Archivio Istituzionale della RicercaThis papers presents the design and optimization of multiple-input and multiple-output (MIMO) antennas through intelligent methods namely as: surrogate modeling. The optimization process is performed automatically with the combination of Microwave Studio (Dassault Systèmes) and MATLAB numerical analyzer. The proposed optimization method aims to find the optimal solution for the total active reflection coefficient (TARC) specification, S 11 , and S 12 by using shallow neural network. This methodology leads to efficiently size the design parameters of MIMO antenna and to optimize S-parameters and TARC specification jointly. To validate the proposed method, an ultra wideband MIMO antenna in the frequency band of 3.1 GHz to 10.6 GHz is designed and optimized.
Surrogate Modeling for Designing and Optimizing MIMO Antennas / Kouhalvandi, Lida; Matekovits, Ladislau. - ELETTRONICO. - (2022), pp. 1540-1541. (Intervento presentato al convegno 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI) tenutosi a Denver, CO, USA nel 10-15 July 2022) [10.1109/AP-S/USNC-URSI47032.2022.9886514].
Surrogate Modeling for Designing and Optimizing MIMO Antennas
Matekovits, Ladislau
2022
Abstract
This papers presents the design and optimization of multiple-input and multiple-output (MIMO) antennas through intelligent methods namely as: surrogate modeling. The optimization process is performed automatically with the combination of Microwave Studio (Dassault Systèmes) and MATLAB numerical analyzer. The proposed optimization method aims to find the optimal solution for the total active reflection coefficient (TARC) specification, S 11 , and S 12 by using shallow neural network. This methodology leads to efficiently size the design parameters of MIMO antenna and to optimize S-parameters and TARC specification jointly. To validate the proposed method, an ultra wideband MIMO antenna in the frequency band of 3.1 GHz to 10.6 GHz is designed and optimized.
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Surrogate_Modeling_for_Designing_and_Optimizing_MIMO_Antennas.pdf
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AP_S_2022_Conference__USA_update_affilication.pdf
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Descrizione: Surrogate_Modeling_for_Designing_and_Optimizing_MIMO_Antennas
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https://hdl.handle.net/11583/2971608