Quantum Computing-Assisted 6G Networks: Use Cases and Future Opportunities

Sixth Generation (6G) communication networks are anticipated to advance the fifth generation technologies as well as introduce new revolutionary technologies to deliver aggressive data rates, end-to-end latency, reliability, energy efficiency, security, network capacity, and mobility requirements of the future innovative applications. To deliver these demands, ultra-fast and secure computing capability for processing a huge amount of data, application-related tasks, and resource management algorithms will be required. Many 6G applications will use advanced learning techniques that work on large data sets and their working can be made more efficient with the help of Quantum Computing (QC) instead of conventional classical computing. In this paper, we provide an overview of QC and 6G networks and highlight the benefit of integrating these two technologies. We briefly review the recent work and present a framework for QC-assisted 6G networks. We also discuss four use cases of QC in 6G networks, including quick task offloading, fast optimization algorithm results, efficient machine learning techniques, and improved security. Finally, we discuss several open challenges of using QC in the context of 6G network applications.

Authors

Publication Details

Journal
Tsinghua Science & Technology
Published
2025-08-05
DOI
https://doi.org/10.26599/tst.2024.9010118
Citations
2
Primary Topic
Molecular Communication and Nanonetworks
Type
article
Field-Weighted Citation Impact
1.35
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Quantum Computing-Assisted 6G Networks: Use Cases and Future Opportunities

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article

Quantum Computing-Assisted 6G Networks: Use Cases and Future Opportunities

Lewis Nkenyereye, Giancarlo Fortino, Syed Junaid Nawaz, Kapal Dev, Muhammad Awais Javed, Jawad Mirza
article en
2 citations

Abstract

Sixth Generation (6G) communication networks are anticipated to advance the fifth generation technologies as well as introduce new revolutionary technologies to deliver aggressive data rates, end-to-end latency, reliability, energy efficiency, security, network capacity, and mobility requirements of the future innovative applications. To deliver these demands, ultra-fast and secure computing capability for processing a huge amount of data, application-related tasks, and resource management algorithms will be required. Many 6G applications will use advanced learning techniques that work on large data sets and their working can be made more efficient with the help of Quantum Computing (QC) instead of conventional classical computing. In this paper, we provide an overview of QC and 6G networks and highlight the benefit of integrating these two technologies. We briefly review the recent work and present a framework for QC-assisted 6G networks. We also discuss four use cases of QC in 6G networks, including quick task offloading, fast optimization algorithm results, efficient machine learning techniques, and improved security. Finally, we discuss several open challenges of using QC in the context of 6G network applications.

Tsinghua Science & Technology
Openalex Percentile: Top 18%
Molecular Communication and Nanonetworks
1.35
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