Burst-Error Statistics Obtained by ML Estimation of a New Structured Markov Channel Model

A new Markovian model (MM) for burst-error generation has been recently presented by the authors. This model is conveniently structured, with the double purpose of reproducing the generation of some typical patterns of burst error sequences and facilitating the maximum-likelihood (ML) estimation of the its parameters. In the present work we show that this model also turns out to be useful for obtaining simple expressions for several statistics of great interest in the context of modeling and performance evaluation of communications systems degraded by burst-errors. So we propose to use these analytical expressions fulfilled with ML estimates of the model parameters in order to obtain good models for the above mentioned statistics. Some numerical results are presented that illustrate the effectiveness of this approach.