S. Chitrashekaraiah, C. N. Dharmasiri, A. Rezazadeh
{"title":"An automated small-signal parameter extraction technique for HBTs using ICCAP","authors":"S. Chitrashekaraiah, C. N. Dharmasiri, A. Rezazadeh","doi":"10.1109/HFPSC.2004.1360377","DOIUrl":null,"url":null,"abstract":"This work presents an automated toolkit for the extraction of small-signal parameters of heterojunction bipolar transistors (HBTs) using Agilent's IC evaluation characterisation and analysis program (ICCAP). On-wafer S-parameters of a 16/spl times/20 /spl mu/m/sup 2/ InGaP/GaAs double HBT (DHBT) for different bias conditions are measured and analysed over a wide temperature range, -25/spl deg/C to +110/spl deg/C. These measured data are used in the extraction of small-signal parameters and compared with ADS simulations to verify and validate the developed small-signal extraction toolkit.","PeriodicalId":405718,"journal":{"name":"High Frequency Postgraduate Student Colloquium, 2004","volume":"73 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"High Frequency Postgraduate Student Colloquium, 2004","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HFPSC.2004.1360377","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This work presents an automated toolkit for the extraction of small-signal parameters of heterojunction bipolar transistors (HBTs) using Agilent's IC evaluation characterisation and analysis program (ICCAP). On-wafer S-parameters of a 16/spl times/20 /spl mu/m/sup 2/ InGaP/GaAs double HBT (DHBT) for different bias conditions are measured and analysed over a wide temperature range, -25/spl deg/C to +110/spl deg/C. These measured data are used in the extraction of small-signal parameters and compared with ADS simulations to verify and validate the developed small-signal extraction toolkit.