The installation of wireless technologies in power substations requirescharacterizing the impulsive noise produced by the high-voltage equipment.Substation impulsive noise might interfere with classic wireless communicationsand none of the existing models can reliably represent this noise in wide band.Previous studies have shown that impulsive noise is characterized by series ofdamped oscillations with the amplitude, the duration and the occurrence timesof the impulses that are random. All these characteristics make this noisetime-correlated and the partitioned Markov chain remains an efficient modelthat can ensure the correlation between the samples. In this study, we proposeto design a partitioned Markov chain to generate an impulsive noise that issimilar to the noise measured in existing substations, in time and frequencydomains. We configure our Markov chain to produce the impulses with the dampedoscillation effect, then, we determine the probability transition matrix andthe distribution of each state of the Markov chain. Finally, we generate noisesamples and we study the distribution of the impulsive noise characteristics.Our Markov chain model can replicate the correlation between the measured noisesamples; also the distributions of the noise characteristics are similar in thesimulations and the measurements.
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