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Accurate channel models are of high importance for the design of upcoming mobile satellite systems. Nowadays most of the models for the land mobile satellite channel (LMSC) are based on Markov chains and rely on measurement data, rather than on pure theoretical considerations. A key problem lies in the determination of the model parameters out of the observed data. In this work we face the issue of state identification of the underlying Markov model whose model parameters are a priori unknown. This can be seen as a hiddem Markov model (HMM) problem. For finding the maximum likelihood (ML) estimates of such model parameters the Baum-Welch (BW) algorithm is adapted} to the context of channel modeling. Numerical results on test data sequences reveal the capabilities of the proposed algorithm. Results on real measurement data are finally presented.

On the Application of the Baum-Welch Algorithm for Modeling the Land Mobile Satellite Channel