Initial (final) state estimation in error-trellises for tail-biting convolutional codes
M Tajima, K Okino, T Murayama - IEICE Transactions on …, 2014 - search.ieice.org
M Tajima, K Okino, T Murayama
IEICE Transactions on Fundamentals of Electronics, Communications and …, 2014•search.ieice.orgIn this paper, we clarify the relationship between an initial (final) state in a tail-biting error-
trellis and the obtained syndromes. We show that a final state is dependent on the first M
syndromes as well, where M is the memory length of the parity-check matrix. Next, we
calculate the probability of an initial (final) state conditioned by the syndromes. We also
apply this method to concrete examples. It is shown that the initial (final) state in a tail-biting
error-trellis is well estimated using these conditional probabilities.
trellis and the obtained syndromes. We show that a final state is dependent on the first M
syndromes as well, where M is the memory length of the parity-check matrix. Next, we
calculate the probability of an initial (final) state conditioned by the syndromes. We also
apply this method to concrete examples. It is shown that the initial (final) state in a tail-biting
error-trellis is well estimated using these conditional probabilities.
In this paper, we clarify the relationship between an initial (final) state in a tail-biting error-trellis and the obtained syndromes. We show that a final state is dependent on the first M syndromes as well, where M is the memory length of the parity-check matrix. Next, we calculate the probability of an initial (final) state conditioned by the syndromes. We also apply this method to concrete examples. It is shown that the initial (final) state in a tail-biting error-trellis is well estimated using these conditional probabilities.
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