Faculty of Electronic Engineering, Niš, Serbia

Faculty of Electronic Engineering, Niš, Serbia

Faculty of Electronic Engineering, Niš, Serbia

Faculty of Electronic Engineering, Niš, Serbia

Fondazione Bruno Kessler (FBK), Trento, Italy

Fondazione Bruno Kessler (FBK), Trento, Italy

The paper is available at the following link: PDF

Abstract:

This paper presents an efficient approach for the analysis of a W-band RF-MEMS switch based on an artificial neural network (ANN) model of the switch return and insertion losses. The analysis is performed over the 92–95 GHz frequency range, with particular emphasis on the influence of the switch recess dimension. In the proposed ANN modeling approach, the recess dimension is used as the primary input parameter. Two separate ANN models are employed to capture the frequency dependence of the return and insertion losses. Moreover, a power flow analysis is carried out by converting the modeled return and insertion losses into reflected, transmitted, and absorbed power components. The developed ANN model enables fast and accurate evaluation of loss characteristics and power distribution, facilitating efficient parametric studies and design optimization of W-band RF-MEMS switches.

Keywords:

Artificial Neural Networks, Insertion Loss, Return Loss, RF-MEMS Switch, Power.

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