DocumentCode
32934
Title
Scalable Compact Modeling for On-Chip Passive Elements with Correlated Parameter Extraction and Adaptive Boundary Compression
Author
Jian Yao ; Zuochang Ye ; Yan Wang
Author_Institution
Inst. of Microelectron., Tsinghua Univ., Beijing, China
Volume
33
Issue
9
fYear
2014
fDate
Sept. 2014
Firstpage
1424
Lastpage
1428
Abstract
Scalable compact models for passive elements are important in the Analog/RF circuit design and optimization. Traditional scalable modeling methods are mainly physical and manual based methods, which usually require deep physical insight and extensive human intervention. In this paper, an automatic scalable compact modeling method for generic passive elements is established. The proposed method is a unified parameter extraction and scalable modeling scheme with novel inner-loop correlated parameter extraction and outer-loop adaptive boundary compression techniques. Experimental results show that both accuracy and scalability have been achieved by the proposed method for industrial inductors and transformers with an acceptable computational cost.
Keywords
analogue integrated circuits; circuit optimisation; inductors; integrated circuit design; integrated circuit modelling; passive networks; radiofrequency integrated circuits; transformers; RF circuit design; adaptive boundary compression; analog circuit design; automatic scalable compact modeling method; correlated parameter extraction; industrial inductors; inner-loop correlated parameter extraction; on-chip passive elements; outer-loop adaptive boundary compression techniques; transformers; unified parameter extraction; Adaptation models; Computational modeling; Inductors; Integrated circuit modeling; Optimization; Parameter extraction; Sociology; Inductor; RF circuit; optimization; parameter extraction; scalable compact model; transformer;
fLanguage
English
Journal_Title
Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on
Publisher
ieee
ISSN
0278-0070
Type
jour
DOI
10.1109/TCAD.2014.2323197
Filename
6879585
Link To Document