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Improvements in SOVA-Based Decoding for Turbo-Coded Storage Channels.

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Title: Improvements in SOVA-Based Decoding for Turbo-Coded Storage Channels.
Authors: Ghrayeb, Ali1 aghrayeb@ece.concordia.ca, Chuan Xiu Huang1
Source: IEEE Transactions on Magnetics. Dec2005, Vol. 41 Issue 12, p4435-4442. 8p.
Subjects: Algorithms, Turbo languages (Computer program language), Decoders (Electronics), Decoders & decoding, Lorentz transformations, Mathematical analysis
Abstract: In this paper, we propose a novel and simple approach for dealing with the exaggerated extrinsic information produced by the soft- output Viterbi algorithm (SOVA). We first identify the reason behind these exaggerated values and then propose a simple remedy for it. We argue that what leads to this optimistic extrinsic information is the inherent strong correlation between the intrinsic information (input to the SOVA) and extrinsic information (output of the SOVA). Our proposed remedy is based on mathematical analysis, and it involves using two attenuators, one applied to the immediate output of the SOVA and another applied to the extrinsic information before it is passed to the other decoder (assuming iterative decoding). We examine the modified SOYA (MSOVA) on idealized partial response (PR) channels and the Lorentzian channel equalized to a PR target. We consider both parallel concatenated codes (PCCs) and serial concatenated codes (SCCs). We show that the MSOVA provides substantial performance improvements over both channels. For example, it provides improvements of about 0.8 to 1.6 dB at Pb = 10-5. Finally, we note that the proposed modifications, while they provide considerable performance improvements, introduce only two additional multipliers to the complexity of the SOVA algorithm, which is remarkable. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Magnetics is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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DbLabel: Engineering Source
An: 19253188
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  Data: Improvements in SOVA-Based Decoding for Turbo-Coded Storage Channels.
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  Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Turbo+languages+%28Computer+program+language%29%22">Turbo languages (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22Decoders+%28Electronics%29%22">Decoders (Electronics)</searchLink><br /><searchLink fieldCode="DE" term="%22Decoders+%26+decoding%22">Decoders & decoding</searchLink><br /><searchLink fieldCode="DE" term="%22Lorentz+transformations%22">Lorentz transformations</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+analysis%22">Mathematical analysis</searchLink>
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  Data: In this paper, we propose a novel and simple approach for dealing with the exaggerated extrinsic information produced by the soft- output Viterbi algorithm (SOVA). We first identify the reason behind these exaggerated values and then propose a simple remedy for it. We argue that what leads to this optimistic extrinsic information is the inherent strong correlation between the intrinsic information (input to the SOVA) and extrinsic information (output of the SOVA). Our proposed remedy is based on mathematical analysis, and it involves using two attenuators, one applied to the immediate output of the SOVA and another applied to the extrinsic information before it is passed to the other decoder (assuming iterative decoding). We examine the modified SOYA (MSOVA) on idealized partial response (PR) channels and the Lorentzian channel equalized to a PR target. We consider both parallel concatenated codes (PCCs) and serial concatenated codes (SCCs). We show that the MSOVA provides substantial performance improvements over both channels. For example, it provides improvements of about 0.8 to 1.6 dB at Pb = 10-5. Finally, we note that the proposed modifications, while they provide considerable performance improvements, introduce only two additional multipliers to the complexity of the SOVA algorithm, which is remarkable. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of IEEE Transactions on Magnetics is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1109/TMAG.2005.857453
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      – Code: eng
        Text: English
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      Pagination:
        PageCount: 8
        StartPage: 4435
    Subjects:
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Turbo languages (Computer program language)
        Type: general
      – SubjectFull: Decoders (Electronics)
        Type: general
      – SubjectFull: Decoders & decoding
        Type: general
      – SubjectFull: Lorentz transformations
        Type: general
      – SubjectFull: Mathematical analysis
        Type: general
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      – TitleFull: Improvements in SOVA-Based Decoding for Turbo-Coded Storage Channels.
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            NameFull: Ghrayeb, Ali
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            NameFull: Chuan Xiu Huang
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              M: 12
              Text: Dec2005
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              Y: 2005
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            – TitleFull: IEEE Transactions on Magnetics
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