Application of linear minimum mean-squared-error equalization for volume holographic data storage

Mehmet Keskinoz; B. V.K. Vijaya Kumar

doi:10.1364/AO.38.004387

Application of linear minimum mean-squared-error equalization for volume holographic data storage

Mehmet Keskinoz, B. V.K. Vijaya Kumar

Carnegie Mellon University

Research output: Contribution to journal › Article › peer-review

37 Citations (Scopus)

Abstract

When target densities of volume holographic data storage systems are increased, the systems experience increased interference from adjacent pixels and noise. Here we present a method for designing and applying linear minimum mean-squared-error (LMMSE) equalization to improve the bit error rates (BER’s) and hence the storage densities achievable. Numerical results with five defocused data pages indicate that a significant improvement in the BER is possible with LMMSE equalization.

Original language	English
Pages (from-to)	4387-4393
Number of pages	7
Journal	Applied Optics
Volume	38
Issue number	20
DOIs	https://doi.org/10.1364/AO.38.004387
Publication status	Published - 10 Jul 1999
Externally published	Yes

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AB - When target densities of volume holographic data storage systems are increased, the systems experience increased interference from adjacent pixels and noise. Here we present a method for designing and applying linear minimum mean-squared-error (LMMSE) equalization to improve the bit error rates (BER’s) and hence the storage densities achievable. Numerical results with five defocused data pages indicate that a significant improvement in the BER is possible with LMMSE equalization.

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Application of linear minimum mean-squared-error equalization for volume holographic data storage

Abstract

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