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Abstract
Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends
critically on active device models that are accurate, computationally efficient, and easily extracted
from measurements or device simulators.
Empirical models of active electron devices, which are based on actual device measurements, do
not provide a detailed description of the electron device physics. However they are numerically
efficient and quite accurate. These characteristics make them very suitable for MMIC design in the
framework of commercially available CAD tools.
In the empirical model formulation it is very important to separate linear memory effects
(parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device
model is generally described by an extrinsic linear part which accounts for the parasitic passive
structures connecting the nonlinear intrinsic electron device to the external world.
An important task circuit designers deal with is evaluating the ultimate potential of a device for
specific applications. In fact once the technology has been selected, the designer would choose the
best device for the particular application and the best device for the different blocks composing the
overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices,
good scalability properties of the model are necessarily required.
Another important aspect of empirical modelling of electron devices is the mathematical (or
equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device.
Once the model has been defined, the proper measurements for the characterization of the device
are performed in order to identify the model. Hence, the correct measurement of the device
nonlinear characteristics (in the device characterization phase) and their reconstruction (in the
identification or even simulation phase) are two of the more important aspects of empirical
modelling.
This thesis presents an original contribution to nonlinear electron device empirical modelling
treating the issues of model scalability and reconstruction of the device nonlinear characteristics.
The scalability of an empirical model strictly depends on the scalability of the linear extrinsic
parasitic network, which should possibly maintain the link between technological process
parameters and the corresponding device electrical response.
Since lumped parasitic networks, together with simple linear scaling rules, cannot provide
accurate scalable models, either complicate technology-dependent scaling rules or computationally
inefficient distributed models are available in literature.
This thesis shows how the above mentioned problems can be avoided through the use of
commercially available electromagnetic (EM) simulators. They enable the actual device geometry
and material stratification, as well as losses in the dielectrics and electrodes, to be taken into
account for any given device structure and size, providing an accurate description of the parasitic
effects which occur in the device passive structure. It is shown how the electron device behaviour
can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed
four-port passive parasitic network, which is identified by means of the EM simulation of the device
layout, allowing for better frequency extrapolation and scalability properties than conventional
empirical models.
Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data
approximation algorithm has been developed for the exploitation in the framework of empirical
table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain
signal reconstruction from a set of samples and the continuous approximation of device
nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion,
nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain,
typical methods of the time-domain sampling theory.
Abstract
Computer aided design of Monolithic Microwave Integrated Circuits (MMICs) depends
critically on active device models that are accurate, computationally efficient, and easily extracted
from measurements or device simulators.
Empirical models of active electron devices, which are based on actual device measurements, do
not provide a detailed description of the electron device physics. However they are numerically
efficient and quite accurate. These characteristics make them very suitable for MMIC design in the
framework of commercially available CAD tools.
In the empirical model formulation it is very important to separate linear memory effects
(parasitic effects) from the nonlinear effects (intrinsic effects). Thus an empirical active device
model is generally described by an extrinsic linear part which accounts for the parasitic passive
structures connecting the nonlinear intrinsic electron device to the external world.
An important task circuit designers deal with is evaluating the ultimate potential of a device for
specific applications. In fact once the technology has been selected, the designer would choose the
best device for the particular application and the best device for the different blocks composing the
overall MMIC. Thus in order to accurately reproducing the behaviour of different-in-size devices,
good scalability properties of the model are necessarily required.
Another important aspect of empirical modelling of electron devices is the mathematical (or
equivalent circuit) description of the nonlinearities inherently associated with the intrinsic device.
Once the model has been defined, the proper measurements for the characterization of the device
are performed in order to identify the model. Hence, the correct measurement of the device
nonlinear characteristics (in the device characterization phase) and their reconstruction (in the
identification or even simulation phase) are two of the more important aspects of empirical
modelling.
This thesis presents an original contribution to nonlinear electron device empirical modelling
treating the issues of model scalability and reconstruction of the device nonlinear characteristics.
The scalability of an empirical model strictly depends on the scalability of the linear extrinsic
parasitic network, which should possibly maintain the link between technological process
parameters and the corresponding device electrical response.
Since lumped parasitic networks, together with simple linear scaling rules, cannot provide
accurate scalable models, either complicate technology-dependent scaling rules or computationally
inefficient distributed models are available in literature.
This thesis shows how the above mentioned problems can be avoided through the use of
commercially available electromagnetic (EM) simulators. They enable the actual device geometry
and material stratification, as well as losses in the dielectrics and electrodes, to be taken into
account for any given device structure and size, providing an accurate description of the parasitic
effects which occur in the device passive structure. It is shown how the electron device behaviour
can be described as an equivalent two-port intrinsic nonlinear block connected to a linear distributed
four-port passive parasitic network, which is identified by means of the EM simulation of the device
layout, allowing for better frequency extrapolation and scalability properties than conventional
empirical models.
Concerning the issue of the reconstruction of the nonlinear electron device characteristics, a data
approximation algorithm has been developed for the exploitation in the framework of empirical
table look-up nonlinear models. Such an approach is based on the strong analogy between timedomain
signal reconstruction from a set of samples and the continuous approximation of device
nonlinear characteristics on the basis of a finite grid of measurements. According to this criterion,
nonlinear empirical device modelling can be carried out by using, in the sampled voltage domain,
typical methods of the time-domain sampling theory.
Tipologia del documento
Tesi di dottorato
Autore
Resca, Davide
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
20
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
mmic fet models
URN:NBN
DOI
10.6092/unibo/amsdottorato/920
Data di discussione
17 Aprile 2008
URI
Altri metadati
Tipologia del documento
Tesi di dottorato
Autore
Resca, Davide
Supervisore
Co-supervisore
Dottorato di ricerca
Ciclo
20
Coordinatore
Settore disciplinare
Settore concorsuale
Parole chiave
mmic fet models
URN:NBN
DOI
10.6092/unibo/amsdottorato/920
Data di discussione
17 Aprile 2008
URI
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