Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions

Oumayma Bouchmal; Bruno Cimoli; Ripalta Stabile; J.J. Vegas Olmos; Idelfonso Tafur Monroy

doi:10.1007/978-3-031-38318-2_48

Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions

Oumayma Bouchmal
, Bruno Cimoli
, Ripalta Stabile
, J.J. Vegas Olmos
, Idelfonso Tafur Monroy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

6 Citations (Scopus)

3 Downloads (Pure)

Abstract

The sixth-generation (6G) wireless networks are envisioned to deliver a paradigm shift in performance, capacity, and complexity compared to the previous generations. The increased complexity, ultra-low latency, and higher data rate requirements of 6G networks require advanced computational capabilities for network optimization, including resource allocation, dynamic slicing, and traffic routing. In this paper, we discuss the need of integrating quantum computing and quantum machine learning for network optimization in 6G.

Original language	English
Title of host publication	Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference
Editors	Rashid Mehmood, Victor Alves, Isabel Praça, Jarosław Wikarek, Javier Parra-Domínguez, Roussanka Loukanova, Ignacio de Miguel, Tiago Pinto, Ricardo Nunes, Michela Ricca
Place of Publication	Cham
Publisher	Springer
Chapter	48
Pages	480-488
Number of pages	9
ISBN (Electronic)	978-3-031-38318-2
ISBN (Print)	978-3-031-38317-5
DOIs	https://doi.org/10.1007/978-3-031-38318-2_48
Publication status	Published - Jul 2023
Event	20th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2023 - University of Minho, Guimarães, Portugal Duration: 12 Jul 2023 → 14 Jul 2023 Conference number: 20 https://www.dcai-conference.net/

Publication series

Name	Lecture Notes in Networks and Systems, LNNS
Publisher	Springer
Volume	741
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	20th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2023
Abbreviated title	DCAI 2023
Country/Territory	Portugal
City	Guimarães
Period	12/07/23 → 14/07/23
Internet address	https://www.dcai-conference.net/

Funding

This work was supported by the EC H2020 MSCA ITN-ETN IoTalentum (GA 953442) project, the ECSEL-JU project BRAINE with grant number 876967 and the Dutch Ministry of Economic Affairs and Climate Policy (EZK), as part of the Quantum Delta NL programme.

Funders	Funder number
Marie Skłodowska‐Curie	GA 953442
Ministerie van Economische Zaken en Klimaat

Keywords

6G
QC
QML
dynamic slicing
optimization
resource allocation
routing

Access to Document

10.1007/978-3-031-38318-2_48

Cite this

Bouchmal, O., Cimoli, B., Stabile, R., Vegas Olmos, J. J., & Tafur Monroy, I. (2023). Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions. In R. Mehmood, V. Alves, I. Praça, J. Wikarek, J. Parra-Domínguez, R. Loukanova, I. de Miguel, T. Pinto, R. Nunes, & M. Ricca (Eds.), Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference (pp. 480-488). (Lecture Notes in Networks and Systems, LNNS; Vol. 741). Springer. https://doi.org/10.1007/978-3-031-38318-2_48

Bouchmal, Oumayma ; Cimoli, Bruno ; Stabile, Ripalta et al. / Quantum-Inspired Network Optimization in 6G : Opportunities, Challenges and Open Research Directions. Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. editor / Rashid Mehmood ; Victor Alves ; Isabel Praça ; Jarosław Wikarek ; Javier Parra-Domínguez ; Roussanka Loukanova ; Ignacio de Miguel ; Tiago Pinto ; Ricardo Nunes ; Michela Ricca. Cham : Springer, 2023. pp. 480-488 (Lecture Notes in Networks and Systems, LNNS).

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abstract = "The sixth-generation (6G) wireless networks are envisioned to deliver a paradigm shift in performance, capacity, and complexity compared to the previous generations. The increased complexity, ultra-low latency, and higher data rate requirements of 6G networks require advanced computational capabilities for network optimization, including resource allocation, dynamic slicing, and traffic routing. In this paper, we discuss the need of integrating quantum computing and quantum machine learning for network optimization in 6G.",

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booktitle = "Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference",

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Bouchmal, O, Cimoli, B , Stabile, R, Vegas Olmos, JJ & Tafur Monroy, I 2023, Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions. in R Mehmood, V Alves, I Praça, J Wikarek, J Parra-Domínguez, R Loukanova, I de Miguel, T Pinto, R Nunes & M Ricca (eds), Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. Lecture Notes in Networks and Systems, LNNS, vol. 741, Springer, Cham, pp. 480-488, 20th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2023, Guimarães, Portugal, 12/07/23. https://doi.org/10.1007/978-3-031-38318-2_48

Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions. / Bouchmal, Oumayma; Cimoli, Bruno ; Stabile, Ripalta et al.
Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. ed. / Rashid Mehmood; Victor Alves; Isabel Praça; Jarosław Wikarek; Javier Parra-Domínguez; Roussanka Loukanova; Ignacio de Miguel; Tiago Pinto; Ricardo Nunes; Michela Ricca. Cham: Springer, 2023. p. 480-488 (Lecture Notes in Networks and Systems, LNNS; Vol. 741).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AB - The sixth-generation (6G) wireless networks are envisioned to deliver a paradigm shift in performance, capacity, and complexity compared to the previous generations. The increased complexity, ultra-low latency, and higher data rate requirements of 6G networks require advanced computational capabilities for network optimization, including resource allocation, dynamic slicing, and traffic routing. In this paper, we discuss the need of integrating quantum computing and quantum machine learning for network optimization in 6G.

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KW - resource allocation

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BT - Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference

A2 - Mehmood, Rashid

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A2 - Praça, Isabel

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A2 - Loukanova, Roussanka

A2 - de Miguel, Ignacio

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PB - Springer

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ER -

Bouchmal O, Cimoli B , Stabile R, Vegas Olmos JJ, Tafur Monroy I. Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions. In Mehmood R, Alves V, Praça I, Wikarek J, Parra-Domínguez J, Loukanova R, de Miguel I, Pinto T, Nunes R, Ricca M, editors, Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference. Cham: Springer. 2023. p. 480-488. (Lecture Notes in Networks and Systems, LNNS). doi: 10.1007/978-3-031-38318-2_48

Quantum-Inspired Network Optimization in 6G: Opportunities, Challenges and Open Research Directions

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