Analysis of the PLC channel statistics using a bottom-up random simulator

We consider a top-down statistical channel generator where the transfer function between pair of nodes is computed using transmission line theory applied to a randomly generated in-home network topology. We describe the random topology model that has been derived from the observation of regulations and common practices in real scenarios. This approach allows a strong connection with physical reality and constitutes a theoretical framework that makes it possible to derive considerations on the statistical channel characteristics. We focus on the study of the statistics of the channel, we investigate the dependency from the model parameters, and we show that the generated channel responses can be classified in terms of average capacity, or in terms of the location of the associated nodes within the topology layout.