Turbo Synchroniser

Physics

Scientific paper

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Scientific paper

ML decoder in a single entity for an Additive White Gaussian Noise (AWGN) channel. In particular, the likelihood function for the transmitted phase has been analised providing a reliability measure on the phase estimation. The phase value is estimated by means of a Decision Direct scheme and its reliability measure is used to merge the synchroniser with the decoder. Once the sequence has been decoded, it is provided back to the synchroniser circuit in order to have a new and better phase estimation. At the second iteration, the reliability measure is used to decide the most reliable phase value. variance is represented as function of SNR. On the right of the threshold the synchroniser achieves the lowest bound for a ML algorithm which is represented by the Cramér Rao Bound. especially when a turbo decoder is used. Indeed the iterative nature of the estimation algorithm suggests to merge it with the turbo-decoder circuit iterating either the sequence and the phase estimation.

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