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Quantum-Inspired Real-Time Optimization for 6G Networks: Opportunities, Challenges, and the Road Aheadopen access

Authors
Duong, Trung Q.Nguyen, Long D.Narottama, BhaskaraAnsere, James AduDang Van HuynhShin, Hyundong
Issue Date
Aug-2022
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Quantum computing; Optimization; 6G mobile communication; Computers; Quantum mechanics; Real-time systems; Qubit; Quantum communications; real-time optimization; resource allocation; 6G networks
Citation
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, v.3, pp 1347 - 1359
Pages
13
Journal Title
IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY
Volume
3
Start Page
1347
End Page
1359
URI
https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/28403
DOI
10.1109/OJCOMS.2022.3195219
ISSN
2644-125X
2644-125X
Abstract
It is envisioned that 6G, unlike its predecessor 5G, will depart from connected machines and connected people to connected intelligence. The main goal of 6G networks is to support massive connectivity for time-sensitive and computation-sensitive services in mission-critical applications. The creation of real-time optimization (RTO) enabled by the fast growing data analytic and machine learning will seize the opportunities for 6G wireless networks to support such immersive services such as virtual reality (VR), augmented reality (AR), mixed reality (MR), and tactile Internet. Recently, with the rapid development of quantum computers, quantum-inspired optimization and machine learning algorithms have been exploited as efficient solutions for future wireless networks. In this article, we provide a comprehensive view on the new concept of quantum-inspired RTO and its application to the optimal resource allocation for 6G wireless networks. Our main contributions are to introduce some of the initial research results and introduce the potentiality of quantum-inspired RTO on some 6G emerging technologies. Not only do we review the fundamental principles; we also explore the challenges and opportunities of this exciting research direction.
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