Artificial neural network modeling approach to power-line communication multi-path channel

Abstract

A trained neural network can be used for high-level design, providing fast and accurate answers to the task it has learned. Neural networks are effective alternatives to conventional methods such as statistical and stochastic modeling methods, which could be computationally expensive, or analytical methods which could be difficult to obtain for new environments, or empirical modeling solutions whose range and accuracy may be limited. Power-line communication (PLC) is a useful way to transmit data and exchange information based on power-line channel. Due to the multi-path propagation inherently in the power line channel, the characteristic of power line channel is analyzed in this paper. The modeling of multi-path propagation is completed base on conventional way and ANN. Results of different modeling methods are analyzed. It is proved that ANN-based modeling of communication channel is an efficient method. This makes stable foundation for future power-line communication simulation.