Nonlinear modeling of SiGe HBTs up to 50 GHz

Rheinfelder, C.; Beisswanger, F.; Heinrich, W.

doi:10.1109/22.643866

Cited by 25 publications

(8 citation statements)

References 11 publications

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“…For the MSL, the extracted values of C p and R p decrease with higher frequencies, which is comparable to the results of [8]. This was modeled by an additional factor k = 1 1 + j f f1 (12) where f 1 is a second corner frequency. The modified values of C p and Rp are then C 3 p = Cp 1 k and R 3 p = Rp 1 k. For exact modeling of the lines with a length of 5 mm up to a frequency of 20 GHz, a chain of 16 equivalent circuits, depicted in Fig.…”

Section: Determination Of the Model Parameterssupporting

confidence: 83%

“…The values of the line resistance R s and R g , including the skin effect, can be easily deduced from the conductivity % Al of the Al metallization and the line dimensions R s = % Al 1 l w 1 t 1 + f f0 (10) with f 0 as the skin-effect corner frequency, which can be determined from the extracted series resistance. R p of the MSL that corresponds to the substrate resistance, which can be calculated from the measurable sheet resistance of the substrate, including the channel stopper, is here, approximately % Sub =d 300 = by Rp = % Sub d 1 s l : (11) The extracted values of L s and C c remain nearly constant over the whole frequency range and the value of Rp for the small CPW is, in fact, nearly zero. For the MSL, the extracted values of C p and R p decrease with higher frequencies, which is comparable to the results of [8].…”

Section: Determination Of the Model Parametersmentioning

confidence: 85%

See 1 more Smart Citation

Investigation of microstrip and coplanar transmission lines on lossy silicon substrates without backside metallization

Dürr

Erben

Schüppen³

et al. 1998

IEEE Trans. Microwave Theory Techn.

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Silicon circuits, now penetrating well into the microwave frequency range, use lossy silicon substrates. Consequently, the microwave performance of transmission lines on this substrate becomes increasingly important and has been investigated here up to 20 GHz. It is shown that transmission lines on 20-1 cm substrates have no need for backside metallization and backside via holes. Two models for different line types are derived from measurements and verified against them. A coplanar waveguide (CPW) with an overall width of less than 30 m was fabricated with an attenuation of 0.5 dB/mm at 20 GHz, which is acceptable for monolithic microwave integrated circuit (MMIC) design.

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Section: Determination Of the Model Parameterssupporting

confidence: 83%

Section: Determination Of the Model Parametersmentioning

confidence: 85%

Investigation of microstrip and coplanar transmission lines on lossy silicon substrates without backside metallization

Dürr

Erben

Schüppen³

et al. 1998

IEEE Trans. Microwave Theory Techn.

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“…Silicon Germanium (SiGe) Heterojunction Bipolar Transistor (HBT) has superior performance at high frequency than standard Silicon based bipolar transistors. In this example, we show how Neuro-SM works in a simple DC case of a SiGe HBT device modeling, with data from measurement (Rheinfelder et al 1997;Zhang et al 2003Zhang et al , 2005. The coarse model used is a standard Curtice model (Curtice 1988).…”

Section: Discussionmentioning

confidence: 98%

Neuro-space mapping technique for semiconductor device modeling

Zhang

2007

Optim Eng

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This paper presents an application of the space mapping concept in the modeling of semiconductor devices. A recently proposed device modeling technique, called neuro-space mapping (Neuro-SM), is described to meet the constant need of new device models due to rapid progress in the semiconductor technology. Neuro-SM is a systematic method allowing us to exceed the present capabilities of the existing device models. It uses a neural network to map the voltage and current signals between an existing device model (coarse model) and the actual device behavior (fine model), such that the mapped model becomes an accurate representation of the new device. An efficient training method based on analytical sensitivity analysis for such mapping neural network is also addressed. The trained Neuro-SM model can retain the speed of the existing device model while improving the model accuracy. The benefit of the Neuro-SM method is demonstrated by examples of SiGe HBT and GaAs MESFET modeling and use of the models in harmonic balance simulation.

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“…Their values can be obtained by measuring the S-parameters of the dummy structures, and then applying any one of them by using the methods described in [5][6][7]. The usual modeling approach would be to subtract the effect of these parasitics.…”

Section: A Pad and Access Transmission-line Parasiticsmentioning

confidence: 99%