Modelling Impulsive Noise in Indoor Powerline Communication Systems

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Date

2020

Authors

Journal Title

Journal ISSN

Volume Title

Publisher

Springer Verlag

Open Access Color

HYBRID

Green Open Access

Yes

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Publicly Funded

No
Impulse
Top 10%
Influence
Top 10%
Popularity
Top 10%

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Abstract

Powerline communication (PLC) is an emerging technology that has an important role in smart grid systems. Due to making use of existing transmission lines for communication purposes, PLC systems are subject to various noise effects. Among those, the most challenging one is the impulsive noise compared to the background and narrowband noise. In this paper, we present a comparative study on modelling the impulsive noise amplitude in indoor PLC systems by utilising several impulsive distributions. In particular, as candidate distributions, we use the symmetric alpha-Stable (S alpha S), generalised Gaussian, Bernoulli Gaussian and Student's t distribution families as well as the Middleton Class A distribution, which dominates the literature as the impulsive noise model for PLC systems. Real indoor PLC system noise measurements are investigated for the simulation studies, which show that the S alpha S distribution achieves the best modelling success when compared to the other families in terms of the statistical error criteria, especially for the tail characteristics of the measured data sets.

Description

Keywords

Comparative studies, Impulse noise, Power line communication system, Power line communications (PLC), Smart grid systems, Emerging technologies, Carrier transmission on power lines, Statistical errors, Simulation studies, Impulsive noise models

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Citation

WoS Q

Q3

Scopus Q

Q2
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OpenCitations Citation Count
18

Source

Signal Image and Video Processing

Volume

14

Issue

8

Start Page

1655

End Page

1661
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Citations

CrossRef : 16

Scopus : 28

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Mendeley Readers : 12

SCOPUS™ Citations

27

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Web of Science™ Citations

22

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Page Views

1123

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Downloads

277

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