DocumentCode :
73779
Title :
A Markov-Middleton Model for Bursty Impulsive Noise: Modeling and Receiver Design
Author :
Ndo, G. ; Labeau, Fabrice ; Kassouf, Marthe
Author_Institution :
Dept. of Electr. & Comput. Eng., McGill Univ., Montreal, QC, Canada
Volume :
28
Issue :
4
fYear :
2013
fDate :
Oct. 2013
Firstpage :
2317
Lastpage :
2325
Abstract :
Transmission over channels impaired by impulsive noise, such as in power substations, calls for peculiar mitigation techniques at the receiver side in order to cope with signal deterioration. For these techniques to be effective, a reliable noise model is usually required. One of the widely accepted models is the Middleton Class A, which presents the twofold advantage to be canonical (i.e., invariant of the particular physical source mechanisms) and to exhibit a simple probability density function (PDF) that only depends on three physical parameters, making this model very attractive. However, such a model fails in replicating bursty impulsive noise, where each impulse spans over several consecutive noise samples, as usually observed (e.g., in power substations). Indeed, the Middleton Class A model only deals with amplitude or envelope statistics. On the other hand, for models based on Markov chains, although they reproduce the bursty nature of impulses, the determination of the suitable number of states and the noise distribution associated with each state can be challenging. In this paper, 1) we introduce a new impulsive noise model which is, in fact, a Hidden Markov Model, whose realizations exactly follow a Middleton Class A distribution and 2) we evaluate optimum and suboptimum detections for a coded transmission impaired by the proposed noise model.
Keywords :
hidden Markov models; impulse noise; probability; radio receivers; signal processing; statistics; Markov chains; Markov-Middleton model; PDF; bursty impulsive noise; envelope statistics; hidden Markov model; peculiar mitigation techniques; probability density function; receiver design; signal deterioration; transmission over channels; Channel coding; Hidden Markov models; Markov processes; Maximum a posteriori estimation; Noise; Channel coding; Hidden Markov model (HMM); Markov chain; Middleton class A model; impulsive noise modeling; maximum a posteriori (MAP) detection;
fLanguage :
English
Journal_Title :
Power Delivery, IEEE Transactions on
Publisher :
ieee
ISSN :
0885-8977
Type :
jour
DOI :
10.1109/TPWRD.2013.2273942
Filename :
6575205
Link To Document :
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