Digital Channel Modeling through Chaotic Generators

Recently, digital channel modeling through chaotic generators has attracted strong interest at literature. Many of them refer to the generation of error detected time series from where we can obtain channel's statistics. In this paper we present a complete modeling of the error-gap distribution (EGD) statistic that helps us to know how the errors are distributed through the channel. Our principal aim was to generate error time series with statistics properties similar to those that we can obtain from a reference model, such as Markov chains based models. Under these considerations, we implemented these algorithms of error time series generation in a digital signal processor (DSP) using as reference three models of real digital channels from literature.