DocumentCode :
1202328
Title :
Statistical nonlinear model of MESFET and HEMT devices
Author :
Martino, A. Di ; Marietti, P. ; Olivieri, M. ; Tommasino, P. ; Trifiletti, A.
Author_Institution :
STMicroelectronics, Catania, Italy
Volume :
150
Issue :
2
fYear :
2003
fDate :
4/1/2003 12:00:00 AM
Firstpage :
95
Lastpage :
103
Abstract :
Accurate statistical models of FET devices are needed for yield-oriented MMIC design. In particular, currently used linear statistical models are not adequate in applications where bias point variations have a strong impact on overall yield. The paper describes a nonlinear statistical model of MESFET and HEMT devices in which statistical parameters are considered as Gaussian multivariate random variables. An automatic procedure is developed to achieve extraction of the statistical model of a FET device from a database of DC Ids and S-parameter measurements, and it is checked on a GaAs HEMT monolithic process. A statistical model has been extracted for Philips PML-D02AH GaAs HEMT devices and accurate evaluation of the S-parameters covariance matrix has been made. Statistical pair-wise tests on mean values, standard deviations and correlation coefficients show that the proposed methodology has the capability of reproducing statistical population distributions.
Keywords :
S-parameters; Schottky gate field effect transistors; equivalent circuits; field effect MMIC; high electron mobility transistors; integrated circuit design; microwave field effect transistors; semiconductor device models; statistical analysis; DC Ids measurements; FET devices; GaAs; Gaussian multivariate random variables; HEMT devices; MESFET devices; Philips PML-D02AH devices; S-parameter measurements; S-parameters covariance matrix; automatic procedure; bias point variations; fitting parameters; nonlinear statistical model; statistical model extraction; statistical population distributions; yield-oriented MMIC design;
fLanguage :
English
Journal_Title :
Circuits, Devices and Systems, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2409
Type :
jour
DOI :
10.1049/ip-cds:20030334
Filename :
1199672
Link To Document :
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