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Due to rapid interest on the applications of convolutional tail-biting to communication systems, several suboptimal algorithms have been proposed to achieve near-optimal Word error rate (WER) performances with circular Viterbi decoding approach. Among them, the wrap-around Viterbi algorithm (WAVA) proposed is the one with least decoding complexity. Very recently, a maximum likelihood (ML) decoding...
Recently, a maximum-likelihood (ML) decoding algorithm with two phases has been proposed for convolutional tailbiting codes. The first phase applies the Viterbi algorithm to obtain the trellis information, and then the second phase employs the algorithm A* to find the ML solution. In this work, we improve the complexity of the algorithm A* by using a new evaluation function. Simulations showed that...
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