Page tree

Versions Compared

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.

Hide If
matchany
userpdfbuild
Float
bordernone
sideright
width25%
Panel
borderColor#eaeef6
bgColor#eaeef6
borderStylesolid
Builder hide
labelno_rsb_toc

On This Page

Table of Contents
maxLevel3
indent15px
Include Page
Additional Resources Text
Additional Resources Text

Anchor
1136761
1136761

Amplifiers and Mixers

Anchor
1136762
1136762

Introduction

The Filters - <filter type> and System - <device type palettes contain two fundamentally different types of behavioral system models.

Filters, System - Amps & Mixers, and System - Mod/Demod can be classified as tops-down system models that support a tops-down system design flow where model behaviors are characterized by a small number of independent parameters such as frequency, power and load. They are often referred to as parameter-based behavioral models.

System - Data Models can be classified as bottoms-up system models that support a bottoms-up verification flow where model behaviors are extracted from a simulation (or measurement) of a transistor-level circuit. They are often referred to as data-based behavioral models.

The parameter-based behavioral models typically provide superior speed relative to the data-based behavioral models with both of these being vastly superior to a brute-force transistor-level simulation.

The data-based behavioral models ypically provide superior accuracy relative to the parameter-based behavioral models as they capture actual behaviors of implemented circuit components and not just design specifications.

The differences between parameter- and data-based behavioral models justify a palette emphasis on flow (all data-based behavioral models grouped together) rather than functionality (all amplifiers, mixers, modulators, and demodulators grouped together) and resulted in the addition of a System - Data Models palette.

The use model for parameter-based behavioral models is to simply set a series of parameters prior to using the model. The use model for data-based behavioral models is slightly more involved. For a discussion, see System Data Models.

Anchor
1141275
1141275

Curve-Fitting Algorithm

The curve-fitting algorithm to determine the nonlinear behavior of the system mixer models is based on fitting a polynomial to the specified data where the saturation power (Psat) is calculated when the derivative of this polynomial is zero.

Pn(x) = a1*x1+a2*x2^2+a3*x^3+...

It is important to note that the coefficients a4,a6,a8,...are always zero. In only one case a2 is non-zero and that's when SOI and TOI are specified.

Parameters

Order

TOI

3

TOI & AM2PM

3

SOI & TOI

3 a2 ≠ 0

PndB

3

PndB & AM2PM

3

Psat

5

TOI & PndB

5

PndB & Psat

7

TOI & Psat

7

PndB & TOI & Psat

9

Components

Children Display