Paper Info
Title
Karhunen-loève-based reduced-complexity representation of the mixed-density messages in SPA on factor graph and its impact on BER
Abstract
The sum product algorithm on factor graphs (FG/SPA) is a widely used tool to solve various problems in a wide area of fields. A representation of generally-shaped continuously valued messages in the FG/SPA is commonly solved by a proper parameterization of the messages. Obtaining such a proper parameterization is, however, a crucial problem in general. The paper introduces a systematic procedure for obtaining a scalar message representation with well-defined fidelity criterion in a general FG/SPA. The procedure utilizes a stochastic nature of the messages as they evolve during the FG/SPA processing. A Karhunen-Loève Transform (KLT) is used to find a generic canonical message representation which exploits the message stochastic behavior with mean square error (MSE) fidelity criterion. We demonstrate the procedure on a range of scenarios including mixture-messages (a digital modulation in phase parametric channel). The proposed systematic procedure achieves equal results as the Fourier parameterization developed especially for this particular class of scenarios.
Year
DOI
Venue
2010
10.1155/2010/574607
EURASIP J. Wireless Comm. and Networking
Keywords
Field
DocType
fourier parameterization,generic canonical message representation,message stochastic behavior,factor graph,scalar message representation,proposed systematic procedure,spa processing,systematic procedure,fidelity criterion,general fg,mixed-density message,proper parameterization,ve-based reduced-complexity representation
Probability mass function,Factor graph,Karhunen–Loève theorem,Computer science,Scalar (physics),Algorithm,Mean squared error,Theoretical computer science,Fourier transform,Parametric statistics,Probability density function
Journal
Volume
Issue
ISSN
2010,
1
1687-1499
Citations 
PageRank 
References 
0
0.34
8
Authors
2
Name
Order
Citations
PageRank
Pavel Prochazka1103.63
Jan Sykora214522.33