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>IMPROVEMENT OF HIDDEN MARKOV MODEL EVALUATION OF THE MOBILE SATELLITE CHANNEL BY RESORTING TO A TRANSITION LOCALISATION METHOD
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IMPROVEMENT OF HIDDEN MARKOV MODEL EVALUATION OF THE MOBILE SATELLITE CHANNEL BY RESORTING TO A TRANSITION LOCALISATION METHOD
The mobile satellite channel has underlying Markovian properties and can then be represented by a Hidden Markov model (HMM). A challenging problem consists in estimating the model parameters from experimental data, especially when these parameters are not easily identifiable. In these cases, classification methods like k-means or scalable clustering, which are considered in this paper, show poor results when applied to the channel signal directly. We show that the detection of change-points of the signal, i.e. the detection of transitions between the model states, in a preliminary step, improves the estimation of the model parameters. We thus propose a method of model estimation including the detection of change-points that enables a better modelling of the satellite channel.
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