Bibliographic Details
| Title: |
Time Series Modelling of Powerline Communication Impulsive Noise: Queuing Theory Approach. |
| Authors: |
Chelangat, Florence1 florencebiwott7@gmail.com, Afullo, Thomas1 |
| Source: |
Progress in Electromagnetics Research C. 2024, Vol. 150, p157-168. 12p. |
| Subjects: |
Distribution (Probability theory), Burst noise, Infinite processes, Time series analysis, Communication models, Queuing theory |
| Abstract: |
The rate at which powerline communication (PLC) impulsive noise arrives and lasts in the channel determines the severity of signal degradation, with impulsive noise bursts capable of causing complete signal loss. Consequently, the PLC impulsive noise requires an appropriate description to enhance the reliability and effective utilisation of the PLC channel. This paper employs the queuing theory approach to analyse and model the PLC impulsive noise inter-arrival and service time distribution, where the impulsive noise is categorised into single-impulse noise events and burst-impulse noise events. The Erlang-k distribution is proposed for modelling both the inter-arrival and service time distributions for the PLC impulsive noise with the process viewed as an infinite queue with a single server. The impulse noise events are assumed to traverse k stages before entering the PLC network and also pass through k stages before leaving the PLC network, with each of the stages following an exponential distribution. The proposed models are then validated through measurements from different indoor environments and compared to the exponential distribution model, commonly employed in modelling inter-arrival and duration of PLC impulsive noise. The Ek/Ek/1 queue model is determined to adequately model the burst-impulse noise events. In regards to the single-impulse noise events, the exponential distribution is observed to provide a suitable fit for the inter-arrival time distribution. The occurrence of PLC impulsive noise events is also found to achieve a state of equilibrium for all the measurement data under study. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |