Abstract
The conventional per-survivor-processing (PSP) scheme suffers from the error propagation problem because it does not fully use the state message provided by a hidden Markov process. This study proposes a vertical cooperation among states to enhance the estimate reliabilities in the PSP scheme. The key idea of the proposed algorithm is to estimate the system uncertainty at each time stage in a maximum likelihood (ML) manner that chooses the parameter estimate of the state with the minimum cumulative branch metric as the survival estimate of the time stage. Computer simulations show that with the improved phase estimates, the proposed algorithm significantly outperforms the conventional PSP scheme in data decoding.
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