首页|Machine Learning Based on Antennas Modeling for 5G and 6G Communication Systems: A Systematic Review

Machine Learning Based on Antennas Modeling for 5G and 6G Communication Systems: A Systematic Review

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  • NETL
  • NSTL
  • Wiley
Artificial intelligence (AI)-aidedcommunications have gained significant traction in recent years due to the widespreadapplication of machine learning (ML) and deep learning (DL) machines with algorithms to solve math problems in wirelesscommunications. This study offers an overview of the use of ML models in antenna design and optimization. Thisincorporates DL on ML frameworks, categories, and structure to get practical and broad insights using ML techniques forhigh throughput, quick data analysis, and prediction. This article also comprehensively reviews recent research papers onantenna design via ML. This includes an analysis of several ML algorithms that have been applied to produce antenna parameterssuch as the reflection coefficient (S-parameters),efficiency and gain values, and radiation patterns of the antennas.However, the current antenna design's structure, variables, and external factors remain complex. In addition, the expenseof time and processing resources is inescapable and unacceptable to most designers. ML-basedantennas have been createdto increase antenna modeling efficiency and accuracy to solve these challenges. Techniques for modeling data may be usedto predict the performance of an antenna for a certain set of antenna factors of design. As a result, this study highlights themost sophisticated applied ML techniques that have been presented to increase antenna modeling efficiency and accuracy.The results demonstrate that AI, ML, and DL may minimize simulation needs, predict antenna behavior, and reduce timewith high accuracy.

antenna design optimizationantenna modelingartificial intelligenceCSTdeep learning machinesHFSSmachine learning algorithmstraining techniques

Karrar Shakir Muttair、Oras Ahmed Shareef、Hazeem Baqir Taher

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Department of Computer Engineering, Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq||Nanotechnology andAdvanced Materials Research Unit, Faculty of Engineering, University of Kufa, Najaf, Iraq

Department of Computer Engineering, Electrical Engineering Technical College, Middle Technical University, Baghdad, Iraq||Department of Medical Devices Technical Engineering,Al-AyenIraqi University, AUIQ, Nasiriyah, Iraq

Department of Computer Science, College of Education for Pure Sciences, Thi-QarUniversity,Nasiriyah, Iraq

2025

10.1002/dac.70105

International journal of communication systems

International journal of communication systems

ISSN：1099-1131
年,卷(期)：2025.38(9)
  • 105