atoll measurement calibration

8/13/2019 Atoll Measurement Calibration

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ATOLL MEASUREMENT MODULE


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Training Programme

1. SPM Calibration Concepts

. u e nes or easurement urveys

3. Working with CW Measurements

4. Automatic Calibration Method

5. Analysing the Calibrated Model

6. Calibration Process Summary

Forsk 2010 Slide 2 of 54Confidential Do not share without prior permission


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Goal

equ rements

Quality target



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Goal

SPM

Macrocell statistical propagation model

Based on empirical formulas + set of parameters

Propagation depends on

Frequency

Area type (urban, suburban, rural, etc.)

Geography (relief, vegetation, climate, etc.)

Calibration is essential to accurately estimate

Coverage predictions

Interferences



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Requirements (1)

Accurate and recent geo data

DTM and clutter resolution


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Requirements (2)

Drive Test data

Possible but not recommended

Conversion to CW measurements is needed

Downside

Real network is measured interferences

Directional antennas: accuracy of pattern, only a few points are relevant

Several frequencies are measured

Low sampling rate for each measured station (lee criterion cant be met)

Signal measured over a short distance from the transmitter (model will not be calibrated forinterference evaluation)

It is not recommended to use Drive Test data to calibrate a model



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Quality Target

Calibration sites

Global mean error on calibration sites < 1 dB

Global standard deviation on calibration sites < 8 dB

Mean error on each calibration site < 2.5 dB

Standard deviation on each calibration site < 8.5 dB

Verification sites

Global mean error on verification sites < 2 dB

Global standard deviation on verification sites < 8.5 dB



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Training Programme









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2. Guidelines for CW Measurement Surveys

Site Preselection criteria

urvey route cr ter a

Radio criteria



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Site Preselection Criteria

Surrounding

Very representative of area type

Major clutter classes equally represented

No major obstruction within a radius of 150 to 200m from the CW sites

Low diffraction within a 10km radius (rural zones)

Enough roads all around the site

nspec on on s e

Possibility to rig omnidirectional antenna (no obstacle on any side)

Panoramic photographs

Report site details: precise height, coordinates



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Survey Route Criteria

Distance

Up to noise floor of the receiver

Equal number of samples near and far in all directions

Clutter

Routes through major clutter classes

Avoid forests and lakes between transmitter and receiver

Maps

Supply vector maps of survey routes to import in Atoll

Check that survey routes match roads (vector data or scanned maps)



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Radio Criteria (1)

Frequency

3 contiguous unused channels for GSM

1 unused carrier for UMTS

Only one channel must be measured

Interferences must be checked before each drive

Equipment data

ntenna patterns + ownt t + az mut not per ect y omn rect ona

Antenna height + transmit power + transmission gain and losses

Receiver height + sensitivity + reception gain and losses



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Radio Criteria (2)

Signal measurement

Lee criterion: at least 36 samples over 40(for f 900 MHz)

Maximum vehicle speed depends on equipments sampling rate

Sampling Rateat 900 MHz

(samples per second)

Sampling Rateat 2100 MHz

(samples per second)

Max. Speed (km/h)

45 100 60

68 150 90

90 200 120

113 250 150

Measurements after averaging

At least 5000 points per site

Typical number: between 10000 and 20000 points



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Training Programme









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Creating a CW measurement path

B co in astin X Y measurement

By importing any ASCII format file

Standard import as in excel

Option of importing any additionalinformation related to CW measurementpoints

configurations



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3. Working With CW Measurements

CW Measurements: Table

List of all measurement points with their attributes and additional information

Standard content management and tools (filters, copy-paste, etc...)

Coordinatesof points

SignalMeasured

values

Altitude, Clutterclasses and

heights,Distance, etc.read from the

Geo data



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CW Measurements: Properties

The points can bedisplayed according to any

data contained in themeasurement Table

For predictions along the CW measurementpath, you can either use Existing path lossmatrices or recalculate them by choosing a

specific Propagation model



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CW Measurements: Calculations and Statistics

To calculate the predictedsignal level of the reference

an any o er op ona y

added) transmitter along theconsidered path.

Note: This can also be run

from top folders.

To compare statisticsbetween measured and

predicted signal levels.

Note: This can also be

run from top folders.



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CW Measurements: Filter (at the Folder level)

Distance, Measurements

Advanced filter on additional survey data Clutter Classes filtering



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CW Measurements: Filtering Assistant and Filtering Zones

Tool to filter the datapath in an more

advanced way than inthe Filter dialogue

available at the folder

level (previous slide)

Tool to exclude some points from the measurement

path according to a drawn polygon (all points within

the polygon will be filtered out)



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CW Measurements: Smoothing BEFORE

AFTER

Create a sliding window to smooth

the measured signal strength

Smoothing can be used to limit fading effect

Smoothing keeps the number of measurement pointsunchanged

Smoothing cannot be used to average gross CWmeasurements



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CW Measurements: Synchronise the Table, the Mapand the CW Measurements Tool

Synchronisation:

- Map

- Table

- CW Measurements Tool

Analysis of aspecific CW

measurement

path

Predicted signal level

Display of any attributerelated to a given path



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Training Programme









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CW measurements pre-processing

Initial model

Calibration wizard

Final model



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CW Measurements Pre-processing

Correspondence between Measurements and Geo data

Projection checking

Check that CW measurements match roads

Routes checking

Check that CW measurements respect planned survey routes

Surrounding checking

Check with panoramic photographs that there is no obstacle

Option of setting an angle filter to avoid attenuation due to obstacles



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Filtering

Available at the Folder level for each site

Will be applied to all the measurement paths in that folder

Distance, Measurementsvalues and Azimuth filtering

Will permanently removethe points outside the filter

Advanced filter on additional survey data



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Distance filtering (Min Distance / Max Distance)

Typical min value: 200 m (not representative of mean propagation)

Typical max value: 10 km (rural area)

Signal filtering (Min Measurement / Max Measurement)

Filtering out the measurements above the receiver overload: typical value -40 dBm

Filtering out the measurements below the receiver sensitivity + target standard deviationtypical value: -120 + 8 = -112 dBm

In order to avoid noise saturation effect in statistical results

Azimuth filtering

To remove points in a certain angle

Filtering assistant

In addition to the Filter located at the Folder level, you can define more precise filteringdepending on the CW measurement file



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Filtering assistant (1/2)

Display of M = f ( 10log(D) )

Selection rectangle simultaneous Signal/Distance filtering Possibility to keepthe selected points

Signal/Distance

filtering

according to the

selectionrectangle

SelectionAzimuth

filtering on the

or to exclude them

ec ang e

measurement

points



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CW M t P i


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Final filtering (1/2)

Display each CW measurement according to their Measured signal level

Check that propagation loss is spatially homogeneous


CW M t P i


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Final filtering (1/2)

Removing which points?

Sudden drop of signal level

How?

Delete from the CW measurement table

Draw Filtering zones


Calibration / Verification Stations


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Calibration / Verification Stations

Display measurement routes after pre-processing

Calibration stations

a ons so a measuremen s cover e w o e area

Avoid keeping stations with a lot of common points

Verification stations

Stations so that measurements are inside covered area (not at edges)

Major part of their covered areas are also covered by calibration stations

How many

If 8 measured stations 6 for calibration; 2 for verification

If < 8 measured stations all stations used for calibration verification performed with same stations


Initial Model


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Initial Model

General SPM formula

( ) ( ) ( ) ( )( ) ( ) ( ) LOShill,clutterRxeff7Rxeff6

Txeff54Txeff321model

Kclutter.fKH.logKHK

Hlogd.logKLossnDiffractioKH.logKd.logKKL++++

++++=

.

..

Let K6 = 0

Others will be calibrated

Effective antenna height

Choose method according to terrain reliefModify height from transmitter properties

Can be selected by the calibration process

Recommendation if terrain is hilly

Enhanced slope at receiver method

Hilly terrain correction 1-YES

Recommendation if terrain is flat

Height above average profile methodHilly terrain correction 0-NO


Initial Model


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Initial Model

Max distance

Forced to 0 during calibration

If >0 no continuity ensured

Kclutter= 1 is recommended

Multiplying factor of clutter losses

Minimum loss= Free space loss

Avoid unrealistic values

Profiles

Radial optimisation quicker


Initial Model


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Initial Model

Heights of Clutter taken or not into account inDiffraction

Then put 1-YES in the box

If you only have a Clutter classes File

2 approaches:

If Clutter Classes file has a very fine resolution You can put 1-YES and the tool will take into

account the average heights defined in your clutterclasses file

you should keep all the losses per clutter class to Zero

If Clutter Classes file resolution is low

Do not take into account the average heights definedin your clutter classes file (0-NO), but instead add aLoss per Clutter class type

Receiver on top of clutter

By default NoOnly useful for fixed receivers


Initial Model


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Initial Model

Clutter Classes Losses can be calibrated

You need to define the max distance from the Receiver (towards the Transmitter) for whichthe different clutter classes will be considered

Choice between 4 t es of Wei htin functions Uniform Trian ular Lo arithmic

Exponential)

( ) =

=

n

iiiwLclutterf

1

wi=f(d'i) Uniform

Triangular

Logarithmic

Exponential

d'i

wi


Initial Model


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Initial Model

Reference model

Create a Reference model containing all the previous settings

,

When duplicated, choose an appropriate name and pay specific attention to:

Methods used for Diffraction and Effective Antenna Height calculation

value of Kclutter

Hilly terrain correction

Heights of Clutter considered or not in Diffraction Clutter Range and associated Weighting function

Start from the Reference model for each calibration trial


Calibration Wizard


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Calibration Wizard

Automatic calibration overview

Algorithm based on solving a least-squares problem

Calculation of the best solution in terms of root mean square : M22RMS +=

,

First Step

Selection of calibration stations


Calibration Wizard


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Calibration Wizard

Second step (1/2)

Selection of the Parameters to calibrate

Possibility to modify their ranges


Calibration Wizard


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Calibration Wizard

Second step (2/2)

Recommended ranges

Constant Min Max

K1 0 100

K2 20 70

K3 -20 20

K4 0 1

K5 -10 0

K7 -1

It is recommended to leave K6 to 0


Calibration Wizard


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Calibration Wizard

Final step

Display of Before and After Parameters values and Statistics

Commit will update the model you are calibrating with the new values of Ki, height anddiffraction methods as well as the Clutter Losses


Final Model


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Extrapolate non-calibrated clutter losses (1/2)

Non-calibrated clutter classes must not have their clutter losses left to 0

Could lead to high error where these classes are present

Must be extrapolated from:

Calibrated clutter losses (from other propagation model)

Typical losses (here centred on the Urban class)

Clutter class Typical lossDense Urban from 4 to 5

Woodland from 2 to 3

Suburban from -5 to -3

Industrial from -5 to -3

Open in urban from -6 to -4

Open from -12 to -10

Water from -14 to -12


Final Model


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Extrapolate non-calibrated clutter losses (2/2)

Centre clutter losses

Relative difference between clutters kept unchanged

Example:

Apply scaling factor

After calibration, model centred on suburban:K1=17.4 Losses: Dense Urban = 6.5

Wood = 5.7Urban = 3.5Suburban = 0

After centring, new values:K1=20.9 Losses: Dense Urban = 3

Wood = 2.2Urban = 0Suburban = -3.5

apt typ ca osses or ca rate ones com ng rom ot er mo e to t e ca rate mo e

Typical Losses

MyModel Losses

Urban

0

0calibrated

4.5

3calibrated

Dense UrbanOpen

-12

-8Extrapolated

C

e

n

t

r

e

d

Define Scaling Factor


Training Programme


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g g








5. Analysing The Calibrated Model


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y g

Statistics (1/2)

Apply the new calibrated propagation model to your CW sites




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Statistics (2/2)

Check the Quality Targets (Std Deviation and Mean Error values) on the Calibration andVerification sites

Statistics available Globall

per Clutter class, per Transmitter andper Measurement path

Possibility to run theStatistics on all the

Measurement paths,

or on specific ones




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Correlation (to be checked on the Calibration sites)

Through the Assisted Calibration Wizard

Displays, for each parameters to be calibrated (K1, K2, K3, etc.), the correlation of thevariables lo D lo Heff Diff etc. with the lobal Error

Check if the Correlation values are between -0,1 and +0,1

Commit will apply the Correction values to the corresponding Ki valuesNotes: This will not take into account the Ki Ranges

The calibration wizard will

attempt to bring thecorrelation as close to zero

as possible. The results will

be a correction value that will

be added or subtracted to the

initial Ki value in the model




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Display Error

Recalculate the Predicted signal values (P) according to the calibrated propagation model

Display the Error (P M) between the CW Measurements values (M) and the Predictedvalues P




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Display CW Measurements & associated Signal Level study

Use the same shading on both displays to be able to compare them

For each site, one by one Check the global behaviour of calibrated model




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CW measurement and Profile windows

Analysis along the path


Training Programme


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Calibration Process Summary


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Before starting...

Check Geographical Database quality & accuracy (DTM, clutter, vectors...)

Define environments (hilly, flat / urban, rural...) to specify the required number of propagationmodels to be calibrated

Measurements preparation

Sites selection

Survey roads

Fulfil radio criteria

Make & Average measurements

Create Transmitters used for measurements in the Atoll document

With exact configuration (coordinates, antenna type & height, EIRP, losses)

Analyse & Filter measurements ( Pre-processing)

Keep representative points and remove suspicious ones

Choice of calibration / verification sites


Calibration Process Summary


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Run the automatic calibration

Display statistics and compare results with target values (Std deviation and Mean

for calibration sites: Global and Individual checkingfor verification sites: Global checking

Extrapolate non-calibrated clutter losses

Analyse calibrated model

Display statistics

h k rr la i n

Maps displaying Error(P-M), Measurements & Signal Level Study, etc.

Apply the calibrated model

Apply resulting standard deviation per clutter in the clutter class description

Apply the calibrated model to networks transmitters (Transmitter Properties\Propagation tab)



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THANK YOU!

atoll measurement calibration

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