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Title A Compact Macromodeling Method for Characterizing Large-signal DC and AC Performance of InP and GaAs HBTs
Authors (Lin Cheng) ; (Hongliang Lu) ; (Yuming Zhang) ; (Yimen Zhang)
DOI https://doi.org/10.5573/JSTS.2022.22.2.84
Page pp.84-92
ISSN 1598-1657
Keywords Heterojunction bipolar transistor; macromodeling method; symbolically-defined device; empirical macro circuit; parameter extraction
Abstract In this paper, a compact macromodeling method for characterizing the large-signal characteristics of heterojunction bipolar transistors (HBTs) is proposed and successfully applied to describe the DC and AC performance of InP and GaAs HBT devices. Using the Symbolically-defined Device (SDD) technology, an empirical macro circuit preserving the Spice Gummel-Poon (SGP) intrinsic network and a simplified thermal network is established. The empirical current and charge functions are embedded in the SDD macro circuit network module. Compared with other large-signal models, the proposed model description and the relevant parameter extraction are relatively simpler, and at the same time, this method can maintain high fitting accuracy. To assess the validity and the accuracy of the proposed model, the compact large-signal model is constructed for 1 μm InP HBT and 1 μm GaAs HBT. Based on the complete extraction of the model parameters, excellent consistency is obtained between the measured and modeled results.