Importance sampling for the random phase Gaussian channel

Importance sampling (IS) is developed as a variance reduction technique for Monte Carlo simulation of data communications over random phase additive white Gaussian noise channels. The binary problem (with known performance) is examined initially to determine parameter values and estimate the perform...

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Bibliographic Details
Published inIEEE transactions on communications Vol. 49; no. 5; pp. 749 - 753
Main Authors Swaszek, P.E., Levine, P.J.
Format Journal Article
LanguageEnglish
Published New York IEEE 01.05.2001
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Additive white noise
AWGN
Blocking
Channels
Computational modeling
Computer errors
Computer simulation
Data communication
Decoding
Gain
Gaussian
Gaussian channels
Importance sampling
Monte Carlo methods
Optimization
Sampling methods
Testing
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Summary:Importance sampling (IS) is developed as a variance reduction technique for Monte Carlo simulation of data communications over random phase additive white Gaussian noise channels. The binary problem (with known performance) is examined initially to determine parameter values and estimate the performance gain of IS. These results can then be applied to intractable m-ary signaling problems through composite IS. An example compares the performance of linear, square-law, and optimum receivers for binary block coded data.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0090-6778
1558-0857
DOI:10.1109/26.923795