Channel modeling and estimation for intrapage equalization in pixel-matched volume holographic data storage.

Area of Science:

• Optical Engineering
• Data Storage Technologies
• Information Theory

Background:

• Volume holographic data storage (VHDS) systems offer high potential density.
• The 4-focal-length architecture is a common configuration for VHDS.
• Accurate channel modeling is crucial for optimizing VHDS performance.

Purpose of the Study:

• To develop and evaluate two channel models (magnitude and intensity) for a pixel-matched VHDS system.
• To assess the linearity and equalization gain of these models under various conditions.
• To present bit error rate (BER) results using linear equalization.

Main Methods:

• A framework for describing channel models was established.
• Model linearity was assessed by comparing diffraction-limited interference data with model predictions.
• Performance was evaluated across varying fill factors, apertures, and contrast ratios.
• Linear equalization methods were applied in conjunction with the developed channel models.

Main Results:

• Model linearity and equalization gain were analyzed under different storage and read-back conditions.
• The magnitude model showed superior performance at small fill factors.
• The intensity model proved more suitable for high fill factors.
• The optimum aperture for storage was found to be near the Nyquist aperture.

Conclusions:

• The choice between magnitude and intensity channel models depends on fill factor conditions.
• The magnitude model can yield storage density improvements up to 65%.
• The intensity model, via deconvolution, can achieve up to 15% density gain.