Low Complexity Noise Predictive Maximum Likelihood Detection Method for High Density Perpendicular Magnetic Recording 


Vol. 27,  No. 6, pp. 562-567, Jun.  2002


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  Abstract

Noise predictive maximum likelihood(NPML) detector embeds noise prediction/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(l221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density 1.0 ≤ K_p ≤ 3.0.

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  Cite this article

[IEEE Style]

S. Kim, J. Lee, J. Lee, "Low Complexity Noise Predictive Maximum Likelihood Detection Method for High Density Perpendicular Magnetic Recording," The Journal of Korean Institute of Communications and Information Sciences, vol. 27, no. 6, pp. 562-567, 2002. DOI: .

[ACM Style]

Seonghwan Kim, Joohyun Lee, and Jaejin Lee. 2002. Low Complexity Noise Predictive Maximum Likelihood Detection Method for High Density Perpendicular Magnetic Recording. The Journal of Korean Institute of Communications and Information Sciences, 27, 6, (2002), 562-567. DOI: .

[KICS Style]

Seonghwan Kim, Joohyun Lee, Jaejin Lee, "Low Complexity Noise Predictive Maximum Likelihood Detection Method for High Density Perpendicular Magnetic Recording," The Journal of Korean Institute of Communications and Information Sciences, vol. 27, no. 6, pp. 562-567, 6. 2002.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880