2-D Signal Processing and Coding for Digital Page- Oriented Memories

Digital page-oriented Volume Holographic Storage
(VHS) is a promising digital storage technology
because of its high data storage density, high data
rate and short access times. As the storage density
increases, the performance of volume holographic
storage channels is degraded due to increased two-
dimensional (2-D) intersymbol interference (ISI) and
noise. The output detector array in VHS detects the
intensity of the incident light wave-front leading
to sign information loss. This sign loss precludes
the applicability of conventional
equalization/detection schemes to mitigate ISI. In
this book, we first address channel modeling under
the quadratic nonlinearity and then develop 2-D
equalization/detection methods such as linear
minimum mean square (LMMSE) equalization, iterative
magnitude square decision feed back equalization
(IMS DFE) and partial response maximum likelihood
(PRML) to mitigate 2-D ISI under quadratic
nonlinearity. We also evalu ate the effect of
modulation coding, particularly balanced codes and
low pass coding. We finally investigate the
performances of the equalization/detection methods
under optical magnification error.

Autorentext

Dr.Mehmet Keskinoz got his Ph.D degrees from Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh (USA) in 2001.Then he joined to Sabanci University Electronics Engineering Program, Istanbul, Turkey. His research interests include signal processing and coding for wired and wireless communications and watermarking.

Klappentext

Digital page-oriented Volume Holographic Storage (VHS) is a promising digital storage technology because of its high data storage density, high data rate and short access times. As the storage density increases, the performance of volume holographic storage channels is degraded due to increased two-dimensional (2-D) intersymbol interference (ISI) and noise. The output detector array in VHS detects the intensity of the incident light wave-front leading to sign information loss. This sign loss precludes the applicability of conventional equalization/detection schemes to mitigate ISI. In this book, we first address channel modeling under the quadratic nonlinearity and then develop 2-D equalization/detection methods such as linear minimum mean square (LMMSE) equalization, iterative magnitude square decision feed back equalization (IMS¬DFE) and partial response maximum likelihood (PRML) to mitigate 2-D ISI under quadratic nonlinearity. We also evalu¬ate the effect of modulation coding, particularly balanced codes and low pass coding. We finally investigate the performances of the equalization/detection methods under optical magnification error.