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2025-03-24
Biomedical Antenna Design Optimization Using Multi-Objective Inverse Neural Networks
By
Progress In Electromagnetics Research C, Vol. 154, 47-59, 2025
Abstract
A new approach based on an Inverse Artificial Neural Network (IANN) for Multi-Objective Antenna Design is presented in this paper. The network sets the geometrical variables as the output and uses three antenna performances as inputs. The proposed ANN model is structured into two distinct parts: In the first part, three autonomous branches establish the correlation among S-parameters, gain, specific absorption rate (SAR), and antenna geometric variables. The outputs of these branches are used as inputs in the second part to derive a distinctive solution for these geometric variables. The proposed antenna dimensions are 20x24x1.58 mm3, an ultra- wide-band of 4.1 GHz to 8.7 GHz is achieved in free space and on human tissue which coincides with the 5.8 GHz ISM band. Body temperature and specific absorption rate are simulated using the suggested rectangular patch antenna, The resulting optimized antenna holds promising potential for biomedical applications.
Citation
Rania Ibtissam Ben Melouka, Yamina Tighilt, Chemseddine Zebiri, Kamil Karaçuha, Abdelhak Ferhat Hamida, Arwa Mashat, and Nail Alaoui, "Biomedical Antenna Design Optimization Using Multi-Objective Inverse Neural Networks," Progress In Electromagnetics Research C, Vol. 154, 47-59, 2025.
doi:10.2528/PIERC25012506
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