Nonuniform Data-Dependent Noise Prediction in Magnetic Recording

Author

Sun, Zhenyu ; Ngwe, Myint

Author_Institution

Seagate Technol. Int., Singapore

Volume

43

Issue

3

fYear

2007

fDate

3/1/2007 12:00:00 AM

Firstpage

1112

Lastpage

1117

Abstract

In this paper, we report a method for nonuniform data-dependent noise prediction (DDNP), in which the noise predictive filters do not have an identical order (number of taps). To accommodate this new architecture, we implemented a partial decision feedback strategy for branch metric computations of the higher order predictive filters. Theoretical analysis and computer simulations show that our proposed DDNP can achieve a better tradeoff between detection performance and computational complexity compared with the previously reported DDNP

Keywords

computational complexity; filtering theory; magnetic recording noise; branch metric computations; computational complexity; higher order predictive filters; magnetic recording; noise predictive filters; nonuniform data-dependent noise prediction; partial decision feedback strategy; Bit error rate; Computational complexity; Computer architecture; Feedback; Filter bank; Finite impulse response filter; Magnetic noise; Magnetic recording; Perpendicular magnetic recording; Sun; Bit-error rate; data-dependent noise prediction; pairwise error event probability; partial decision feedback; perpendicular recording;

fLanguage

English

Journal_Title

Magnetics, IEEE Transactions on

Publisher

ieee

ISSN

0018-9464

Type

jour

DOI

10.1109/TMAG.2006.888738

Filename

4100812