doc.: ieee 802.15-09-0279-01-004g submission april 2009 tg4g - channel characterization project:...

doc.: IEEE 802.15-09-0279-01-004g

Submission

April 2009

TG4g - Channel Characterization

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Submission Title: Channel Characterization for SUNDate Submitted: 29 April, 2009Source: Multiple (see inserts)Group Coordination: Clint PowellContributions by: George Flammer, Emmanuel Monnerie, Steve Shearer, Shusaku Shimada

Re: IEEE 802.15 Task Group 4g Call for Proposals (CFP) on the 22 January 2009

Abstract: Summary and conclusion from the TG4g Channel Characterization subgroup

Purpose: A subgroup within TG4g has been created in an ad-hoc manner to discuss the SUN channel and to try to characterize it. A significant amount of data was exchanged and is summarized in this document. The conclusion and recommendations of the subgroup are also formulated for consideration by the TG4g proposers.

Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein.Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15.

Slide 1

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Geographical Data

Source: Emmanuel Monnerie Company Landis+GyrAddress 30000 Mill Creek Avenue, Alpharetta, GA 30022Voice: +1 678 258 1695 , FAX: , E-Mail: Emmanuel . Monnerie [at] landisgyr.com

Slide 2

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• The following data shows the different types of meter densities in typical large meter deployments in the USA.

• The charts are representing for each category of meter density :– The % of meters in each category (blue bars)– The area in square miles occupied by each category (green

bars)– The average minimum distance between meters for each

category (X-axis)

Slide 3

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Utility A - 2.6 million electric meters spread over 7000 sq miles

TG4g - Channel CharacterizationSlide 4

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Utility B - 1.4 million gas meters spread over 5000 sq miles


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Utility C - 350k electric meters spread over 400 sq miles


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Connectivity Data

Source: George Flammer Company Silver Spring NetworksAddressVoice: , FAX: , E-Mail:


Slide 7

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• The following data shows some examples of connectivity distributions for normally deployed meters in urban/suburban and rural areas.

Slide 8

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Suburban network


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Rural Network


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Link distance distribution


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April 2009


Channel Multipath Characterization


Data collected and processed in cooperation with Dr Yimin Zhang and Dr Xin Li (Villanova University)

Source: Steve Shearer Company SelfAddress 3655 Bernal Avenue Pleasanton CA 94566 USAVoice: +1 905 997-0576 , FAX: , E-Mail: shearer_inc [at] yahoo . com

Source: Shusaku Shimada Company Yokogawa Electric CorporationAddress 2-9-32 Nakacho-town Musashino-city Tokyo, 180-8750 JapanVoice: , FAX: , E-Mail: shusaku [at] ieee . org

Slide 12

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April 2009

Post-processingPost-processing

Test Setup

Oscilloscope4 channels

2GHz sampling rate

Oscilloscope4 channels

2GHz sampling rate

LNA

4 antennas

1st Low pass filter

1st Low pass filter

DecDec 2nd Low pass filter

2nd Low pass filter

Frequency offset

correction

Frequency offset

correction

DSSS Correlators

DSSS Correlators

Peak Detection and

rearrangement

Peak Detection and

rearrangement917 MHz917 MHz

DecDec

917MHz DSSSMeter module

1 PN sequence every 52us

3 feet high

20 feet high

* The oscilloscope recording is triggered by a hardware-based DSSS receiver

Trigger *


doc.: IEEE 802.15-09-0279-01-004g

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Test Location: Philadelphia, PA

FS: Fernon St S

1: 5482: 5423: 536

8: 5269: 52010:514

(508)

Special mention – Fernon St (Poles in North side)blocked by pole: FS 3air conditioner: FS5; FS10; FN2; FN3; FN4air conditioner in back: FN5

1: 5492: 5433: 537

8: 5279: 52110:515

(509)

MN: Mountain St N

1: 5492: 5473: 5414: 535

9: 52510: 519

MS: Mountain St S4: 520

9: 51010: 504

1: no add2: 5303: 526

Special mention – Mountain Stair conditioner: MN7, MN8

TS: Tasker St S

(508)

10:510

(546) 9:516

8:522

2:534

1:540

construction trucks in this area (TS8-10)

Special mention – Tasker St (Construction truckers in the East end)air conditioner: TS9air conditioner in back: TS3

TN: Tasker St N

11:602

12:612

18:624

19:630

20:636

11:603

20:63519:62718:621

12:609

(648)

11:602

12:608

13:614

18:624

19:630

20:636(643)

11:603

12:609

13:615

18:625`

19:631

20:637

(640) 11:604

12:608

13:612

18:622

19:628

20:634

TS: Tasker St S

FN: Fernon St N

FS: Fernon St S

MN: Mountain St N

MS: Mountain St S

Special mention – Tasker St Metal door on ground: TS14

Special mention – Fernon St UPS trucker near receiver: FS15

Special mention – Mountain St air conditioner: FS18air conditioner in back: FS19

Legend

Receiver antenna array

#: address Meter positions

Meter positions with invalid data

(address) End units (not measured)

Field Experiment

4/17/08 * 10:00 am – 3:00 pm

FS: Fernon St S

1: 5482: 5423: 536

8: 5269: 52010:514

(508)

Special mention – Fernon St (Poles in North side)blocked by pole: FS 3air conditioner: FS5; FS10; FN2; FN3; FN4air conditioner in back: FN5

1: 5492: 5433: 537

8: 5279: 52110:515

(509)

MN: Mountain St N

1: 5492: 5473: 5414: 535

9: 52510: 519

MS: Mountain St S4: 520

9: 51010: 504

1: no add2: 5303: 526

Special mention – Mountain Stair conditioner: MN7, MN8

TS: Tasker St S

(508)

10:510

(546) 9:516

8:522

2:534

1:540

construction trucks in this area (TS8-10)

Special mention – Tasker St (Construction truckers in the East end)air conditioner: TS9air conditioner in back: TS3

TN: Tasker St N

11:602

12:612

18:624

19:630

20:636

11:603

20:63519:62718:621

12:609

(648)

11:602

12:608

13:614

18:624

19:630

20:636(643)

11:603

12:609

13:615

18:625`

19:631

20:637

(640) 11:604

12:608

13:612

18:622

19:628

20:634

TS: Tasker St S

FN: Fernon St N

FS: Fernon St S

MN: Mountain St N

MS: Mountain St S

Special mention – Tasker St Metal door on ground: TS14

Special mention – Fernon St UPS trucker near receiver: FS15

Special mention – Mountain St air conditioner: FS18air conditioner in back: FS19

Legend

Receiver antenna array

#: address Meter positions

Meter positions with invalid data

(address) End units (not measured)

Field Experiment

4/17/08 * 10:00 am – 3:00 pm


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Ideal Output (location FS1)


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Location FS10, antenna #2


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Location MN9, antenna #3


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Location MN17, antenna #1


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Location MS6, antenna #1


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Location MS12, antenna #3


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Location TN19, antenna #3


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Location TS2, antenna #3


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Location TS7, antenna #1


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Measurement Characteristics

• Many channels measured have some degree of dispersion between 1 and 2us for these relatively short distances– Rapid fading appears to be absent on all but a few measurements

as expected

• It seems reasonable to model a channel characterizing this urban environment by a simple two path pseudo-static model – Each path gain is chosen from different Rayleigh distributions and

held constant for the time that the channel is used

• This method allows average performance to be evaluated for a population of receivers in an area, or for a receiver used in a frequency hopping scenario [*]

[*] Performance modeling for Smart Grid radios in Geographically Stationary and Frequency Hopping environments. Steve Shearer April 2009


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April 2009

Example Matlab Codefunction [y]=TN19channel(x)% This channel is designed to mimic the channel% whose impluse response was measured by Landis&Gyr% with certain simplifying assumptions%amp1=0; % Average amplitude of 1'st path in dBamp2=0; % Average amplitude of 2'nd path in dBn_FsDelay=1; % Delay is 1 sample. (1.6us at Fs=600kHz) RV1=(randn(1,1)+1i*randn(1,1))/sqrt(2)*10^(amp1/20);RV2=(randn(1,1)+1i*randn(1,1))/sqrt(2)*10^(amp2/20); % Create the output from scaled and delayed versions% of the inputy=(x*RV1 + [zeros(1,n_FsDelay) x(1:(length(x)-n_FsDelay))]*RV2);

% Normalise the output according to the average amplitudes% of the two paths to ensure that long-term average=1y=y/sqrt(10^(amp1/20) + 10^(amp2/20));


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Results from reference [2]

“The results of multipath power delay profile measurements of 900-MHz mobile radio channels in Washington, DC, Greenbelt, MD, Oakland, CA, and San Francisco, CA, are presented. The measurements have focused on acquiring worst case profiles for typical operating locations. The data reveal that at over 98% of the measured locations, rms delay spreads are less than 12 us. Urban areas typically have rms delay spreads on the order of 2-3 us and continuous multipath power out to excess delays of 5 us. In hilly residential areas and in open areas within a city, root mean square (rms) delay spreads are slightly larger, typically having values of 5-7 us. In very rare instances, reflections from city skylines and mountains can cause rms delay spreads in excess of 20 us. The worst case profiles show resolvable diffuse multipath components at excess delays of 100 us and amplitudes 18 dB below that of the first arriving signal.”


doc.: IEEE 802.15-09-0279-01-004g

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Conclusion regarding the multipath analysis

• Signal delay spread in urban environment can reach 1us to 2us, even in line of sight and short distance conditions (100 to 150 meters).

• A 2-path Rayleigh model is applicable in many cases.• Fast time fading due to moving objects appears to have a

minimal impact.• Measurements are compatible with results published in

reference #2.• Considering these test results and the results publish in

reference [2], it is clear that, while many links will have no multipath, another significant percentage of the links will have multipath with a delay spread between 1us and 5us.


doc.: IEEE 802.15-09-0279-01-004g

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April 2009

References

1. Localization of orphan utility meters based on spatio-temporal signature information (Zhang, Y.; Li, X.; Monnerie, E.; Pritchard G.; Salazar Cardozo, R.). Sensor Array and Multichannel Signal Processing Workshop, 2008. SAM 2008. 5th IEEE

2. 900 MHz multipath propagation measurements for US digital cellular radiotelephone (Rappaport, T.S.; Seidel, S.Y.; Singh, R.). Global Telecommunications Conference, 1989, and Exhibition. Communications Technology for the 1990s and Beyond. GLOBECOM’89., IEEE


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Group Conclusion and Recommendations

• The data analyzed shows a broad range of deployment conditions ranging from low density areas with less than 10 meters per sq mile, to high density areas with more than 2500 meters per sq mile (and some up to 6600 meters per sq mile).

• While the area covered by meters in low density zones can be significant (sometimes > 60%), the corresponding proportion of meters in this areas can be less than 10%.

• The vast majority of meters are deployed in areas with more than 1000 meters per sq mile. The average minimum distance between meters ranges from 50 to 200 feet (15m to 60m).

• The meters in this area are well connected with a typical neighbor count of around 30.

• Regarding Multipath Mitigation, the subgroup recommends that the TG4g proposers state the following:

– For proposed PHY in widespread deployment, state how SUN multipath has been mitigated,

– Otherwise, state planned SUN multipath mitigation techniques.TG4g - Channel CharacterizationSlide 29

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April 2009

Does a SUN Channel have multipath?•

Channel Models taken from ETSI ETSI EN 300 392-2 V3.2.1 (2007-09)

Propagation Model Tap Number

Relative delay (us)

Average relative

power (dB)Rural Area (Rax) 1 0 0Typical Urban (Tux) 1 0 0 2 5 -22.3Bad Urban (Bux) 1 0 0 2 5 -3Hilly Terrain (HTx) 1 0 0 2 15 -8.6

doc.: ieee 802.15-09-0279-01-004g submission april 2009 tg4g - channel characterization project:...

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