Large and Moderate Deviations for Joint Source-Channel Coding of Systems With Markovian Memory
نویسندگان
چکیده
We derive novel upper and lower finite length bounds of the error probability in joint source-channel coding when the source is distributed according to an ergodic Markov process and the channel is a Markovian additive channel or a Markovian conditional additive channel. We show that these bounds are tight in the moderate deviations regime and for a certain interval of rates, also in the large deviations regime. Index Terms Markovian source, Markovian channel, Joint source-channel coding, Finite-length analysis, Large deviations, Error exponent, Moderate deviations
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Finite-Length Bounds for Joint Source-Channel Coding with Markovian Source and Additive Channel Noise to Achieve Large and Moderate Deviation Bounds
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-l...
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