Back to Search Start Over

Large-scale broad-band parasitic extraction for fast layout verification of 3-D RF and mixed-signal on-chip structures

Authors :
Ling, Feng
Okhmatovski, Vladimir I.
Harris, Warren
McCracken, Stephen
Dengi, Aykut
Source :
IEEE Transactions on Microwave Theory and Techniques. Jan, 2005, Vol. 53 Issue 1, p264, 10 p.
Publication Year :
2005

Abstract

In this paper, a methodology for efficient parasitic extraction and verification flow for RF and mixed-signal integrated-circuit designs is presented. The implementation of a multiplane precorrected fast Fourier transform (PFFT) computational engine enables the full-wave electromagnetic (EM) simulation of interconnects and passive components. The PFFT algorithm is implemented on a set of two-dimensional fast Fourier transform grids associated with the current sheets corresponding to the conductor loss models. This leads to the full-wave modeling of silicon embedded three-dimensional circuits within the two-and-one-half-dimensional computational framework yielding the O(N log N) computational complexity and O(N) memory requirements of the algorithm. The broad-band capability of the EM solver is provided through the loop-tree/charge implementation of the PFFT algorithm allowing for robust full-wave modeling from dc to microwaves. The EM verification flow is integrated seamlessly within the Cadence environment allowing for non-linear circuit simulation of the entire device. The capability and accuracy of the proposed methodology is demonstrated through EM simulation results for an individual on-chip spiral inductor, as well as a low-noise amplifier. Index Terms--Electromagnetic (EM) solver, fast algorithm, method of moments (MoM), multiplane precorrected fast Fourier transform (PFFT), parasitic extraction, RF integrated circuit (RFIC), spiral inductor.

Details

Language :
English
ISSN :
00189480
Volume :
53
Issue :
1
Database :
Gale General OneFile
Journal :
IEEE Transactions on Microwave Theory and Techniques
Publication Type :
Academic Journal
Accession number :
edsgcl.128206708