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Università degli Studi di UdineWireless and Power Line Communications Laboratory
9th Workshop on Power Line Communications (WSPLC)21-22 September 2015 – Klagenfurt – Austria
New Results in Channel Modelling
Alberto Pittolo and Andrea M. Tonello
WiPli Lab – University of Udine, ItalyEcoSys Lab – Alpen-Adria-Universität, Austria
Summary
Quick overview Market requirements Power line communication scenario Our research group activities
Channel characterization Scenarios comparison Average statistical metrics
Channel modeling & Results Possible approaches Synthetic channel model Numerical results
Conclusions
Pittolo Alberto – PLC Channel Analysis & Synthetic Channel Modeling2
Quick overviewMain demands from the telecommunication market and briefoverview about the PLC channel phenomena.
Pittolo Alberto – PLC Channel Analysis & Synthetic Channel Modeling3
Market Requirements
Customers demand High speed connectivity Reliable data transfer Pervasive coverage Robustness & availability
Industries want Save production costs Short developing time Quick and easy testing
These features depend on the medium characteristics
Pittolo Alberto – PLC Channel Analysis & Synthetic Channel Modeling4
Power Line Communication Scenario
Well known PLC channel phenomena Extreme channel variability
• Unmatched loads• Line discontinuities
Severe frequency selectivity Attenuation & Distortion
• Several branches (multipath)
Noise detrimental effects Stationary background noise
• Colored & Correlated Non-stationary impulsive noise
• Synchronous & Asynchronous
Pittolo Alberto – PLC Channel Analysis & Synthetic Channel Modeling5
[REF] F. J. Cañete, J. A. Cortés, L. Díez, and J. T. Entrambasaguas, “Analysis of the cyclic short-term variation of indoor powerline channels,” IEEE J. Select. Areas Commun., vol. 24, no. 7, pp. 1327-1338, Jul 2006.
PLC Networks Heterogeneity
A variety of different application scenarios Indoor scenario
• Home• Buildings• Vehicles (car, ship, plane, …)
Outdoor scenario• Low voltage (LV)• Medium voltage (MV)• High voltage (HV)
Attractive solution, especially in the Smart Grid context The focus is on the broadband frequency range
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[REF] S. Goel, S.F. Bush, and D. Bakken, eds., IEEE Vision for Smart Grid Communications: 2030 and Beyond, IEEE Std.Association, 2013.
Research Group Activities
Measuring & characterization Impairments Channel properties Implicit relationships
Models development Simple & effective Exploiting smart solutions
Emulators implementation Software simulators Hardware devices
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Channel CharacterizationDifferent types of environments are compared in terms of themost commonly used statistical metrics.
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Scenarios Comparison
Attenuation ↑ Dispersion ↑ In-home (ITA, USA & ESP)
• Good match In-car (electric & conventional)
• Short wires DS ↓ In-ship Outdoor (LV & MV)
• Branches + Length ACG ↓
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[R1] A. M. Tonello, F. Versolatto, and A. Pittolo, “In-home power linecommunication channel: Statistical characterization,” IEEE Trans.Commun., vol. 62, no. 6, pp. 2096-2106, Jun. 2014.[R2] J. A. Cortés, F. J. Cañete, L. Díez, and J. L. G. Moreno, “On thestatistical properties of indoor power line channels: Measurementsand models,” in IEEE ISPLC, Apr. 2011, pp. 271-276.[R3] S. Galli, “A novel approach to the statistical modeling of wirelinechannels,” IEEE Trans. Commun.,vol.59, no.5,pp.1332-1345,May 2011.[R4] F. Versolatto, A. M. Tonello, C. Tornelli, and D. D. Giustina,“Statistical analysis of broadband underground medium voltagechannels for PLC applications,” in IEEE SmartGridComm, Nov. 2014.
[R5] M. Antoniali, M. De Piante, A. M. Tonello, “PLC Noise and ChannelCharacterization in a Compact Electrical Car,” in IEEE ISPLC, Mar. 2013.[R6] M. Antoniali, A. M. Tonello, M. Lenardon, A. Qualizza,“Measurements and Analysis of PLC Channels in a Cruise Ship,” in IEEEISPLC, Udine, Italy, April 3-6, 2011, pp. 102-107.[R7] M. Mohammadi, L. Lampe, M. Lok, S. Mirabbasi, M. Mirvakili, R.Rosales, and P. Van Veen, “Measurement Study and Transmission for In-Vehicle Power Line Communication,” in IEEE ISPLC, Mar 2009, pp.73-78.[R8] M. Babic, M. Hagenau, K. Dostert, and J. Bausch, “Theoreticalpostulation of the PLC channel model OPERA,” IST Integrated ProjectNo. 507667 funded by EC, Tech. Rep., Mar 2005, OPERA Deliverable D4
Average Statistical Metrics
Average channel gain (ACG) Similar for indoor scenarios
• Lowest for the in-ship High for outdoor lines
• Long cables• Many branches
RMS delay spread (DS) High for outdoor Relevant for home & ship Low for the in-car context
• Short wires• Few branches
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Scenario Band (MHz) (dB) (μs) (kHz)In-home 1.8− 50 − 33.10 0.357 251.48In-ship 1.8− 50 − 22.89 0.320 258.83
In-car (CC) 1.8− 50 − 27.33 0.102 677.14In-car (EC) 1.8− 50 − 33.25 0.086 874.26Outdoor LV 1.8− 50 − 56.96 0.581 140.63
Outdoor MV 1.8− 50 − 44.39 0.722 399.59
Channel Modelling &Simulation ResultsIntroducing the concepts underlying a novel top-downsynthetic channel model based on the CFR. Some results areprovided
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Channel Modeling
Modelling is appealing since Avoids on field testing Is cheap, quick and simple Reproduces different scenarios
Two possible methods Deterministic Statistical
Two dual approaches Bottom-up Top-down
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[R1] T. Esmailian, F.R. Kschischang, and P. Glenn Gulak, “In-Building Power Lines as High-Speed Communication Channels:Channel Characterization and a Test Channel Ensemble,” Intern. J. of Commun. Syst., vol. 16, no. 5, pp. 381-400, Jun. 2003.[R2] M. Zimmermann and K. Dostert, “A multipath model for the powerline channel,” IEEE Trans. Commun., vol. 50, no. 4,pp. 553-559, Apr 2002.
Bottom-Up Tight PHY connection Faithful but onerous
Top-Down Analytical fitting General but simple Suitable for statistical analysis
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Bottom-Up vs Top-Down
Two dual approaches to model the PLC channel Each has strengths and weaknesses
Synthetic Channel Model Description
Consider the CFR, amplitude and phase, in dB scale( ) = ( ) ( ) = + ( ) is normally distributed ( ) uniformly distributed in − ,
The normalized covariance matrix depend onℛ = ℛ + ℛ + ℛ , − ℛ , From dataℛ , ≈ 0.033 & Im ℛ ≈ 0.024, implying
• & uncorrelated (~independent)• ℛ assumed as real
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[REF] A. M. Tonello, A. Pittolo, and M. Girotto, “Power line communications: Understanding the channel for physical layerevolution based on filter bank modulation,” IEICE Trans. On Commun., vol. E97-B, no. 8, pp. 1494-1503, Aug 2014.
Experimental vs Simulated Channels
Comparison among Experimental measures Simulated channels
Note as exhibits High values almost everywhere Higher between nearer
Good correlation matching Variations limited to
• Sharp transitions• Low correlation values
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[REF] A. M. Tonello, A. Pittolo, and M. Girotto, “Power line communications: Understanding the channel for physical layerevolution based on filter bank modulation,” IEICE Trans. On Commun., vol. E97-B, no. 8, pp. 1494-1503, Aug 2014.
Conclusions
PLC represents a challenging environment A variety of detrimental channel effects Heterogeneity of possible scenarios Great deal of noise
It has been demonstrated through our measurement campaigns Differences exist But similar behavior and relations hold
SYNTHETIC channel modeling is appealing since it is Statistically representative Flexible parameters can be selected from environment Simple short run-time in simulation
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