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Related Experiment Videos

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

M Keskinoz1, B V Kumar

  • 1Department of Electrical and Computer Engineering, Carnegie Mellon University, Data Storage Systems Center, Pittsburgh, Pennsylvania 15213, USA.

Applied Optics
|March 8, 2008
PubMed
Summary
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Higher storage densities in holographic data systems cause interference. Applying linear minimum mean-squared-error (LMMSE) equalization significantly improves bit error rates (BER), enabling denser data storage.

Area of Science:

  • Optical data storage
  • Information theory
  • Signal processing

Background:

  • Volume holographic data storage offers high potential density.
  • Increased target densities lead to inter-pixel interference and noise.
  • This degrades system performance and limits achievable storage density.

Purpose of the Study:

  • To introduce a method for designing and applying linear minimum mean-squared-error (LMMSE) equalization.
  • To improve bit error rates (BER) in volume holographic data storage systems.
  • To enable higher storage densities by mitigating interference and noise.

Main Methods:

  • Design and application of LMMSE equalization.
  • Numerical simulations using five defocused data pages.

Related Experiment Videos

  • Evaluation of bit error rates (BER) before and after equalization.

    • Main Results:

    • LMMSE equalization effectively reduces interference and noise.
    • A significant improvement in bit error rates (BER) was observed.
    • The method demonstrates the potential for enhanced storage densities.

    Conclusions:

    • LMMSE equalization is a viable technique for improving holographic data storage performance.
    • The proposed method enhances BER, paving the way for denser data storage.
    • This approach addresses a key challenge in scaling holographic storage systems.