An improved switch migration decision algorithm for SDN load balancing. IEEE Open J. Commun. Soc. 1, 1602–1613 (2020)

    Article  Google Scholar 

  119. T. Wang, F. Liu, H. Xu, An efficient online algorithm for dynamic SDN controller assignment in data center networks. IEEE/ACM Trans. Netw. 25(5), 2788–2801 (2017)

    Article  Google Scholar 

  120. K. Sagar Sahoo et al., Metaheuristic solutions for solving controller placement problem in SDN-based WAN architecture, in 14th International Joint Conference on e-Business and Telecommunications, vol. 1 (2017), pp. 15–23

    Google Scholar 

  121. S. Lange et al., Heuristic approaches to the controller placement problem in large scale SDN networks. IEEE Trans. Netw. Ser. Manag. 12(1), 4–17 (2015)

    Article  Google Scholar 

  122. H. Kuang, Y. Qiu, R. Li, X. Liu, A hierarchical K-means algorithm for controller placement in SDN-based WAN architecture, in 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) (2018), pp. 263–267

    Google Scholar 

  123. X. Yang, D. Wang, W. Tang, W. Feng, C. Zhu, IPsec cryptographic algorithm invocation considering performance and security for SDN southbound interface communication. IEEE Access 8, 181782–181795 (2020)

    Article  Google Scholar 

  124. S. Midha, K. Triptahi, Extended TLS security and defensive algorithm in OpenFlow SD, in 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence) (2019), pp. 141–146

    Google Scholar 

  125. Z. Latif, K. Sharif, F. Li, Md.M. Karim, Y. Wang, A comprehensive survey of interface protocols for software defined networks. J. Netw. Comput. Appl. (2020). https://arxiv.org/abs/1902.07913. Accessed Dec 2021

  126. D. Hasan, M. Othman, Efficient topology discovery in software defined networks: revisited. J. Netw. Comput. Appl. 156, 539–547 (2017)

    Google Scholar 

  127. L. EL-Garoui, S. Pierre, S. Chamberland, A New SDN-based routing protocol for improving delay in smart city environments. Smart Cities 3(3), 1004–1021 (2020). https://doi.org/10.3390/smartcities3030050

  128. M. Abdollahi, M. Abolhasan, N. Shariati, J. Lipman, A. Jamalipour, W. Ni, A routing protocol for SDN-based multi-hop D2D communications, in 16th IEEE Annual Consumer Communications & Networking Conference (CCNC) (2019), pp. 1–4

    Google Scholar 

  129. K. Indira, P. Ajitha, V. Reshma, A. Tamizhselvi, An efficient secured routing protocol for software defined internet of vehicles, in International Conference on Computational Intelligence in Data Science (ICCIDS) (2019), pp. 1–4

    Google Scholar 

  130. M.J. Anjum, I. Raza, S.A. Hussain, Real-time multipath transmission protocol (RMTP): a software defined networks (SDN) based routing protocol for data centric networks, in International Conference on Electrical, Communication, and Computer Engineering (ICECCE) (2019), pp. 1–6

    Google Scholar 

  131. O. Lemeshko, O. Nevzorova, V. Rossikhin, A.M. Hailan, Hierarchical method of load balancing routing on SDN controllers with multicore architecture, in International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T) (2018), pp. 457–460

    Google Scholar 

  132. A. Azzouni et al., sOFTDP: Secure and Efficient Topology Discovery Protocol for SDN (2017). https://hal.sorbonne-universite.fr/hal-01538564/file/sOFTDP.pdf. Accessed Dec 2021

  133. N. Abdolmaleki, M. Ahmadi, H.T. Malazi, S. Milardo, Fuzzy topology discovery protocol for SDN-based wireless sensor networks. Simul. Model. Pract. Theory 79, 54–68 (2017)

    Article  Google Scholar 

  134. F.Z. Yousaf, M. Bredel, S. Schaller, F. Schneider, NFV and SDN—key technology enablers for 5G networks. IEEE J. Sel. Areas Commun. 35(11), 2468–2478 (2017)

    Article  Google Scholar 

  135. Y. Hu, J. Wang, Architectural and cost implications of the 5G edge NFV systems, in IEEE 37th International Conference on Computer Design (ICCD) (2019), pp. 594–603

    Google Scholar 

  136. L. Zhang et al., Characterizing and orchestrating NFV-ready servers for efficient edge data processing, in IEEE/ACM 27th International Symposium on Quality of Service (IWQoS) (2019), pp. 1–10

    Google Scholar 

  137. ETSI, ETSI GS NFV 002: Network Functions Virtualisation (NFV); Architectural Framework (2014). https://www.etsi.org/deliver/etsi_gs/nfv/001_099/002/01.02.01_60/gs_nfv002v010201p.pdf. Accessed Dec 2021

  138. 5GPPP SN WG, Vision on Software Networks and 5G (2017). https://5g-ppp.eu/wp-content/uploads/2014/02/5G-PPP_SoftNets_WG_whitepaper_v20.pdf. Accessed Dec 2021

  139. ETSI, ETSI ISG NFV working group (2021). https://www.etsi.org/technologies/nfv. Accessed Dec 2021

  140. 3GPP TS 28.500, Management concept, architecture and requirements for mobile networks that include virtualized network function (2020). https://www.3gpp.org/ftp//Specs/archive/28_series/28.500/. Accessed Dec 2021

  141. K. Sienkiewicz, W. Latoszek, P. Krawiec, Services orchestration within 5G networks — challenges and solutions, in Baltic URSI Symposium (URSI) (2018), pp. 265–268

    Google Scholar 

  142. M. Casazza, M. Bouet, S. Secci, Availability-driven NFV orchestration. Comput. Netw. 155, 47–61 (2019). https://doi.org/10.1016/j.comnet.2019.02.017

    Article  Google Scholar 

  143. B. Gerő et al., The orchestration in 5G exchange – a multi-provider NFV framework for 5G services, in IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) (2017), pp. 1–2

    Google Scholar 

  144. X. Liang, X. Huang, D. Li, T. Yang, Dynamic orchestration mechanism of service function chain in hybrid NFV networks, in Asia Communications and Photonics Conference (ACP) (2018), pp. 1–3

    Google Scholar 

  145. G. Abolfazl, A. Behzad, T.M. Mahdi, Joint Reliability-aware and Cost Efficient Path Allocation and VNF Placement using Sharing Scheme (2019). https://arxiv.org/abs/1912.06742. Accessed Dec 2021

  146. C. Park, D. Shin, VNF management method using VNF Group Table in Network Function Virtualization, in 19th International Conference on Advanced Communication Technology (ICACT) (2017), pp. 210–212

    Google Scholar 

  147. M. Kumazaki, M. Ogura, T. Tachibana, VNF management with model predictive control for service chains, in IEEE International Conference on Consumer Electronics – Taiwan (ICCE-TW) (2019), pp. 1–2

    Google Scholar 

  148. Ruiz et al., A genetic algorithm for VNF provisioning in NFV-enabled cloud/MEC RAN architectures. Appl. Sci. 8(12) (2018). https://doi.org/10.3390/app8122614

  149. M. Huang, W. Liang, X. Shen, Y. Ma, H. Kan, Reliability-aware virtualized network function services provisioning in mobile edge computing. IEEE Trans. Mob. Comput. 19(11), 2699–2713 (2020)

    Article  Google Scholar 

  150. Q. Xia, W. Ren, Z. Xu, P. Zhou, W. Xu, G. Wu, Learn to optimize: adaptive VNF provisioning in mobile edge clouds, in 17th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON) (2020), pp. 1–9

    Google Scholar 

  151. J. Incheol, K. Gu-In, Genetic algorithm for service function chaining in NFV. Adv. Sci. Technol. Lett. 129, 223–228 (2016)

    Google Scholar 

  152. M. Wang, B. Cheng, B. Li, J. Chen, Service function chain composition and mapping in NFV-enabled networks, in IEEE World Congress on Services (SERVICES) (2019), pp. 331–334

    Google Scholar 

  153. A. OI, M. Nakajima, Y. Soejima and M. Tahara, Reliable design method for service function chaining, in 20th Asia-Pacific Network Operations and Management Symposium (APNOMS) (2019), pp. 1–4

    Google Scholar 

  154. L. Ochoa-Aday, C. Cervelló-Pastor, A. Fernández-Fernández, P. Grosso, An Online Algorithm for Dynamic NFV Placement in Cloud-Based Autonomous Response Networks. Symmetry. 10(5), 163 (2018)

    Google Scholar 

  155. D. Gedia, L. Perigo, Latency-aware, static, and dynamic decision-tree placement algorithm for containerized SDN-VNF in OpenFlow architectures, in IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN) (2019), pp. 1–7

    Google Scholar 

  156. M. Karimzadeh-Farshbafan, V. Shah-Mansouri, D. Niyato, A dynamic reliability-aware service placement for network function virtualization (NFV). IEEE J. Sel. Areas Commun. 38(2), 318–333 (2020)

    Article  Google Scholar 

  157. I. Sarrigiannis et al., VNF lifecycle management in an MEC-enabled 5G IoT architecture. IEEE Internet Things J. 7(5), 4183–4194 (2020)

    Article  Google Scholar 

  158. S. Lange et al., A network intelligence architecture for efficient VNF lifecycle management. IEEE Trans. Netw. Ser. Manag. 18(2), 1476–1490 (2021)

    Article  Google Scholar 

  159. ETSI, ETSI NFV API Specifications (2021). https://nfvwiki.etsi.org/index.php?title=API`_specifications. Accessed Dec 2021

  160. 5GPPP, On Board Procedure to 5G PPP Infrastructure Projects (2020). https://5g-ppp.eu/wp-content/uploads/2020/04/. Accessed Dec 2021

  161. 5G PPP, 5G Exchange (5GEx) project (2021). [Online]. Available: https://5g-ppp.eu/5gex/. Accessed Dec 2021

  162. 5G PPP, Cloud-Native and Verticals services5G-PPP projects analysis (2019). https://5g-ppp.eu/wp-content/uploads/2019/09/. Accessed Dec 2021

  163. L.U. Khan, I. Yaqoob, N.H. Tran, Z. Han, C.S. Hong, Network slicing recent advances, taxonomy, requirements, and open research challenges. IEEE Access 8, 36009–36028 (2020)

    Article  Google Scholar 

  164. 3GPP TS 38.300, NR and NG-RAN Overall Desciption (2020). https://www.3gpp.org/ftp//Specs/archive/38_series/38.300/. Accessed Jan 2021

  165. S. Ahmadi, 5G NR: Architecture, Technology, Implementation, and Operation of 3GPP New Radio Standards (Academic Press, Cambridge, 2019)

    Google Scholar 

  166. D. Sattar, A. Matrawy, Optimal slice allocation in 5G core networks. IEEE Netw. Lett. 1(2), 48–51 (2019)

    Article  Google Scholar 

  167. R. Wen et al., On robustness of network slicing for next-generation mobile networks. IEEE Trans. Commun. 67(1), 430–444 (2019)

    Article  Google Scholar 

  168. X. Shen et al., AI-assisted network-slicing based next-generation wireless networks. IEEE Open J. Veh. Technol. 1, 45–66 (2020)

    Article  Google Scholar 

  169. 3GPP TS 23.501, System architecture for the 5G system (2020). https://www.3gpp.org/ftp//Specs/archive/23_series/23.501/. Accessed Jan 2021

  170. ITU-T Y.3112 series Y, Global information infrastructure, internet protocol aspects, next-generation networks, internet of things and smart cities (2018). https://www.itu.int/rec/T-REC-Y.3112-201812-I/en. Accessed Jan 2021

  171. A.M. Escolar, J.M. Alcaraz-Calero, P. Salva-Garcia, J.B. Bernabe, Q. Wang, Adaptive network slicing in multi-tenant 5G IoT networks. IEEE Access 9, 14048–14069 (2021)

    Article  Google Scholar 

  172. M.A. Habibi, B. Han, H.D. Schotten, Network slicing in 5G mobile communication: architecture, prot modeling, and challenges, in Proceedings of the 14th International Symposium Wireless Communications System (2017), p. 16

    Google Scholar 

  173. Q. Li, An end-to-end network slicing framework for 5G wireless communication systems (2016). https://arxiv.org/abs/1608.00572. Accessed Jan 2021

  174. O. Sallent, J. Pérez-Romero, R. Ferrús, R. Agustí, On radio access network slicing from a radio resource management perspective. IEEE Wirel. Commun. 24(5), 166–174 (2017)

    Article  Google Scholar 

  175. I.D. Silva, Impact of network slicing on 5G radio access networks. Proc. Eur. Conf. Netw. Commun., 153–157 (2016)

    Google Scholar 

  176. Y.L. Lee, J. Loo, T.C. Chuah, A new network slicing framework for multi-tenant heterogeneous cloud radio access networks. Proc. Int. Conf. Adv. Electr. Electron. Syst. Eng., 414–420 (2016)

    Google Scholar 

  177. J. Ordonez-Lucena et al., Network slicing for 5G with SDN/NFV: concepts, architectures, and challenges. IEEE Commun. Mag. 55(5), 80–87 (2017)

    Article  Google Scholar 

  178. M. Boldi, O. Queseth, P. Marsch, Ö. Bulakci, 5G System Design: Architectural and Functional Considerations and Long Term Research (John Wiley and Sons, Hoboken, 2018)

    Google Scholar 

  179. ITU-T Y.3102, Series Y: Global Information Infrastructure, Internet Protocol Aspects, Next-Generation Networks, Internet of Things and Smart Cities (2018). https://www.itu.int/rec/T-REC-Y.3102/en. Accessed Nov 2021

  180. NGMN Alliance, 5G End-to-End Architecture Framework (2019). https://www.ngmn.org/publications/5g-end-to-end-architecture-framework-v3-0-8.html. Accessed Nov 2021

  181. 5GPPP, AI and ML – Enablers for Beyond 5G Networks (2021). https://5g-ppp.eu/wp-content/uploads/2021/05/AI-MLforNetworks-v1-0.pdf.Accessed Nov 2021

  182. ITU, Architectural framework for machine learning in future networks including IMT-2020 (2019). https://www.itu.int/rec/T-REC-Y.3172-201906-I/en. Accessed Dec 2020

  183. V.P. Kafle, Y. Fukushima, P. Martinez-Julia, T. Miyazawa, Consideration on automation of 5G network slicing with machine learning, in 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K) (2018), pp. 1–8

    Google Scholar 

  184. M.E. Morocho-Cayamcela, H. Lee, W. Lim, Machine learning for 5G/B5G mobile and wireless communications: potential, limitations, and future directions. IEEE Access 7, 137184–137206 (2019)

    Article  Google Scholar 

  185. M.S. Mollel et al., A survey of machine learning applications to handover management in 5G and beyond. IEEE Access 9, 45770–45802 (2021)

    Article  Google Scholar 

  186. J. Kaur, M.A. Khan, M. Iftikhar, M. Imran, Q. Emad Ul Haq, Machine learning techniques for 5G and beyond. IEEE Access 9, 23472–23488 (2021)

    Google Scholar 

  187. M. Kaaviya, S. Deepa, Machine learning approaches for 5G network challenges. Int. J. Res. Eng. Sci. 9(4) (2021)

    Google Scholar 

  188. ITU, Machine learning in future networks including IMT-2020: use cases (2019). https://www.itu.int/rec/T-REC-Y.Sup55-201910-I. Accessed Dec 2020

  189. D. Bega, M. Gramaglia, A. Banchs, V. Sciancalepore, K. Samdanis, X. Costa-Perez, Optimising 5G infrastructure markets: the business of network slicing, in IEEE INFOCOM 2017 – IEEE Conference on Computer Communications (2017), pp. 1–9

    Google Scholar 

  190. D. Bega, M. Gramaglia, M. Fiore, A. Banchs, X. Costa-Perez, DeepCog: cognitive network management in sliced 5G networks with deep learning, in IEEE INFOCOM 2019 – IEEE Conference on Computer Communications (2019), pp. 280–288

    Google Scholar 

  191. Y. Abiko, T. Saito, D. Ikeda, K. Ohta, T. Mizuno, H. Mineno, Flexible resource block allocation to multiple slices for radio access network slicing using deep reinforcement learning. IEEE Access 8, 68183–68198 (2020)

    Article  Google Scholar 

  192. T. Li, X. Zhu, X. Liu, An end-to-end network slicing algorithm based on deep Q-learning for 5G network. IEEE Access 8, 122229–122240 (2020)

    Article  Google Scholar 

  193. G. Kibalya, J. Serrat, J. Gorricho, R. Pasquini, H. Yao, P. Zhang, A reinforcement learning based approach for 5G network slicing across multiple domains, in 2019 15th International Conference on Network and Service Management (CNSM) (2019), pp. 1–5

    Google Scholar 

  194. M.R. Raza, C. Natalino, P. Öhlen, L. Wosinska, P. Monti, Reinforcement learning for slicing in a 5G flexible RAN. J. Lightwave Technol. 37(20), 5161–5169 (2019)

    Article  Google Scholar 

  195. M. Yan, G. Feng, J. Zhou, Y. Sun, Y. Liang, Intelligent resource scheduling for 5G radio access network slicing. IEEE Trans. Veh. Technol. 68(8), 7691–7703 (2019)

    Article  Google Scholar 

  196. G. Sun, Z.T. Gebrekidan, G.O. Boateng, D. Ayepah-Mensah, W. Jiang, Dynamic reservation and deep reinforcement learning based autonomous resource slicing for virtualized radio access networks. IEEE Access 7, 45758–45772 (2019)

    Article  Google Scholar 

  197. S. Troia, R. Alvizu, G. Maier, Reinforcement learning for service function chain reconfiguration in NFV-SDN metro-core optical networks. IEEE Access 7, 167944–167957 (2019)

    Article  Google Scholar 

  198. C. Vallati, A. Virdis, E. Mingozzi, G. Stea, Mobile-edge computing come home connecting things in future smart homes using LTE device-to-device communications. IEEE Consumer Electron. Mag. 5(4), 77–83 (2016)

    Article  Google Scholar 

  199. S. Abdelwahab, B. Hamdaoui, M. Guizani, T. Znati, Replisom: disciplined tiny memory replication for massive IoT devices in LTE edge cloud. IEEE Internet Things J. 3(3), 327–338 (2016)

    Article  Google Scholar 

  200. ETSI, Industry Specification Group (ISG) on Multi-Access Edge Computing (MEC) (2021). https://www.etsi.org/committee/1425-mec. Accessed May 2021

  201. ETSI, ETSI GS MEC 003: Multi-access Edge Computing (MEC); Framework and Reference Architecture (2019). www.etsi.org/deliver/etsi_gs/mec/001_099/003/02.01.01_60/gs_mec003v020101p.pdf. Accessed March 2021

  202. ETSI, ETSI White Paper No. 28; MEC in 5G networks (2018). https://www.etsi.org/images/files/ETSIWhitePapers/etsi_wp28_mec_in_5G_FINAL.pdf. Accessed Mar 2021

  203. ETSI, ETSI GR MEC 031: Multi-access Edge Computing (MEC); MEC 5G Integration (2020). www.etsi.org/deliver/etsi_gr/MEC/001_099/031/02.01.01_60/gr_MEC031v020101p.pdf. Accessed Mar 2021

  204. N. Abbas, Y. Zhang, A. Taherkordi, T. Skeie, Mobile edge computing: a survey. IEEE Internet Things J. 5(1), 450–465 (2018)

    Article  Google Scholar 

  205. Q. Pham et al., A survey of multi-access edge computing in 5G and beyond: fundamentals, technology integration, and state-of-the-art. IEEE Access 8, 116974–117017 (2020)

    Article  Google Scholar 

  206. S. Dario, R. Alex, F. Rui, Multi-Access Edge Computing in Action (CRC Press, Boca Raton, 2020)

    Google Scholar 

  207. ETSI, ETSI GS MEC 010-1: Mobile Edge Computing (MEC); Mobile Edge Management; Part 1: System, host and platform management (2017). https://www.etsi.org/deliver/etsi_gs/mec/001_099/01001/01.01.01_60/gs_mec01001v010101p.pdf. Accessed Mar 2021

  208. ETSI, ETSI GS MEC 010-2: Mobile Edge Computing (MEC); Mobile Edge Management; Part 2: Application lifecycle, rules and requirements management (2017). https://www.etsi.org/deliver/etsi_gs/mec/001_099/01002/01.01.01_60/gs_mec01002v010101p.pdf. Accessed Mar 2021

  209. L. Bonati et al., Open, programmable, and virtualized 5G networks: state-of-the-art and the road ahead. Comput. Netw. 182 (2020)

    Google Scholar 

  210. MATLAB 5G Toolbox (2020). www.mathworks.com/products/5g.html. Accessed Jan 2021

  211. 5G LENA Project on NS-3 (2020). https://5g-lena.cttc.es/. Accessed Jan 2021

  212. Vienna 5G Simulator (2020). www.nt.tuwien.ac.at/research/mobile-communications/vccs/vienna-5g-simulators/. Accessed Jan 2021

  213. Open Air Interface (OAI) (2020). www.openairinterface.org/. Accessed Jan 2021

  214. 5G K-Simulator (2020). http://5gopenplatform.org/main. Accessed Jan 2021

  215. J. Baek et al., 5G K-simulator of flexible, open, modular (FOM) structure and web-based 5G K-simplatform, in 2019 16th IEEE Annual Consumer Communications & Networking Conference (CCNC) (2019), pp. 1–4

    Google Scholar 

  216. F. Kaltenberger, OpenAirInterface 5G Overview, Installation, Usage. OpenAirInterface Workshop 2019 (2019). https://www.openairinterface.org/docs/workshop/8_Fall2019Workshop-Beijing/Training/2019-12-03-KALTENBERGER-1.pdf. Accessed Jan 2021

  217. SCF, 5G FAPI: PHY API Specification (2020). https://scf.io/en/documents/222_5G_FAPI_PHY_API_Specification.php. Accessed Jan 2021

  218. F. Kaltenberger et al., OpenAirInterface: democratizing innovation in the 5G era. Comput. Netw. 176 (2020)

    Google Scholar 

  219. SCF, 5G nFAPI specifications (2020). https://scf.io/en/documents/225_5G_nFAPI_specifications.php. Accessed Jan 2021

  220. Network simulator-3 (2020). https://www.nsnam.org/. Accessed Feb 2021

  221. P. Solis, D4.4 Cognitive MAC Simulation, Evaluation and Optimization. 5G-RANGE Research and Innovation Action (2019). http://5g-range.eu/wp-content/uploads/2018/04/D4.4_final.pdf. Accessed Dec 2020

  222. N. Patriciello, S. Lagen, B. Bojovic, L. Giupponi, An E2E simulator for 5G NR networks, in Elsevier Simulation Modelling Practice and Theory (SIMPAT) (2019)

    Google Scholar 

  223. C. Felber, Prototyping wireless systems with NI SDR and open source stacks (2019). https://www.openairinterface.org/docs/workshop/8_Fall2019Workshop-Beijing/Talks/2019-12-05-FELBER.pdf. Accessed Dec 2020

  224. R. Gupta et al., NS-3-based real-time emulation of LTE testbed using LabVIEW platform for software defined networking (SDN) in CROWD Project. Association for Computing Machinery (2015).

    Google Scholar 

  225. MathWorks, 5G Development with MATLAB. eBook (2020)

    Google Scholar 

  226. Mosaic5G, Enabling Agile 4G/5G Service platforms (2018). https://mosaic5g.io/resources/mosaic5g.pdf. Accessed Jan 2021

  227. 3GPP TR 28.801, Study on management and orchestration of network slicing for next generation network (2018). https://www.3gpp.org/ftp//Specs/archive/28_series/28.801/. Accessed Feb 2021

  228. ONF, Broadband Projects (2021). https://opennetworking.org/onf-broadband-projects/. Accessed Feb 2021

  229. ONF, CORD Project (2021). https://opennetworking.org/cord/. Accessed Feb 2021

Download references

Author information

Authors and Affiliations

  1. Altran Labs, Velizy-Villacoublay, France

    Mohammed Alfaqawi & Mouna Ben Mabrouk

  2. Altran ACS, Saint-Herblain, France

    Martine Gateau, Patrick Huard, Pascal Reungoat, Marie-Christine Le Mercier & Stéphane Davai

Authors
  1. Mohammed Alfaqawi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Martine Gateau
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Patrick Huard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pascal Reungoat
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marie-Christine Le Mercier
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Stéphane Davai
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Mouna Ben Mabrouk
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mohammed Alfaqawi .

Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, North South University,, Dhaka, Bangladesh

    Mohammad Abdul Matin

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Alfaqawi, M. et al. (2023). A Comprehensive Study on 5G: RAN Architecture, Enabling Technologies, Challenges, and Deployment. In: Matin, M.A. (eds) A Glimpse Beyond 5G in Wireless Networks. Signals and Communication Technology. Springer, Cham. https://doi.org/10.1007/978-3-031-13786-0_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-13786-0_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-13785-3

  • Online ISBN: 978-3-031-13786-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation