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Decoding LDPC Convolutional Codes on Markov Channels

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Abstract

This paper describes a pipelined iterative technique for joint decoding and channel state estimation of LDPC convolutional codes over Markov channels. Example designs are presented for the Gilbert-Elliott discrete channel model. We also compare the performance and complexity of our algorithm against joint decoding and state estimation of conventional LDPC block codes. Complexity analysis reveals that our pipelined algorithm reduces the number of operations per time step compared to LDPC block codes, at the expense of increased memory and latency. This tradeoff is favorable for low-power applications.

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Correspondence to Manohar Kashyap.

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Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License (https://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Kashyap, M., Winstead, C. Decoding LDPC Convolutional Codes on Markov Channels. J Wireless Com Network 2008, 729180 (2008). https://doi.org/10.1155/2008/729180

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Keywords

  • Expense
  • State Estimation
  • System Application
  • Complexity Analysis
  • Channel State