DocumentCode :
892042
Title :
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
Link To Document :
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