Impulsive Noise Models Used in Power Line Communications

Abstract

In a communication system, noise has always been considered as a serious cause of error. Although most common noises can be modeled by well-known Gaussian distributions, some communication systems experience other types of noise. Power Line Communication (PLC) is one of these systems which run on a difficult medium since it uses the preexisting power line network for transmission. PLC experiences several different types of human-made and natural noise which are mostly impulsive and cannot be modeled simply by Gaussian. Different statistical models are used for characterizing the impulsive noise of PLC systems in the literature. The purpose of this study is to go over the impulsive noise models previously presented in order to have a contribution to this hot topic. We point out the similarities and differences of the models, namely Middleton Class A, Bernoulli Gaussian and Alpha Stable statistical models. It is presented that all have heavy tails which make them appropriate for impulsive noise. Although Middleton Class A is more generic, Bernoulli Gaussian model is wide enough and can be preferable because of its compact simple form especially when analytical results are needed.

Comparison of Time and Time-Frequency Domains Impulsive Noise Mitigation Techniques for Power Line Communications

“…In Çürük [15], narrowband PLC time variations and nonwhite noise are represented mathematically for the first time. N. Andreadou [16] proposed a noise model for power line channels that is easy to apply.…”