Electron device modelling at very high frequencies needs, as a preliminary step, the identification of suitable parasitic elements mainly describing the passive structure used for accessing the intrinsic device. However, when dealing with device modelling at millimetre-wave frequencies conventional lumped parasitic networks necessarily become less adequate in describing inherently distributed parasitic phenomena. In this paper, a distributed approach is adopted for the modelling of the parasitic network and a new identification procedure, based on electromagnetic simulation and conventional S-parameter measurements, is proposed. The intrinsic device, obtained after de-embedding from the distributed parasitic network, is particularly suitable for the extraction of accurate nonlinear models. Preliminary validation results are provided in the paper. © 2006 EuMA.
Titolo: | A distributed approach for millimetre-wave electron device modelling | |
Autore/i: | Resca D.; Santarelli A.; Raffo A.; Cignani R.; Vannini G.; Filicori F.; Cidronali A. | |
Autore/i Unibo: | ||
Anno: | 2006 | |
Titolo del libro: | Proceedings of the 1st European Microwave Integrated Circuits Conference, EuMIC 2006 | |
Pagina iniziale: | 257 | |
Pagina finale: | 260 | |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/EMICC.2006.282801 | |
Abstract: | Electron device modelling at very high frequencies needs, as a preliminary step, the identification of suitable parasitic elements mainly describing the passive structure used for accessing the intrinsic device. However, when dealing with device modelling at millimetre-wave frequencies conventional lumped parasitic networks necessarily become less adequate in describing inherently distributed parasitic phenomena. In this paper, a distributed approach is adopted for the modelling of the parasitic network and a new identification procedure, based on electromagnetic simulation and conventional S-parameter measurements, is proposed. The intrinsic device, obtained after de-embedding from the distributed parasitic network, is particularly suitable for the extraction of accurate nonlinear models. Preliminary validation results are provided in the paper. © 2006 EuMA. | |
Data stato definitivo: | 6-mag-2022 | |
Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |