Title :
Bottom-Up Statistical PLC Channel Modeling—Part I: Random Topology Model and Efficient Transfer Function Computation
Author :
Tonello, Andrea M. ; Versolatto, Fabio
Author_Institution :
Dipt. di Ing. Elettr., Gestionale e Meccanica, Univ. di Udine, Udine, Italy
fDate :
4/1/2011 12:00:00 AM
Abstract :
We propose an efficient bottom-up power-line communication (PLC) channel simulator that exploits transmission-line theory concepts and that is able to generate statistically representative in-home channels. We first derive from norms and practices a statistical model of European in-home topologies. The model describes how outlets are arranged in a topology and are interconnected via intermediate nodes referred to as derivation boxes. Then, we present an efficient method to compute the channel transfer function between any pair of outlets belonging to a topology realization. The method is based on a systematic remapping technique that leads to the subdivision of the network in elementary units, and on an efficient way to compute the unit transfer function referred to as the voltage ratio approach. The difference from the more conventional and complex ABCD matrix approach is also discussed. We finally show that the simulator can be configured with a small set of parameters and that it offers a theoretical framework to study the statistical PLC channel properties as a function of the topology characteristics, which is discussed in Part II of this work.
Keywords :
carrier transmission on power lines; matrix algebra; statistical analysis; transfer functions; ABCD matrix; European in-home topologies; bottom-up statistical PLC channel modeling; channel transfer function; elementary units; in-home channels; power-line communication channel simulator; statistical model; systematic remapping technique; transfer function computation; transmission-line theory; unit transfer function; Channel modeling; in-home networks; power-line communications;
Journal_Title :
Power Delivery, IEEE Transactions on
DOI :
10.1109/TPWRD.2010.2096518