Adaptive importance sampling [digital communication]

Author

Stadler, J. Scott ; Roy, Sumit

Author_Institution

Dept. of Electr. Eng., Pennsylvania Univ., Philadelphia, PA, USA

Volume

11

Issue

3

fYear

1993

fDate

4/1/1993 12:00:00 AM

Firstpage

309

Lastpage

316

Abstract

Parametric adaptive importance sampling (IS) algorithms that adapt the IS density to the system of interest during the course of the simulation are discussed. This approach removes the burden of selecting the IS density from the system designer. The performance of two such algorithms is investigated for both linear and nonlinear systems operating in Gaussian noise. In addition, the algorithms are shown to converge to the optimum improved importance sampling density for the special case of a linear system with Gaussian noise

Keywords

digital communication systems; linear systems; nonlinear systems; random noise; telecommunication channels; telecommunications computing; Gaussian noise; digital communication; importance sampling density; linear system; nonlinear systems; parametric adaptive importance sampling; simulation; Communication systems; Computational modeling; Computer errors; Digital communication; Discrete event simulation; Gaussian noise; High performance computing; Linear systems; Monte Carlo methods; Nonlinear systems;

fLanguage

English

Journal_Title

Selected Areas in Communications, IEEE Journal on

Publisher

ieee

ISSN

0733-8716

Type

jour

DOI

10.1109/49.219545

Filename

219545