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Digital twins approach proposition for 5G/6G

Oumaima El Rhazal, Tomader Mazri

Abstract


In order to step toward the next decade with steady pace in terms of mobile networks we need to admit that the advanced technologies enabled in the last decade by 5G mobile networks produced more dimensions for totally new high-performance technologies for the next generation. Truly immersive extended Reality XR, high fidelity mobile hologram and digital replica. The usage of such technologies cannot be achieved only by actual 5G mobile networks. This is because of various problems such as capacity and data rates, but most importantly network coverage, which is one of the challenges mobile networks will be facing in the next few years. In this paper, we will discuss specifically coverage challenges in mobile networks, in addition to the digital twin concept as an important concept in 6G mobile networks, and we will finally propose an approach to deal with network coverage problems based on the 6G service digital twin.


Keywords


digital twin DT; coverage; 6G

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References


1. Al-Falahy N, Alani OY. Technologies for 5G Networks: Challenges and Opportunities.

2. Sanou B. Setting the Scene for 5G: Opportunities & Challenges.

3. Jiang W, Strufe M, Schotten HD. A SON decision-making framework for intelligent management in 5G mobile networks. 2017 3rd IEEE International Conference on Computer and Communications (ICCC). Published online December 2017. doi: 10.1109/compcomm.2017.8322725

4. Ashraf I, Boccardi F, Ho L. SLEEP mode techniques for small cell deployments. IEEE Communications Magazine. 2011, 49(8): 72-79. doi: 10.1109/mcom.2011.5978418

5. Hossain E, Hasan M. 5G cellular: key enabling technologies and research challenges. IEEE Journals & Magazine.

6. Borralho R, Mohamed A, Quddus AU, et al. A Survey on Coverage Enhancement in Cellular Networks: Challenges and Solutions for Future Deployments. IEEE Communications Surveys & Tutorials. 2021, 23(2): 1302-1341. doi: 10.1109/comst.2021.3053464

7. Ouamri MA, Oteşteanu ME, Isar A, et al. Coverage, Handoff and cost optimization for 5G Heterogeneous Network. Physical Communication. 2020, 39: 101037. doi: 10.1016/j.phycom.2020.101037

8. Hernandez-Boussard T, Macklin P, Greenspan EJ, et al. Digital twins for predictive oncology will be a paradigm shift for precision cancer care. Nature Medicine 2021; 27(12): 2065–2066. doi: 10.1038/s41591-021-01558-5

9. Glaessgen E, Stargel D. The Digital Twin Paradigm for Future NASA and U.S. Air Force Vehicles. 53rd AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference&lt, BR&gt, 20th AIAA/ASME/AHS Adaptive Structures Conference&lt, BR&gt, 14th AIAA. Published online April 23, 2012. doi: 10.2514/6.2012-1818

10. Grieves M. Digital twin: manufacturing excellence through virtual factory replication.

11. Tao F, Cheng J, Qi Q, et al. Digital twin-driven product design, manufacturing and service with big data. The International Journal of Advanced Manufacturing Technology. 2017, 94(9-12): 3563-3576. doi: 10.1007/s00170-017-0233-1

12. Söderberg R, Wärmefjord K, Carlson JS, et al. Toward a Digital Twin for real-time geometry assurance in individualized production. CIRP Annals. 2017, 66(1): 137-140. doi: 10.1016/j.cirp.2017.04.038

13. Tao F, Zhang M. Digital Twin Shop-Floor: A New Shop-Floor Paradigm Towards Smart Manufacturing. IEEE Access. 2017, 5: 20418-20427. doi: 10.1109/access.2017.2756069

14. DebRoy T, Zhang W, Turner J, et al. Building digital twins of 3D printing machines. Scripta Materialia. 2017, 135: 119-124. doi: 10.1016/j.scriptamat.2016.12.005

15. Vachalek J, Bartalsky L, Rovny O, et al. The digital twin of an industrial production line within the industry 4.0 concept. 2017 21st International Conference on Process Control (PC). Published online June 2017. doi: 10.1109/pc.2017.7976223

16. Tao F, Qi Q, Wang L, et al. Digital Twins and Cyber–Physical Systems toward Smart Manufacturing and Industry 4.0: Correlation and Comparison. Engineering. 2019, 5(4): 653-661. doi: 10.1016/j.eng.2019.01.014

17. Wright L, Davidson S. How to tell the difference between a model and a digital twin. Advanced Modeling and Simulation in Engineering Sciences. 2020, 7(1). doi: 10.1186/s40323-020-00147-4

18. Neethirajan S, Kemp B. Digital Twins in Livestock Farming. Animals. 2021, 11(4): 1008. doi: 10.3390/ani11041008

19. Zhou G, Zhang C, Li Z, et al. Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. International Journal of Production Research. 2019, 58(4): 1034-1051. doi: 10.1080/00207543.2019.1607978

20. Fuller A, Fan Z, Day C, et al. Digital Twin: Enabling Technologies, Challenges and Open Research. IEEE Access. 2020, 8: 108952-108971. doi: 10.1109/access.2020.2998358

21. Liu Y, Zhang L, Yang Y, et al. A Novel Cloud-Based Framework for the Elderly Healthcare Services Using Digital Twin. IEEE Access. 2019, 7: 49088-49101. doi: 10.1109/access.2019.2909828

22. Bruynseels K, Santoni de Sio F, van den Hoven J. Digital Twins in Health Care: Ethical Implications of an Emerging Engineering Paradigm. Frontiers in Genetics. 2018, 9. doi: 10.3389/fgene.2018.00031

23. VanDerHorn E, Mahadevan S. Digital Twin: Generalization, characterization and implementation. Decision Support Systems. 2021, 145: 113524. doi: 10.1016/j.dss.2021.113524

24. Baruffaldi G, Accorsi R, Manzini R. Warehouse management system customization and information availability in 3pl companies. Industrial Management & Data Systems. 2019, 119(2): 251-273. doi: 10.1108/imds-01-2018-0033

25. Qi Q, Tao F, Hu T, et al. Enabling technologies and tools for digital twin. Journal of Manufacturing Systems. 2021, 58: 3-21. doi: 10.1016/j.jmsy.2019.10.001




DOI: https://doi.org/10.32629/jai.v7i5.1417

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Copyright (c) 2024 Oumaima El Rhazal, Tomader Mazri

License URL: https://creativecommons.org/licenses/by-nc/4.0/