Microwave neural modeling for silicon FinFET varactors

The FinFET architecture is currently attracting increasing attention to enable further downscaling of the complementary metal-oxide-semiconductor CMOS technology. The interest towards the FinFET technology for microwave applications is not only limited to transistors but extended also to varactors. Therefore, there is a need for efficient and accurate varactor models in the high-frequency range. In this paper, an artificial neural network-based behavioral model of varactors fabricated in advanced FinFET technology is proposed. The model is developed and verified by comparing measured and simulated scattering parameters up to 50GHz. The extracted model can reproduce very well the measured behavior of the tested varactor before and after applying the de-embedding procedure based on open dummy structure. Copyright © 2014 John Wiley & Sons, Ltd.

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