Novel soft-feedback equalisation method for multilevel magnetic recording
Shah, Purav ORCID: https://orcid.org/0000-0002-0113-5690, Ahmed, M. Z., Ambroze, M., Tjhai, C. and Davey, P. J.
(2007)
Novel soft-feedback equalisation method for multilevel magnetic recording.
IEEE transactions on magnetics, 43
(6)
.
pp. 2280-2282.
ISSN 0018-9464
[Article]
(doi:10.1109/TMAG.2007.894010)
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Abstract
This paper investigates the use of multilevel modulation for magnetic recording using a novel soft-feedback equalization (SFE) approach. Different aspects of investigation are 1)multilevel recording, 2) SFE, and 3) application of turbo codes. The SFE scheme is a model in which the partial response (PR) equalizer and maximum a posteriori (MAP) decoder are replaced by a linear filter with an iterative MAP decoder. Error correction codes (ECCs) are applied to the multilevel recording system in order to achieve very low error rates. Implementation of the SFE scheme for multilevel recording shows a reduction in complexity in comparison to various PRML schemes. The simulation results show a clear performance gain of multi-level-coded against binary-coded recording systems. At higher signal-to-noise ratio (SNR), the coded multilevel SFE scheme overcomes the error floor effect produced in the coded multilevel PRML scheme, which is caused by minimum distance error events. Overall, this paper proposes the use of coded multilevel recording with SFE scheme at lower rates rather than coded binary recording at higher densities in order to achieve similar performance
Item Type: | Article |
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Additional Information: | Conference details: Tenth joint Magnetism and magnetic materials - International Magentics (MMM–INTERMAG) conference; held at Marriott Waterfront Hotel, Baltimore, Maryland, January 7 – 11, 2007. |
Keywords (uncontrolled): | Soft Feedback Equalization, Multilevel, Magnetic Recording, Longitudinal Recording, PRML, MAP, Error Correction Codes, noise coloration |
Research Areas: | A. > School of Science and Technology > Computer and Communications Engineering A. > School of Science and Technology > Computer Science > SensoLab group |
Item ID: | 7765 |
Notes on copyright: | Post refereed version as permitted by publisher. |
Useful Links: | |
Depositing User: | Purav Shah |
Date Deposited: | 03 May 2011 12:34 |
Last Modified: | 10 Jun 2021 05:06 |
URI: | https://eprints.mdx.ac.uk/id/eprint/7765 |
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