A Scalable Model of the Substrate Network in Deep n-Well RF MOSFETs with Multiple Fingers

Jun Liu, Marissa Condon

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DOI: 10.4236/cs.2011.22014                

Abstract

A novel scalable model of substrate components for deep n-well (DNW) RF MOSFETs with different number of fingers is presented for the first time. The test structure developed in [1] is employed to directly access the characteristics of the substrate to extract the different substrate components. A methodology is developed to directly extract the parameters for the substrate network from the measured data. By using the measured two-port data of a set of nMOSFETs with different number of fingers, with the DNW in grounded and float configuration, respectively, the parameters of the scalable substrate model are obtained. The method and the substrate model are further verified and validated by matching the measured and simulated output admittances. Excellent agreement up to 40 GHz for configurations in common-source has been achieved.

Keywords

Deep N-Well (DNW), RF Mosfets, Substrate Network, Scalable Model

Conflicts of Interest

The authors declare no conflicts of interest.

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