Two-Dimensional Optical Storage

Coene, W.; Bruls, Dominique; Immink, A.H.J.; Lee, A.M. van der; Hekstra, A.P.; Riani, J.; Beneden, S. Van; Ciacci, M.; Bergmans, J.W.M.; Furuki, Motohiro

doi:10.1109/icassp.2005.1416412

Cited by 27 publications

(17 citation statements)

References 5 publications

(5 reference statements)

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“…Also shown is the periodic nature of our interactions. The bit on the boundary, (5,4), interacts with (5, 5), (5,3), (4,4), (1,4). Similar periodic interactions are also present (but not shown in the figure) for information bits which belong to the top-most row (they have one interaction with a bt on the bottom-most row).…”

Section: B Interference Patternmentioning

confidence: 80%

“…We consider periodic grid interaction so that we can rule out any boundary effects which would influence the LP detector. (3,2) interacting with its 4 neighbors, (2, 2), (4, 2), (3,3), (3,1). Also shown is the interaction of a bit in the boundary.…”

Section: B Interference Patternmentioning

confidence: 95%

“…Although it seems the hexagonal interaction is the design choice for the TwoDOS system because of its higher density [1] we perform our experiments on the 4-neighborhood for demonstrating our methods.…”

Section: Optimal Detection and The Integer Programmentioning

confidence: 99%

“…2D systems will naturally suffer from 2D ISI. One such 2D storage system is the TwoDOS (two-dimensional optical storage) [1], [2]. Detection in TwoDOS reduces to detection on a 2D lattice or grid.…”

Section: Introductionmentioning

confidence: 99%

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Linear programming based detectors for two-dimensional intersymbol interference channels

Kudekar

Johnson

Chertkov

2011

2011 IEEE International Symposium on Information Theory Proceedings

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Abstract-We present and study linear programming based detectors for two-dimensional intersymbol interference channels. Interesting instances of two-dimensional intersymbol interference channels are magnetic storage, optical storage and Wyner's cellular network model.We show that the optimal maximum a posteriori detection in such channels lends itself to a natural linear programming based sub-optimal detector. We call this the Pairwise linear program detector. Our experiments show that the Pairwise linear program detector performs poorly. We then propose two methods to strengthen our detector. These detectors are based on systematically enhancing the Pairwise linear program. The first one, the Block linear program detector adds higher order potential functions in an exhaustive manner, as constraints, to the Pairwise linear program detector. We show by experiments that the Block linear program detector has performance close to the optimal detector. We then develop another detector by adaptively adding frustrated cycles to the Pairwise linear program detector. Empirically, this detector also has performance close to the optimal one and turns out to be less complex then the Block linear program detector.

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Section: B Interference Patternmentioning

confidence: 80%

Section: B Interference Patternmentioning

confidence: 95%

Section: Optimal Detection and The Integer Programmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Linear programming based detectors for two-dimensional intersymbol interference channels

Kudekar

Johnson

Chertkov

2011

2011 IEEE International Symposium on Information Theory Proceedings

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“…The performance is evaluated in terms of BER of the detected binary image experiencing i.i.d. Gaussian noise with where * denotes 2D convolution of the image f by a 2D interference mask c defined in (1). The PD and MD in the two-phase ISI detection are realised by the 3 × 3 DF-HD and 4 × 2 IRCSDFA, respectively.…”

Section: Simulation Resultsmentioning

confidence: 99%

Simplification of strip‐wise algorithms applied for two‐dimensional intersymbol interference detection

Lee

Lin

2014

IET Communications

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With the development of the high-speed communication channel or high-capacity storage device, the intersymbol interference (ISI) occurs more frequently in the condensed data. The traditional Bahl -Cocke -Jelineu -Raviv (BCJR) method is capable of solving the two-dimensional (2D) symbol influence problem with extremely high cost. By analysing the complexity in terms of branch, state and path in the 2D trellis-based ISI detection, the authors verify that the system complexity is mainly dominated by the window size. To reduce the detection complexity, the conventional simplifications are applied in the 2D stripwise ISI detection. In addition, a two-phase strip-wise detection is proposed to achieve a lower complexity than that of the conventional simplifications. In this system, the first detector can be realised by a low-complexity method (like the hard detection or Viterbi algorithm) to provide the mask shrinking with predicted data. After reducing the mask size, the second detector can detect the main portion of ISI by the trellis-based detection (like BCJR algorithm) with a small mask. Under the similar detection performance, the proposed scheme can achieve more than 91.76% saving in the metric computation compared with the 5 × 3-window IRCSDFA (iterative row-column soft-decision feedback algorithm) simplified by the M-algorithm with M = 8.

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Nyquist pulse shaping criterion for two-dimensional systems

Yang

Pandharipande

Bergmans

2008

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

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We present Nyquist pulse shaping conditions for twodimensional (2-D) digital communication systems to be free from inter-symbol interference, for general regular sampling grids. We provide examples of 2-D pulse functions satisfying these Nyquist conditions. In particular, we show that a family of 2-D pulse functions that we construct as separable pulse functions from one-dimensional Nyquist-1 pulse functions obey the 2-D Nyquist criterion and moreover include the one with minimum support area in the frequency domain.

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Two-Dimensional Optical Storage

Cited by 27 publications

References 5 publications

Linear programming based detectors for two-dimensional intersymbol interference channels

Linear programming based detectors for two-dimensional intersymbol interference channels

Simplification of strip‐wise algorithms applied for two‐dimensional intersymbol interference detection

Nyquist pulse shaping criterion for two-dimensional systems

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