On the asymptotic efficiency of importance sampling techniques

Author

Schlebusch, Heinz-Josef

Author_Institution

CADIS GmbH, Herzogenrath, Germany

Volume

39

Issue

2

fYear

1993

fDate

3/1/1993 12:00:00 AM

Firstpage

710

Lastpage

715

Abstract

The asymptotic efficiency of importance sampling (IS) techniques for the simulation of rare events in a multidimensional nonlinear setting was studied by J.S. Sadowsky and J.A. Bucklew (see ibid., vol.36, p.579-88, 1990). Fundamental results on the asymptotic efficiency of the mean-value modification (MM) technique were derived. Additionally, a statement was made that other IS techniques cannot be asymptotically efficient. It is shown that for the simulation of digital communication systems with Gaussian input, a broad class of asymptotically efficient IS techniques exists. Necessary and sufficient conditions are provided for the asymptotic efficiency of five different IS techniques (including MM) for one-dimensional linear systems. Multidimensional generalizations of these IS techniques are proposed. A sufficient condition for the asymptotic efficiency of these techniques applied to multidimensional nonlinear systems is provided

Keywords

digital communication systems; error statistics; information theory; linear systems; multidimensional systems; nonlinear systems; BER; Gaussian input; asymptotic efficiency; bit error rate; digital communication systems; importance sampling techniques; mean-value modification; multidimensional nonlinear systems; necessary condition; one-dimensional linear systems; sufficient condition; Bit error rate; Computational modeling; Discrete event simulation; Linear systems; Monte Carlo methods; Multidimensional systems; Nonlinear systems; Performance analysis; Sampling methods; Sufficient conditions;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/18.212308

Filename

212308