Journal article
Applications of artificial intelligence in powerline communications in terms of noise detection and reduction: a review
Australian journal of electrical & electronics engineering, v 15(1-2), pp 29-37
03 Apr 2018
Abstract
The technology which utilises the power line as a medium for transferring information known as powerline communication (PLC) has been in existence for over a hundred years. It is beneficial because it avoids new installation since it uses the present installation for electrical power to transmit data. However, transmission of data signals through a power line channel usually experience some challenges which include impulsive noise, frequency selectivity, high channel attenuation, low line impedance, etc. The impulsive noise exhibits a power spectral density within the range of 10-15 dB higher than the background noise, which could cause a severe problem in a communication system. For better outcome of the PLC system, these noises must be detected and suppressed. This paper reviews various techniques used in detecting and mitigating the impulsive noise in PLC and suggests the application of machine learning algorithms for the detection and removal of impulsive noise in powerline communication systems.
Metrics
5 Record Views
6 citations in Scopus
Details
- Title
- Applications of artificial intelligence in powerline communications in terms of noise detection and reduction: a review
- Creators
- Olamide M. Shekoni - University of JohannesburgAli N. Hasan - University of JohannesburgThokozani Shongwe - University of Johannesburg
- Publication Details
- Australian journal of electrical & electronics engineering, v 15(1-2), pp 29-37
- Publisher
- Taylor & Francis
- Number of pages
- 9
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Engineering Leadership and Society/Engineering Technology
- Scopus ID
- 2-s2.0-85050366674
- Other Identifier
- 991022004632404721