Modelling impulsive noise in indoor powerline communication systems
- PDF / 364,908 Bytes
- 7 Pages / 595.276 x 790.866 pts Page_size
- 61 Downloads / 213 Views
ORIGINAL PAPER
Modelling impulsive noise in indoor powerline communication systems Oktay Karaku¸s1,4
· Ercan E. Kuruoglu ˘ 2,3 · Mustafa A. Altınkaya4
Received: 29 July 2019 / Revised: 29 January 2020 / Accepted: 2 May 2020 © The Author(s) 2020
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 α-Stable (SαS), 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 SαS 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.
1 Introduction Smart grid technology, which is regarded as the next generation electric power infrastructure, is being developed day by day in order to provide a more efficient and safe power system. The ability to control this complex system automatically (or remotely) also makes it necessary to use advanced O. Karaku¸s: This work was entirely carried out during Oktay Karaku¸s’ stay in IZTECH as Ph.D. student, and he is now with the Visual Information Laboratory, University of Bristol, Bristol BS8 1UB, UK. E Kuruoglu is on leave from ISTI-CNR. This work was carried out while he was with ISTI-CNR.
B
Oktay Karaku¸s [email protected] Ercan E. Kuruo˘glu [email protected] Mustafa A. Altınkaya [email protected]
1
The Visual Information Laboratory, University of Bristol, Bristol BS8 1UB, UK
2
Data Science and Information Technology Center, Tsinghua–Berkeley Shenzhen Institute, Shenzhen, China
3
CNR, Istituto di Scienza e Tecnologie dell’Informazione, “A. Faedo”, Pisa, Italy
4
Electrical–Electronics Engineering, ˙Izmir Institute of Technology (IZTECH), ˙Izmir, Turkey
communication technologies [1]. Powerline communication (PLC) systems use power lines to carry telecommunication data. In PLC systems, a communication speed can be achieved up to 2Gbps with a good quality of service. PLC systems have important potential in applications, namely remote metering, distribution automation and internet access through home networking [2]. Moreover, PLC can also provide a physical environment for closed multimedia data traffic without additional cables. Despite all these competencies, the most challenging problem of PLC systems is the transmission of data in an environment d
Data Loading...
