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HBT: compact models

HBT: compact models

Abstract

The aim of this chapter has been to provide a background for bipolar compact modelling. The main improvements of the VBIC model over the SGP model is the addition of Early voltage effect, quasi-saturation, substrate parasitic, avalanche multiplication, self-heating and modelling of the parasitic pnp transistor. A methodology to extract and optimise d.c. and a.c. parameters for the VBIC model is developed and applied to SiGe HBTs. The model has been verified and optimized using a VBIC pseudo-code and an excellent agreement has been found. A comparison of the VBIC and SGP model clearly illustrates the weakness of the conventional SPICE Gummel-Poon model when applied to advanced SiGe HBTs. The MEXTRAM model includes a direct coupling between current and charge, thus leading to coupled d.c. and a.c. behaviour. This has the advantage of a physical representation of the device, which facilitates accurate scaling. The MEXTRAM and VBIC bipolar transistor models are comparable for low and medium collector current densities and frequencies. Parameter conversion from MEXTRAM to VBIC can easily be done for the depletion capacitances and d.c. parameters related to low and medium current levels. HICUMs major advantages over other bipolar models are its scalability, simple and process-based/related parameter extraction, predictive capability of process and layout variations, and simple numerical formulation. TCAD tool TRADICA has also been discussed. ANFIS automates RF modelling as it is technology independent, neuro-computing based, intelligent and capable of achieving any predetermined accuracy limit required.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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Average
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