Finite-Length Bounds for Joint Source-Channel Coding with Markovian Source and Additive Channel Noise to Achieve Large and Moderate Deviation Bounds

نویسندگان

  • Ryo Yaguchi
  • Masahito Hayashi
چکیده

We derive novel upper and lower finite-length bounds of the error probability in joint source-channel coding when the source obeys the ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive channel. These bounds achieve the tight bounds in the large and moderate deviation regimes. Index Terms Markov chain, joint source-channel coding, finite-length analysis, large deviation, moderate deviation

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عنوان ژورنال:
  • CoRR

دوره abs/1701.03305  شماره 

صفحات  -

تاریخ انتشار 2017