Accession Number:

ADA429148

Title:

Global Modeling of Compact High-Speed Circuits

Descriptive Note:

Final rept. no. 4, 26 Apr 1999-31 Dec 2002

Corporate Author:

ARIZONA STATE UNIV TEMPE TELECOMMUNICATIONS RESEARCH CENTER

Personal Author(s):

Report Date:

2003-04-01

Pagination or Media Count:

50.0

Abstract:

In this report, we present the work done during May 2002 to April 2003. We developed a fast wavelet-based time-domain modeling technique to study the effect of electromagnetic-wave propagation on the performance of high power and frequency multifinger transistors. The proposed approach solves the active device model that combines the transport physics, and Maxwells Equations on nonuniform self-adaptive grids, obtained by applying wavelet transforms followed by hard thresholding. This allows forming fine and coarse grids in the locations where variable solutions change rapidly and slowly, respectively. Comparison graphs showed a CPU-time reduction of 75 compared to a uniform-grid case, while maintaining the same degree of accuracy. After validation, the potential of the developed technique is demonstrated by electromagnetic-physical modeling of multifinger transistors. Different numerical examples are presented emphasizing that accurate modeling of high-frequency devices should incorporate the effect of EM-wave propagation and electron-wave interactions, within and around the device. Moreover, high-frequency advantages of multifinger transistors over singlefinger transistors are highlighted. To our knowledge, this is the first time in literature to introduce and implement a fully numerical electromagnetic-physics-based simulator for accurate modeling of high-frequency multifinger transistors. We have also considered the use of genetic algorithms to develop efficient simulators for modeling of high-frequency active microwave devices. We have successfully developed a new genetic-based simulator for large signal modeling of high-frequency devices. The new approach is compared to standard simulators showing moderate speed of convergence along with excellent accuracy. The advantages of genetic algorithms are their capabilities to obtain global solutions of multiple minima optimization problems along with being unconditionally stable.

Subject Categories:

  • Electrical and Electronic Equipment
  • Radiofrequency Wave Propagation

Distribution Statement:

APPROVED FOR PUBLIC RELEASE