Adaptive Threshold Detection Using Expectation-Maximization Algorithm for Multi-LevelHolographic Data Storage 


Vol. 37,  No. 10, pp. 809-814, Oct.  2012


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  Abstract

We propose an adaptive threshold detector algorithm for multi-level holographic data storage based on the expectation-maximization (EM) method. In this paper, the signal intensities that are passed through the four-level holographic channel are modeled as a four Gaussian mixture with unknown DC offsets and the threshold levels are estimated based on the maximum likelihood criterion. We compare the bit error rate (BER) performance of the proposed algorithm with the non-adaptive threshold detection algorithm for various levels of DC offset and misalignments. Our proposed algorithm shows consistently acceptable performance when the DC offset variance is fixed or the misalignments are lower than 20%. When the DC offset varies with each page, the BER of the proposed method is acceptable when the misalignments are lower than 10% and DC offset variance is 0.001.

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  Cite this article

[IEEE Style]

J. Kim and J. Lee, "Adaptive Threshold Detection Using Expectation-Maximization Algorithm for Multi-LevelHolographic Data Storage," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 10, pp. 809-814, 2012. DOI: .

[ACM Style]

Jinyoung Kim and Jaejin Lee. 2012. Adaptive Threshold Detection Using Expectation-Maximization Algorithm for Multi-LevelHolographic Data Storage. The Journal of Korean Institute of Communications and Information Sciences, 37, 10, (2012), 809-814. DOI: .

[KICS Style]

Jinyoung Kim and Jaejin Lee, "Adaptive Threshold Detection Using Expectation-Maximization Algorithm for Multi-LevelHolographic Data Storage," The Journal of Korean Institute of Communications and Information Sciences, vol. 37, no. 10, pp. 809-814, 10. 2012.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880