NDLI: Analysis of the truncation biasing for importance sampling simulation of encoded systems

Content Provider	IEEE Xplore Digital Library
Author	Gurjao, E.C. Albert, B.B. de Assis, F.M.
Copyright Year	2006
Description	Author affiliation: Univ. Fed. de Campina Grande, Campina Grande (Gurjao, E.C.; Albert, B.B.; de Assis, F.M.)
Abstract	Importance sampling (IS) simulation of convolutionally encoded communication systems requires choosing code-words distinct of the transmitted one, called error-centers, in order to bent the simulation distribution along the direction of such that centers and so speed up simulation [1], [2]. As in practice it is mandatory to limit the number of error-centers the estimative turns up to be biased. We call truncation bias $(Delta^{T})$ the difference between the IS estimative using all error-centers and the IS estimative using a limited number of error-centers. In this paper we employ the results given by Urbanke et alli [3] on the asymptotic input-output weight distribution to analyze the asymptotic behaviour of E* $[Delta^{T}]$ the expected value of the truncation bias.
Starting Page	1020
Ending Page	1023
File Size	1067823
Page Count	4
File Format	PDF
ISBN	9788589748049
DOI	10.1109/ITS.2006.4433421
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-09-03
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Monte Carlo methods Analytical models Maximum likelihood decoding Bit error rate Convolutional codes Discrete event simulation Computational modeling Brazil Council Performance analysis Power system reliability Expected Error Simulation Importance Sampling
Content Type	Text
Resource Type	Article

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