Skip to main content
SpringerLink
Log in

An Overview of 5G and 6G Networks from the Perspective of AI Applications

  • REVIEW PAPER
  • Published:
Journal of The Institution of Engineers (India): Series B Aims and scope Submit manuscript

Abstract

The development of fifth-generation (5G) wireless technology has led to an explosion in the number of connected devices, enabling applications that were previously impossible. However, the emergence of 5G has also exposed limitations that must be overcome for the realization of future applications, and the next-generation network, 6G, is expected to address these limitations. In this review paper, we provide an overview of 5G and 6G networks from the perspective of the applications of Artificial Intelligence (AI). We discuss the benefits and challenges of 5G and AI integration and how 6G is expected to leverage AI to overcome current limitations. The growth of mobile communication tools has been on the rise with the evolution of communications systems. Although the 5G mobile network trials are underway in some areas, research into the 6G standard has picked up speed. Through 6G technology, consumers may have more opportunities to engage with artificial intelligence (AI), expanding their understanding of areas like the Internet of Things (IoT), self-driven cars, and automated or programmed surgery. The extensive application of AI systems requires extremely potent computer systems. This study presented the development of various mobile technologies and wireless communication protocols over time and the future of 5G and 6G communication networks. Overall, this review paper provides insights into the current state of 5G and the potential of 6G to integrate AI and highlights the key challenges and opportunities in this exciting field.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

References

  1. A. Pouttu et al., “6G White Paper on Validation and Trials for Verticals towards 2030’s,” 6G Research Visions, vol. 4, 2020.

  2. K.-C. Chen, T. Zhang, R.D. Gitlin, G. Fettweis, Ultra-low latency mobile networking. IEEE Network 33(2), 181–187 (2018)

    Article  Google Scholar 

  3. C.-Y. Lin, K.-C. Chen, D. Wickramasuriya, S.-Y. Lien, and R. D. Gitlin, “Anticipatory mobility management by big data analytics for ultra-low latency mobile networking,” In 2018 IEEE International Conference on Communications (ICC), 2018, pp. 1–7: IEEE.

  4. E. M. Report, “Mobile data traffic outlook,” Ericsson Mobility Report Data And Forecasts, 2022.

  5. I.F. Akyildiz, H. Guo, Wireless extended reality (XR): challenges and new research directions. ITU J. Future Evol. Technol 3, 1–15 (2022)

    Google Scholar 

  6. J. Clement, “Global mobile data traffic 2017–2022,” Statista 2022, Jul 27, 2022.

  7. W. Saad, M. Bennis, M. Chen, A vision of 6G wireless systems: Applications, trends, technologies, and open research problems. IEEE Network 34(3), 134–142 (2019)

    Article  Google Scholar 

  8. B. Li, Z. Fei, Y. Zhang, UAV communications for 5G and beyond: Recent advances and future trends. IEEE Internet Things J. 6(2), 2241–2263 (2018)

    Article  Google Scholar 

  9. H. Liao et al., Learning-based context-aware resource allocation for edge-computing-empowered industrial IoT. IEEE Internet Things J. 7(5), 4260–4277 (2019)

    Article  Google Scholar 

  10. P. Kumar, Review Paper on Development of Mobile Wireless Technology. J Phys Conf Ser 1979(1), 012024 (2021)

    Article  Google Scholar 

  11. K. Kaur, S. Kumar, A. Baliyan, 5G: a new era of wireless communication. Int. J. Inf. Technol. 12(2), 619–624 (2020)

    Google Scholar 

  12. E.M. Torroglosa-Garcia, J.M.A. Calero, J.B. Bernabe, A. Skarmeta, Enabling roaming across heterogeneous IoT wireless networks: LoRaWAN MEETS 5G. IEEE Access 8, 103164–103180 (2020)

    Article  Google Scholar 

  13. Y. Hao, D. Tian, G. Fortino, J. Zhang, I. Humar, Network slicing technology in a 5G wearable network. IEEE Commun Stand Magaz 2(1), 66–71 (2018)

    Article  Google Scholar 

  14. R. Chataut, R. Akl, Massive MIMO systems for 5G and beyond networks—overview, recent trends, challenges, and future research direction. Sensors 20(10), 2753 (2020)

    Article  Google Scholar 

  15. S. Wijethilaka, M. Liyanage, Survey on network slicing for Internet of Things realization in 5G networks. IEEE Commun Surv Tutor 23(2), 957–994 (2021)

    Article  Google Scholar 

  16. C. Benzaid, T. Taleb, AI-driven zero touch network and service management in 5G and beyond: challenges and research directions. IEEE Network 34(2), 186–194 (2020)

    Article  Google Scholar 

  17. A. Kumari, S. Tanwar, S. Tyagi, N. Kumar, M.S. Obaidat, J.J. Rodrigues, Fog computing for smart grid systems in the 5G environment: challenges and solutions. IEEE Wirel. Commun. 26(3), 47–53 (2019)

    Article  Google Scholar 

  18. J. Varga, A. Hilt, J. Bíró, C. Rotter, and G. Járó, “Reducing operational costs of ultra-reliable low latency services in 5G,” 2018.

  19. M. Katz, P. Pirinen, and H. Posti, “Towards 6G: Getting ready for the next decade,” In 2019 16th international symposium on wireless communication systems (ISWCS), 2019, pp. 714–718: IEEE.

  20. S. Ali et al., New Trends and Advancement in Next Generation Mobile Wireless Communication (6G): A Survey. Wireless Commun Mob Comput 2021, 1–14 (2021)

    Google Scholar 

  21. K.B. Letaief, W. Chen, Y. Shi, J. Zhang, Y.J.A. Zhang, The roadmap to 6G: AI empowered wireless networks. IEEE Commun Magaz 57(8), 84–90 (2019)

    Article  Google Scholar 

  22. M. Wang, T. Zhu, T. Zhang, J. Zhang, S. Yu, W. Zhou, Security and privacy in 6G networks: New areas and new challenges. Dig Commun Netw 6(3), 281–291 (2020)

    Article  Google Scholar 

  23. B. Ji et al., A survey of computational intelligence for 6G: Key technologies, applications and trends. IEEE Trans. Industr. Inf. 17(10), 7145–7154 (2021)

    Article  Google Scholar 

  24. C.-X. Wang, J. Huang, H. Wang, X. Gao, X. You, Y. Hao, 6G wireless channel measurements and models: Trends and challenges. IEEE Veh. Technol. Mag. 15(4), 22–32 (2020)

    Article  Google Scholar 

  25. R.-A. Stoica and G. T. F. de Abreu, “6G: the wireless communications network for collaborative and AI applications,” 2019.

  26. A.M. Al-Saegh, A. Sali, J.S. Mandeep, F.P. Fontán, Channel measurements, characterization, and modeling for land mobile satellite terminals in tropical regions at Ku-band. IEEE Trans. Veh. Technol. 66(2), 897–911 (2016)

    Article  Google Scholar 

  27. W. Khawaja, I. Guvenc, D.W. Matolak, U.-C. Fiebig, N. Schneckenburger, A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles. IEEE Commun Surv Tutor 21(3), 2361–2391 (2019)

    Article  Google Scholar 

  28. F. Clazzer, A. Munari, G. Liva, F. Lazaro, C. Stefanovic, and P. Popovski, “From 5G to 6G: Has the time for modern random access come?,” 2019.

  29. J. Wang, H. Zhou, Y. Li, Q. Sun, Y. Wu, S. Jin, C. Xu, Wireless channel models for maritime communications. IEEE Access 6, 68070–68088 (2018)

    Article  Google Scholar 

  30. C. Seker, M. T. Güneser, and T. Ozturk, “A review of millimeter wave communication for 5G,” In 2018 2nd International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT), 2018, pp. 1–5: Ieee.

  31. D. Bega, M. Gramaglia, M. Fiore, A. Banchs, and 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: IEEE.

  32. A. Thantharate, R. Paropkari, V. Walunj, and C. Beard, “DeepSlice: A deep learning approach towards an efficient and reliable network slicing in 5G networks,” In 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), 2019, pp. 0762–0767: IEEE.

  33. V. P. Kafle, Y. Fukushima, P. Martinez-Julia, and 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: IEEE.

  34. B. Hughes, S. Bothe, H. Farooq, and A. Imran, “Generative adversarial learning for machine learning empowered self organizing 5G networks,” In 2019 international conference on computing, networking and communications (ICNC), 2019, pp. 282–286: IEEE.

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

    Article  Google Scholar 

  36. S. Schwarzmann, C. Cassales Marquezan, M. Bosk, H. Liu, R. Trivisonno, and T. Zinner, “Estimating video streaming QoE in the 5G architecture using machine learning,” In Proceedings of the 4th Internet-QoE Workshop on QoE-based Analysis and Management of Data Communication Networks, 2019, pp. 7–12.

  37. D. Careglio et al., “ALLIANCE Project: Architecting a knowledge-defined 5G-enabled network infrastructure,” In 2018 20th International Conference on Transparent Optical Networks (ICTON), 2018, pp. 1–6: IEEE.

  38. A. Yazar and H. Arslan, “Selection of waveform parameters using machine learning for 5G and beyond,” In 2019 IEEE 30th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2019, pp. 1–6: IEEE.

  39. J. Ali-Tolppa, S. Kocsis, B. Schultz, L. Bodrog, and M. Kajo, “Self-healing and resilience in future 5G cognitive autonomous networks,” In 2018 ITU Kaleidoscope: Machine Learning for a 5G Future (ITU K), 2018, pp. 1–8: IEEE.

  40. M. Mozaffari, A.T.Z. Kasgari, W. Saad, M. Bennis, M. Debbah, Beyond 5G with UAVs: foundations of a 3D wireless cellular network. IEEE Trans. Wireless Commun. 18(1), 357–372 (2018)

    Article  Google Scholar 

  41. S. Niknam, H.S. Dhillon, J.H. Reed, Federated learning for wireless communications: motivation, opportunities, and challenges. IEEE Commun. Mag. 58(6), 46–51 (2020)

    Article  Google Scholar 

  42. B. McMahan, E. Moore, D. Ramage, S. Hampson, and B. A. y Arcas, “Communication-efficient learning of deep networks from decentralized data,” In Artificial intelligence and statistics, 2017, pp. 1273–1282: PMLR.

  43. K. Yang, Y. Shi, and Z. Ding, “Low-rank optimization for data shuffling in wireless distributed computing,” In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018, pp. 6343–6347: IEEE.

  44. S. Dang, O. Amin, B. Shihada, M.-S. Alouini, What should 6G be? Nat Electron 3(1), 20–29 (2020)

    Article  Google Scholar 

  45. L. Zhang, Y.-C. Liang, D. Niyato, 6G visions: mobile ultra-broadband, super internet-of-things, and artificial intelligence. China Commun 16(8), 1–14 (2019)

    Article  Google Scholar 

  46. A. Al-Kinani, C.-X. Wang, L. Zhou, W. Zhang, Optical wireless communication channel measurements and models. IEEE Commun Surv 20(3), 1939–1962 (2018)

    Article  Google Scholar 

  47. C. Seker, M.T. Guneser, H. Arslan, Millimeter-wave propagation modeling and characterization at 32 GHz in indoor office for 5G networks. Int J RF Microw Comput Aid Eng 30(12), e22455 (2020)

    Article  Google Scholar 

  48. H. Ghorbani, M. S. Mohammadzadeh, and M. H. Ahmadzadegan, “Modeling for malicious traffic detection in 6G next generation networks,” In 2020 International Conference on Technology and Entrepreneurship-Virtual (ICTE-V), 2020, pp. 1–6: IEEE.

  49. F. Tariq, M.R. Khandaker, K.-K. Wong, M.A. Imran, M. Bennis, M. Debbah, A speculative study on 6G. IEEE Wirel. Commun. 27(4), 118–125 (2020)

    Article  Google Scholar 

  50. B. Barakat et al., 6G opportunities arising from internet of things use cases: a review paper. Future Internet 13(6), 159 (2021)

    Article  Google Scholar 

  51. F. Al-Turjman, J.P. Lemayian, Intelligence, security, and vehicular sensor networks in internet of things (IoT)-enabled smart-cities: An overview. Comput Electric Eng 87, 106776 (2020)

    Article  Google Scholar 

  52. X. Fang, W. Feng, T. Wei, Y. Chen, N. Ge, C.-X. Wang, 5G embraces satellites for 6G ubiquitous IoT: Basic models for integrated satellite terrestrial networks. IEEE Internet Things J. 8(18), 14399–14417 (2021)

    Article  Google Scholar 

  53. Mostafa Chowdhury, Md. Shahjalal, Shakil Ahmed, Yeong Min Jang, 6G wireless communication systems: applications, requirements, technologies, challenges, and research directions. IEEE Open J Commun Soc (2020). https://doi.org/10.1109/OJCOMS.2020.3010270

    Article  Google Scholar 

Download references

Funding

The authors declare that no fund was received for a said work.

Author information

Authors and Affiliations

  1. E&TC Department, Cummins College of Engineering for Women, Pune, 411052, India

    Ashok Khedkar, Sandeep Musale, Ganesh Padalkar, Ravikant Suryawanshi & Shashikant Sahare

Authors
  1. Ashok Khedkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sandeep Musale
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ganesh Padalkar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ravikant Suryawanshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Shashikant Sahare
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ashok Khedkar.

Ethics declarations

Conflicts of interest

The authors declare that there is no conflict of interest regarding the publication of this article.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Khedkar, A., Musale, S., Padalkar, G. et al. An Overview of 5G and 6G Networks from the Perspective of AI Applications. J. Inst. Eng. India Ser. B 104, 1329–1341 (2023). https://doi.org/10.1007/s40031-023-00928-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40031-023-00928-6

Keywords

Search

Navigation