Digital Twin for Enhanced Resource Allocation in 6G Non-Terrestrial Networks

Non-terrestrial networks (NTNs) are poised to play an important role in the future communication landscape, particularly with the advent of 6G technology. This article explores the integration of digital twin (DT) technology with 6G NTNs to enhance resource allocation and network management. We outline the vision and architecture for developing DT-NTNs, discussing key integration challenges such as data freshness, computational power, reliable interconnections, interoperability, and data security procedures. Various enabling technologies are also presented to facilitate integration and overcome these challenges. Moreover, a case study demonstrates the practical application of artificial intelligence (AI) and learning algorithms within DT-NTNs for optimizing network resources. Through these efforts, this article aims to provide insights and guidelines for developing highly intelligent and dynamic non-terrestrial communication systems in the era of 6G technology, particularly by proposing a novel DT-NTN-based resource allocation approach, and demonstrating the effectiveness of AI-driven optimization.

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Publication Details

Journal
IEEE Communications Magazine
Published
2024-11-04
DOI
https://doi.org/10.1109/mcom.001.2400211
Citations
9
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
3.14

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article

Digital Twin for Enhanced Resource Allocation in 6G Non-Terrestrial Networks

Madyan Alsenwi, Symeon Chatzinotas, Junaid ur Rehman, Eva Lagunas et al.
9 citations
IEEE Communications Magazine
Software-Defined Networks and 5G
3.14
article

Digital Twin for Enhanced Resource Allocation in 6G Non-Terrestrial Networks

Madyan Alsenwi, Symeon Chatzinotas, Junaid ur Rehman, Eva Lagunas, Hayder Al-Hraishawi
article en
9 citations

Abstract

Non-terrestrial networks (NTNs) are poised to play an important role in the future communication landscape, particularly with the advent of 6G technology. This article explores the integration of digital twin (DT) technology with 6G NTNs to enhance resource allocation and network management. We outline the vision and architecture for developing DT-NTNs, discussing key integration challenges such as data freshness, computational power, reliable interconnections, interoperability, and data security procedures. Various enabling technologies are also presented to facilitate integration and overcome these challenges. Moreover, a case study demonstrates the practical application of artificial intelligence (AI) and learning algorithms within DT-NTNs for optimizing network resources. Through these efforts, this article aims to provide insights and guidelines for developing highly intelligent and dynamic non-terrestrial communication systems in the era of 6G technology, particularly by proposing a novel DT-NTN-based resource allocation approach, and demonstrating the effectiveness of AI-driven optimization.

IEEE Communications MagazineVol. 63(3)
University of Luxembourg (LU)
Fonds National de la Recherche Luxembourg
Openalex Percentile: Top 8%
Software-Defined Networks and 5G
3.14
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