Computational Intelligence-Based Methodology for Antenna Development

• Published in: IEEE access 2022, Vol.10, p.1860-1870
• Main Authors: Melo, Marcello Caldano De, Santos, Pedro Buarque, Faustino, Everaldo, Bastos-Filho, Carmelo J. A., Cerqueira Sodre, Arismar
• Format: Article
• Language: English
• Subjects: Antenna design; Antennas; Antennas design; Artificial intelligence; Artificial neural networks; Back propagation; Back propagation networks; computational intelligence; Computational modeling; Design optimization; Dipole antennas; Evolutionary algorithms; Genetic algorithms; Heuristic methods; Impedance matching; machine learning; Mathematical models; Methodology; multi-objective optimization; Multilayer perceptrons; Multiple objective analysis; Optimization; Reflector antennas; Sorting algorithms; Training
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3137198

The antenna design is a challenging task, which might be time-consuming using conventional computational methods that typically require high computational capability, due to the need for several sweeps and re-running processes. This work proposes an efficient and accurate computational intelligence-based methodology for the antenna design and optimization. The computational technical solution consists of a surrogate model application, composed of a Multilayer Perceptron (MLP) artificial neural network with backpropagation for the regression process. Combined with the surrogate model, two multiobjective optimization meta-heuristic strategies, Non-dominated Sorting Genetic Algorithm (NSGA-II) and Multiobjective Evolutionary Algorithm based on Decomposition (MOEA/D), are used to overcome the mentioned issues from the traditional antenna design method. A study of case considering a dipole antenna for the 3.5 GHz 5G band is reported, as proof of the proposed methodology concept. Comparisons of antenna impedance matching obtained by the proposed methodology, numerical full-wave results from ANSYS HFSS and experimental result from the antenna prototype are performed for demonstrating its applicability and effectiveness for antenna development.