Energy efficiency optimisation in massive multiple‐input, multiple‐output network for 5G applications using new quantum genetic algorithm
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Published:2023-11-14
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Volume:
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ISSN:2047-4954
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Container-title:IET Networks
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language:en
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Short-container-title:IET Networks
Author:
Sabaawi Abdulbasit M. A.12ORCID,
Almasaoodi Mohammed R.13,
El Gaily Sara1,
Imre Sándor1
Affiliation:
1. Department of Networked Systems and Services Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary
2. College of Electronics Engineering Ninevah University Mosul Iraq
3. Kerbala University Kerbala Iraq
Abstract
AbstractDevising efficient optimisation methods has been a subject of great research attention since current evolving trends in communication networks, machine learning, and other cutting‐edge systems that need a fast and accurate optimised computational model. Classical computers became incapable of handling new optimisation problems posed by newly emerging trends. Quantum optimisation algorithms appear as alternative solutions. The existing bottleneck that restricts the use of the newly developed quantum strategies is the limited qubit size of the available quantum computers (the size of the most recent universal quantum computer is 433 qubits). A new quantum genetic algorithm (QGA) is proposed that handles the presented problem. A quantum extreme value searching algorithm and quantum blind computing framework are utilised to extend the search capabilities of the GA. The quantum genetic strategy is exploited to maximise energy efficiency at full spectral efficiency of massive multiple‐input, multiple‐output (M‐MIMO) technology as a toy example for pointing out the efficiency of the presented quantum strategy. The authors run extensive simulations and prove how the presented quantum method outperforms the existing classical genetic algorithm.
Publisher
Institution of Engineering and Technology (IET)
Subject
Control and Optimization,Management Science and Operations Research,Computer Networks and Communications
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