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Y. Cheng and M. Matloubian, “Parameter Extraction of Accurate and Scaleable Substrate Resistance Components in RF MOS-FETs,” IEEE Electron Device Letters, Vol. 23, No. 4, 2002, pp. 221-223. doi:10.1109/55.992845

has been cited by the following article:

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

  AUTHORS: Jun Liu, Marissa Condon

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

  JOURNAL NAME: Circuits and Systems, Vol.2 No.2, March 28, 2011

  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.