Power Optimization of Massive MIMO Using Quantum Genetic Algorithm

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Abstract
The massive Multiple-Input Multiple-Output (MIMO) is key enabling technology for the 5G and 6G cellular technologies, which allows dramatically improving the energy efficiency of the network, as well as increasing the transmission bit rate. In this paper. We developed a new quantum genetic algorithm for handling non-constrained objective functions. The study aims to compare the performance of the classical genetic algorithm and its newly extended quantum version in minimizing the overall transmit power of the downlink massive MIMO system. In terms of the total number of performed generations and total transmit power, a simulation environment was used to demonstrate the efficiency of the quantum genetic strategy versus the classical one.- Title
- Power Optimization of Massive MIMO Using Quantum Genetic Algorithm
- Author
- Almasaoodi, Mohammed
- Sabaawi, Abdulbasit
- El Gaily, Sara
- Imre, Sándor
- Date of issue
- 2023
- Access level
- Open access
- Copyright owner
- Szerző
- Conference title
- 1st Workshop on Intelligent Infocommunication Networks, Systems and Services (WI2NS2)
- Conference place
- Budapest
- Conference date
- 2023.02.07
- Language
- en
- Page
- 89 - 94
- Subject
- genetic algorithm, massive MIMO, quantum computing, quantum extreme value searching algorithm, transmit power
- Version
- Post print
- Identifiers
- DOI: 10.3311/WINS2023-016
- Title of the container document
- 1st Workshop on Intelligent Infocommunication Networks, Systems and Services
- ISBN, e-ISBN
- 978-963-421-902-6
- Document type
- Konferenciaközlemény
- Document genre
- Konferenciacikk
- University
- Budapest University of Technology and Economics
- Faculty
- Faculty of Electrical Engineering and Informatics