Analog Behavioral Simulation and Modeling

Edward W. Y. Liu

EECS Department
University of California, Berkeley
Technical Report No. UCB/ERL M93/38
May 1993

http://www2.eecs.berkeley.edu/Pubs/TechRpts/1993/ERL-93-38.pdf

We propose a top-down, constraint-driven approach to designing complex mixed signal circuits. To support the proposed design methodology, we develop system simulation algorithms and behavioral models for many types of analog systems and components. In analog systems, the nominal circuit ns are usually very simple, and system malfunctions are most often due to second order effects caused by noise and process variations. Therefore, behavioral models at all levels must capture second order effects for constraint translation in top down design. Using traditional circuit simulation and macromodeling approaches, it is very difficult to simulate frequency domain effects, noise effects, or effects due to process variations because all models are deterministic. As a result, we propose a new strategy for behavioral simulation and modeling for the design and verification of systems in the presence of noise effects and effects due to process variations.

Advisor: Alberto L. Sangiovanni-Vincentelli


BibTeX citation:

@phdthesis{Liu:M93/38,
    Author = {Liu, Edward W. Y.},
    Title = {Analog Behavioral Simulation and Modeling},
    School = {EECS Department, University of California, Berkeley},
    Year = {1993},
    Month = {May},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/1993/2348.html},
    Number = {UCB/ERL M93/38},
    Abstract = {We propose a top-down, constraint-driven approach to designing complex mixed signal circuits. To support the proposed design methodology, we develop system simulation algorithms and behavioral models for many types of analog systems and components. In analog systems, the nominal circuit ns are usually very simple, and system malfunctions are most often due to second order effects caused by noise and process variations. Therefore, behavioral models at all levels must capture second order effects for constraint translation in top down design. Using traditional circuit simulation and macromodeling approaches, it is very difficult to simulate frequency domain effects, noise effects, or effects due to process variations because all models are deterministic. As a result, we propose a new strategy for behavioral simulation and modeling for the design and verification of systems in the presence of noise effects and effects due to process variations.}
}

EndNote citation:

%0 Thesis
%A Liu, Edward W. Y.
%T Analog Behavioral Simulation and Modeling
%I EECS Department, University of California, Berkeley
%D 1993
%@ UCB/ERL M93/38
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/1993/2348.html
%F Liu:M93/38