• Corpus ID: 9747335

Two-Dimensional Magnetic Recording: Read Channel Modeling and Detection

@inproceedings{Krishnan2009TwoDimensionalMR,
  title={Two-Dimensional Magnetic Recording: Read Channel Modeling and Detection},
  author={A.R. Krishnan and Rathnakumar Radhakrishnan and Bane V. Vasic and Aleksander Kavcic and William Ryan and Fatih Erden},
  year={2009}
}
of upto 10 Tb/in 2 . It uniquely differs from other proposed next-generation architectures because of its reliance on sophisticated two-dimensional signal processing algorithms. Recently, a number of contributions have been made in the development of read-channel models and detectors for TDMR systems. In this paper, we provide a detailed review on all important readchannel models under consideration. Our discussion focuses on the purpose of each of these models, placing a special emphasis on… 
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A new writing method is introduced that can decrease the nonlinear media error effectively effectively, and it can also achieve 10 Tb/in2 of user bit density on a magnetic recording medium with 20 Teragrains/in².
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TLDR
A communication theoretic framework for modeling 2-D magnetic recording channels and defines the signal-to-noise ratio (SNR) for the channel considering several physical parameters, such as the channel bit density, code rate, bit aspect ratio, and noise parameters.
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TLDR
An advanced channel model is made use: the grain-flipping probability model, to perform an equivalent optimization together with a software recording channel that is able to include the impact of the generalized partial response equalizer, soft-output Viterbi algorithm detector, and low density parity check decoder on the final performance.
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