DocumentCode :
2938503
Title :
Pattern Dependent Noise Predictive Belief Propagation
Author :
Kaynak, M.N. ; Duman, T.M. ; Kurtas, E.M.
Author_Institution :
STMicroelectron., San Diego
fYear :
2006
fDate :
8-12 May 2006
Firstpage :
298
Lastpage :
298
Abstract :
Inter-symbol interference (ISI) channels are encountered in many applications, including magnetic recording and wireless communication systems. In general maximum a-posteriori (MAP) or maximum likelihood (ML) algorithms are used for channel detection. Recently, iterative belief propagation (BP) algorithm is proposed for channel detection as well. When factor graph of the ISI channel is length 4 cycle free, BP gives a similar performance with the MAP detector, while it has the advantage of parallel structure leading to advantages in read channel architectures. Unlike ISI channels with white noise, for magnetic recording systems, noise is correlated and data (pattern) dependent. Correlation is a result of partial response (PR) equalization and data dependence is a result of the media noise (jitter).
Keywords :
belief networks; intersymbol interference; iterative methods; jitter; magnetic recording; maximum likelihood estimation; white noise; MAP detector; channel detection; factor graph; inter-symbol interference channels; iterative belief propagation algorithm; jitter; magnetic recording; maximum a-posteriori algorithm; maximum likelihood algorithm; media noise; partial response equalization; pattern dependent noise predictive belief propagation; read channel architectures; white noise; wireless communication systems; Belief propagation; Detectors; Intersymbol interference; Iterative algorithms; Magnetic noise; Magnetic recording; Maximum a posteriori estimation; Maximum likelihood detection; White noise; Wireless communication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Magnetics Conference, 2006. INTERMAG 2006. IEEE International
Conference_Location :
San Diego, CA
Print_ISBN :
1-4244-1479-2
Type :
conf
DOI :
10.1109/INTMAG.2006.375880
Filename :
4261731
Link To Document :
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