1. Comparative Study of Impulse Noise Models in the Narrow Band Indoor PLC Environment 10 th Workshop on Power Line Communications Paris, October 10-11, 2016 Authors Fatma Rouissi, Hélà Gassara, Adel Ghazel, Safa Najjar GRESCOM Lab, Ecole Supérieure des Communications de Tunis, University of Carthage, Tunisia fatma.rouissi@supcom.tn gassara.hela@supcom.tn adel.ghazel@supcom.tn safa.najjar@supcom.tn

2. Motivation & Challenges of NB-PLC 2 Low-cost and easy deployment Narrow-Band (NB) Power Line Communication (PLC) Indoor Network to support Smart Home and Building Control services Highly noisy transmission channel Line impedance variation Multi-path fading channel © Copyrights 2016, GRESCOM, 10 th WSPLC, Paris, October 10-11, 2016

3. Addressed Subject 3 © Copyrights 2016, GRESCOM, 10 th WSPLC, Paris, October 10-11, 2016 NB Impulsive Noise High Signal Corruption High PSD : -65 dBm/Hz to - 75 dBm/Hz in the frequency band until 500 KHz Random characteristics : Amplitude, Pulse duration, Inter-arrival time… Modeling approach choice to design efficient cancellation technique ? ? Different used models in literature : Averaging approach, Comparison with measurement ! Burst Errors

4. Impulse Noise Models 4 © Copyrights 2016, GRESCOM, 10 th WSPLC, Paris, October 10-11, 2016 ModelCharacteristics Middleton Class-A  Widely used in literature  Memoryless model, with a simple analytical formulation Bernoulli- Gaussian  Simpler than Middleton class-A  Also a Memoryless model, and Widely used in literature  Sum of two Gaussian pdfs weighted according to a Bernoulli distribution Markov  Takes into account the memory nature of impulse noise  Based on partitioned Markov chains with 2 groups of states for impulse event occurrence, and no impulse event, respectively Markov-Middelton  Model with memory, too, simpler than the one based on partitioned Markov chains  Modification of Middelton Class-A including Markov chains Stochastic  Based on a known form of pulses (damped sinusoid), with a statistical study of characteristic parameters  Approximation with known mathematical distribution

5. Outlines 5 Introduction Narrow Band Impulse Noise Measurement and Characterization Middleton Class A as a Memroyless Model Markov-Middleton Model Models Comparison Conclusion & Future Work © Copyrights 2016, GRESCOM, 10 th WSPLC, Paris, October 10-11, 2016

6. NB-PLC Impulse Noise Measurement Set-up 6 Test configuration Measurements NumberMore than 230 Frequency band9 kHz – 500 kHz (CENELEC/FCC/ARIB bands) PlaceLV laboratory, and Inside a several buildings of an academic campus TimeAt diverse times of the day Connected Loads  Different distances between the transmitter and the receiver  Different types of lamps, and connected loads  Various electrical devices (home appliances, PCs, air-conditioners, heaters,…)  2.5 MSPS digital oscilloscope  Compensated coupling circuit with the mains  Recorded noise segments set to 4 ms

7. NB-PLC Impulse Noise Characterization 7 Pulse ClassOccurrence Probability Class 143.88% (208 single pulses in the form of damped sinusoids) Class 224.47% (116 single pulses in exponential form) Class 312.24% (58 bursts of damped sinusoids) Class 419.41% (92 bursts of exponential pulses) Examples of measured (a) Class 1 pulses, (b) Class 2 pulses (c), Class3 pulses, (d) Class4 pulses. (a) (d) (c) (b) Pulses Classes Repartition

8. NB-PLC Impulse Noise Characterization 8 Cumulative distributions of the pulse duration for the different classes of impulsive noise.  For duration >1 µs, Class 1 pulses are longer than those of Class 2  For duration > 8 µs, bursts of Class 3 are shorter than those of Class 4

9. Middleton Class-A Model Principle Memoryless model, Seen as a superposition of an infinite number of impulsive source emissions, statistically independent and Poisson distributed in space and time Canonical and simple analytical formulation of the noise samples n k pdf Could be approximated, using only the first few terms of the pdf summation where ; ; Five-term approximation of the Middleton Class-A Model Entirely defined by parameters:  Impulsive index, A  density of pulses in one observation period,   the variance of the impulse noise   the Gaussian to impulse noise power ratio 9

10. Statistical Study of Middleton Class-A Model Parameters 10 Cumulative Distribution function of impulsive index A Cumulative Distribution function of Gaussian to impulsive noise power ratio  ParameterDistribution A Gamma (0.771;01236)  Log-normal (-2.6;15668)

11. Markov-Middleton Model Principle A model that takes into account the memory nature of the impulse noise Based on Markov Chains theory Introduction of a new parameter x  time correlation between noise samples Where is the impulse mean duration in terms of samples number 11 Markov-Middleton impulse noise model with five terms

12. 12 Statistical Study of Markov-Middleton Model Parameters  Impulsive index A  Gamma distribution  Gaussian to impulsive noise power ratio   log-normal distribution  Time correlation parameter x  Beta distribution Complementary Cumulative Distribution function of parameter x

13. Models Comparison in the Time Domain (1/2) 13 Noise segment generated by Middleton class-A Model Noise segment generated by Markov-Middleton Model i.i.d samples randomly distributed over the observation widow Different from a damped or exponential form

14. 14 Complementary cumulative distribution function of pulses duration Models Comparison in the Time Domain (2/2)

15. 15 Models Comparison in the Frequency Domain Mean PSD of Middleton Class-A noise in comparison with measurements Mean PSD of Markov-Middleton noise in comparison with measurements Almost same average value of the PSD in the band up to 500 KHz  -106.5 dBW/Hz = -76.5 dBm/Hz  No frequency effect on PSD of noises generated by both models  No pseudo periodic form of the generated noise  9 dB

16. Conclusion & Future Work 16  Comparison of the memoryless Middleton Class- A model to the Markov-Middleton model with memory  Particular focus on the two models adequacies to measured NB-PLC impulse noise:  Markov-Middleton model is more suitable to represent bursts  Independence of both models to the frequency  Study of BER performances of a NB-PLC transmission schema, in the presence of measured and modelled noise, and comparison of their effects on the transmission.

17. Thank You