The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical Engineering University of Southern California

Technical Report USC-SIPI-367

“Iterative Detection for Page-Oriented Optical Data Storage Systems”

by Nopparit Intharasombat

August 2005

Data storage requirements have rapidly increased in the past few years due to the development of several storage-intensive applications. Beside high storage capacity, other desirable characteristics of data storage systems are high data transfer rate and fast access time. Page-oriented optical data storage systems (PODS) with their parallel readout channels and volumetric storage area have good potential for becoming the next generation data storage system. In particular, we develop signal processing techniques for two-photon PODS systems.

We concentrate on modulation and detection aspects of the system including protecting data against sources of interference that cause errors. The three main interference sources are intersymbol interference (ISI), interpage interference (IPI) and additive noise. Our main effort is to mitigate ISI and IPI in the presence of noise. The level of ISI and IPI becomes more pronounced as the data bit packing density increases. Typical methods of combating an ISI problem (a channel with memory) are equalization-based methods. However, the computational complexity of equalization methods depends on the channel memory length, which is directly proportional to the level of ISI and IPI.

We describe an iterative algorithm and extensions that mitigate ISI and IPI in the presence of additive noise, while maintaining acceptable bit-error-rate. The algorithm uses a decision-feedback equalization-like approach. The algorithm effectively removes the ISI effects contributed by neighboring pixels from the received intensity and either makes a decision based on this result or defers making a decision if the result cannot be classified with a strong certainty. The decision is later verified by checking the consistency between the estimated value and the received intensity. The pixels that fail the consistency test are assigned a new value by following a set of correction rules.

Our algorithm is further extended to mitigate a combination of ISI and IPI. The IPI problem is essentially a three-dimensional ISI problem and the relevant data pages extend from several preceding pages to several proceeding pages. To solve this causality problem, a pipelined processing is implemented. We also extend our algorithm to implement multi-level encoding. A joint error correction/detection method is used to combat ISI effect with non-binary encoding.

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