Digital twin for 5G and beyond
Nguyen, Huan X. ORCID: https://orcid.org/0000-0002-4105-2558, Trestian, Ramona
ORCID: https://orcid.org/0000-0003-3315-3081, To, Duc and Tatipamula, Mallik
(2021)
Digital twin for 5G and beyond.
IEEE Communications Magazine, 59
(2)
.
pp. 10-15.
ISSN 0163-6804
[Article]
(doi:10.1109/MCOM.001.2000343)
|
PDF
- Final accepted version (with author's formatting)
Download (1MB) | Preview |
Abstract
Although many countries have started the initial phase of rolling out 5G, it is still in its infancy with researchers from both academia and industry facing the challenges of developing to its full potential. With the support of Artificial Intelligence, development of digital transformation through the notion of a ‘Digital Twin’ has been taking off in many industries such as smart manufacturing, oil & gas, constructions, bio-engineering, and automotive. However, Digital Twins remain relatively new for 5G networks, despite the obvious potential in helping develop and deploy the complex 5G environment. This paper looks into these topics and discusses how Digital Twin could be a powerful tool to fulfil the potentials of 5G networks and beyond.
Item Type: | Article |
---|---|
Research Areas: | A. > School of Science and Technology > Design Engineering and Mathematics |
Item ID: | 31282 |
Notes on copyright: | © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Useful Links: | |
Depositing User: | Ramona Trestian |
Date Deposited: | 29 Oct 2020 11:17 |
Last Modified: | 29 Nov 2022 18:00 |
URI: | https://eprints.mdx.ac.uk/id/eprint/31282 |
Actions (login required)
![]() |
View Item |
Statistics
Additional statistics are available via IRStats2.