Title :
Pattern-Dependent Noise Predictive Belief Propagation
Author :
Kaynak, Mustafa N. ; Duman, Tolga M. ; Kurtas, Erozan M.
Author_Institution :
STMicroelectronics, San Diego, CA
Abstract :
In this paper, we introduce iterative pattern-dependent noise prediction for belief propagation (BP) channel detectors over intersymbol interference channels with correlated noise. The new scheme, called pattern-dependent noise predictive belief propagation, makes use of factor graphs, and it iteratively whitens the noise samples by modifying the edge probability computation of the BP algorithm. To illustrate the benefits of the proposed scheme, specifically, we consider longitudinal recording channels corrupted by the data-dependent media noise. Simulation results and convergence behavior analysis show that the proposed detector leads to significant performance improvements especially when the media noise level is high
Keywords :
belief networks; convergence of numerical methods; graph theory; intersymbol interference; magnetic recording; maximum likelihood detection; belief propagation; channel detection; convergence behavior analysis; correlated noise; edge probability computation; factor graphs; intersymbol interference channels; longitudinal recording channels; media noise; noise prediction; Additive white noise; Belief propagation; Convergence; Detectors; Gaussian noise; Intersymbol interference; Iterative algorithms; Magnetic analysis; Magnetic noise; Maximum likelihood detection; Belief propagation (BP); channel detection; pattern-dependent noise prediction;
Journal_Title :
Magnetics, IEEE Transactions on
DOI :
10.1109/TMAG.2006.878620
