Quantum-inspired evolutionary algorithms for NOMA user pairing

Narottama, Bhaskara; Hendraningrat, Denny Kusuma; Shin, Soo Young

doi:10.1016/j.icte.2022.01.014

Cited by 10 publications

(4 citation statements)

References 29 publications

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“…Some other recent works have also shown the applicability of quantum algorithms for computation complexity reduction in ML MUD problems for multiple access schemes including OFDMA, CDMA, and SDMA [165, 166]. Quantum algorithms are also shown to provide enhanced performance for joint channel estimation and MUD for non‐orthogonal multiple access (NOMA) wireless communication systems [167, 168]. The authors of Ref.…”

Section: Quantum Information Technologies In 6g Networkmentioning

confidence: 99%

“…Quantum neural networks (QNNs) are hybrid classicalquantum ML models that are composed of parametrised quantum circuits (Ansatz) and classical feedforward neural networks that are trained iteratively by minimising a cost function [156]. Recent studies have investigated the applicability of QNNs to reduce training and inference time complexity for wireless resource allocation problems [168,188,189]. QNNs have also been investigated for cognitive radio spectrum sensing [190], CDMA MUD [191], and network traffic forecasting [192].…”

Section: Quantum Machine Learning For 6gmentioning

confidence: 99%

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The quantum internet: A synergy of quantum information technologies and 6G networks

Rozenman,

Kundu,

Liu

et al. 2023

IET Quantum Communication

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The quantum internet is a cutting‐edge paradigm that uses the unique characteristics of quantum technology to radically alter communication networks. This new network type is expected to collaborate with 6G networks, creating a synergy that will fundamentally alter how we communicate, engage, and trade information. The improved security, increased speed, and increased network capacity of the quantum internet will lead to the emergence of a broad variety of new applications and services. The current state of quantum technology and its integration with 6G networks are summarised in this study, with an emphasis on the key challenges and untapped possibilities. The main goal is to get knowledge about how the quantum internet might impact communication in the future and alter several economic and societal sectors.

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Section: Quantum Information Technologies In 6g Networkmentioning

confidence: 99%

Section: Quantum Machine Learning For 6gmentioning

confidence: 99%

The quantum internet: A synergy of quantum information technologies and 6G networks

Rozenman,

Kundu,

Liu

et al. 2023

IET Quantum Communication

View full text Add to dashboard Cite

show abstract

“…Fig. 4: A particular result of using quantum-based optimization for NOMA beam assignment [81]. In the figure, d µ denotes normalised user's distance to the base station.…”

Section: Quantum Optimization For Future Wireless Communicationmentioning

confidence: 99%

Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions

Duong

Ansere

Narottama

et al. 2022

IEEE Open J. Veh. Technol.

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Quantum computing is envisaged as an evolving paradigm for solving computationally complex optimization problems with a large-number factorization and exhaustive search. Recently, there has been a proliferation growth of the size of multi-dimensional datasets, the input-output space dimensionality, and data structures. Hence, the conventional machine learning approaches in data training and processing face a huge limited computing capabilities to support the sixthgeneration (6G) networks with highly dynamic applications and services. Under this regard, the fast developing quantum computing with machine learning (QML) for 6G networks is investigated. QML algorithms can significantly enhanced the processing efficiency and exponentially computational speed-up for effective quantum data representation and superposition framework, highly capable of guaranteeing high data storage and secured communications. We present the state-of-the-art in quantum computing and provide comprehensive overviews through machine learning approaches for their applications in the 6G networks. Furthermore, we introduce quantum-inspired machine learning applications for 6G networks, considering their enabling technologies and potential challenges. Finally, some dominating research issues and future research directions for the quantum-inspired machine learning in 6G networks are elaborated.

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“…In general, the quantum-inspired optimisation employs vectors that represents quantum bits and assumes quantum-based mechanics such as quantum superposition [56]. As an example of this approach, an elitist quantum evolutionary algorithm can be employed to optimise user pairing in non-orthogonal multiple access [57]. Here, the optimisation solution is presented as an array of "qubit" vectors.…”

Section: E Quantum-inspired Optimisation Problems and Algorithmsmentioning

confidence: 99%

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

Duong

Nguyen

Narottama

et al. 2022

IEEE Open J. Commun. Soc.

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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 optimisation (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 optimisation 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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Quantum-inspired evolutionary algorithms for NOMA user pairing

Cited by 10 publications

References 29 publications

The quantum internet: A synergy of quantum information technologies and 6G networks

The quantum internet: A synergy of quantum information technologies and 6G networks

Quantum-Inspired Machine Learning for 6G: Fundamentals, Security, Resource Allocations, Challenges, and Future Research Directions

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

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