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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
Abstract
Design of modern antenna structures is a challenging endeavor. It is laborious, and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the devel-opment of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating suitability of particular geometric setups, typical antenna development requires many weeks and significant involvement of a human expert. The same reasons only allow the designer to try out a very limited number of options in terms of antenna geometry arrangements. Automated topology development and dimension sizing is therefore of high interest, especially from industry perspective where time-to-market and expert-related ex-penses are of paramount importance. This paper discusses a novel approach to unsupervised specification-driven design of planar antennas. The presented methodology capitalizes on a flexi-ble and scalable antenna parameterization, which enables realization of complex geometries while maintaining reasonably small parameter space dimensionality. A customized nature-inspired al-gorithm is employed to carry out space exploration and identification of a quasi-optimum antenna topology in a global sense. A fast gradient-based procedure is then incorporated to fine tune an-tenna dimensions. The design framework works entirely in a black-box fashion with the only in-put being design specifications, and optional constraints, e.g., concerning the structure size. Nu-merous illustration case studies demonstrate the capability of the presented technique to generate unconventional antenna topologies of satisfactory performance using reasonable computational budgets, and with no human expert interaction necessary whatsoever.
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Authors (7)
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Weiping Dou
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Peter Renner
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Andrew Cohen
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Yuandong Tian
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Jiang Zhu
Cite as
Full text
- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/electronics12163462
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Details
- Category:
- Articles
- Type:
- artykuły w czasopismach
- Published in:
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Electronics
no. 12,
ISSN: 2079-9292 - Language:
- English
- Publication year:
- 2023
- Bibliographic description:
- Kozieł S., Dou W., Renner P., Cohen A., Tian Y., Zhu J., Pietrenko-Dąbrowska A.: On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices// Electronics -Vol. 12,iss. 16 (2023), s.1-32
- DOI:
- Digital Object Identifier (open in new tab) 10.3390/electronics12163462
- Sources of funding:
-
- COST_FREE
- Verified by:
- Gdańsk University of Technology
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