Abstract
A conventional schematic of holographic data storage (HDS) with the 4-fL (focal length) architecture is described in Fig. 1 [1]. The input data page is displayed on the spatial light modulator (SLM) and the modulated signals pass through the frequency-plane aperture which is like a low pass filter. As aperture width is smaller, areal density becomes larger, and two-dimensional (2D) inter-symbol interference (ISI) becomes severe. In addition, nonlinearity of HDS channel caused by intensity detection using charge-coupled detector (CCD) worsen the ISI problem. In nonlinear channels, the conventional linear equalizers have performance limitation. Therefore, we need a type of nonlinear equalizer which mitigates 2D ISI effectively for HDS systems. Most popular nonlinear signal processing are Volterra series and multivariate polynomial model [2]. However, these models are too complex to use since a large number of equalizer coefficients are needed. As a type of nonlinear equalizer, the bilinear recursive polynomial perceptron (BRP) is well kwon to have a good performance in spite of its simple structure [3]. BRP with decision feedback equalizer (BRPDFE) which has a better performance than the conventional BRP equalizer (BRPE) is proposed in [4]. In this paper, we extend the conventional 1D BRP model to a 2D BRP model for HDS systems. In order to verify that the proposed method is good for HDS systems, the proposed BRP and BRPDFE are compared with conventional adaptive decision feedback equalizer (DFE) and partial response maximum likelihood (PRML).
© 2011 Optical Society of America
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