utf-8_wizard-adv (day one).ppt

March 2006

x-Wizard – Advanced Training

DAY ONE – RF Modeling and Drive Test Data

2

How Does it all Work?

Prediction Tuning

Create IM

Model

Optimize

AFP/ACP

Drive Test

Switch

Channels

Traffic

Exp

ort

AFP/ACP Results

3

Class Agenda

• RSL Predictions – – A general description of how Macro cellular Propagation

Models work

• x-Wizard Predictions – – A description of how x-Wizard has implemented several

propagation models

• Drive Testing – – A discussion on how to collect and import drive test data

for x-Wizard

4

Class Agenda - RSL Predictions

• General Description of RSL Predictions– Basic Propagation Modeling– Accounting for Terrain

Effective Antenna Height Knife Edge Diffraction

– Accounting for Clutter General Concept of Clutter Local vs Pass-Through adjustments

5


• This section of the class is offered . . .– To define basic parts of ANY macrocell Propagation

Model– To illustrate how the predictions account for terrain– To illustrate how the predictions account for clutter

Details of specific models are offered after a general treatment of the material

6





7

RSL Predictions in x-Wizard

Predicted received signal level is composed of three basic parts:– Propagation model prediction (RSLPM)– Terrain Factors

Diffraction loss prediction (DL)

OR Effective Antenna Height (EAH)

– Clutter Adjustments (CA)

CA

EAH

or

DL

RSLRSL PMbin

CA

EAH

or

DL

RSLRSL PMbin

8

Basic Propagation Model

All Macrocell Models share:– The assumption that power decays as Log (Dist) – RSL will form a straight line plot (RSL vs Log (Dist))

The Straight Line Assumption

RSL = N*Log(Dist) + P

log(R/R0)

RSLdBm

n.10.log(R/R0)

P1-mile+10.log(Pt/100)+...

0 1 10

X-Wizard Modelcontrols

9


There are a couple more factors added:– The prediction depends on the ERP and Tx/Rx height– Some models have explicit frequency dependency

A Basic Propagation Model

)()(*

)(*)(*

FH

HLogQ

P

PLogMDLogNPRSL

ref

act

ref

actoPM

)()(*

)(*)(*

FH

HLogQ

P

PLogMDLogNPRSL

ref

act

ref

actoPM

Straight Line Assumption

ERP

Tx/Rx Height

Frequency

10


The Propagation Model (RSLPM) only accounts for:– Distance– ERP– Tx/Rx Height– Frequency

But does not account for terrain obstructions

Predictions withEAH turned off,KED set to zero &No Clutter

Note: no shadowing behind a hill

11

Class Agenda - Optimization




12

Accounting for Terrain

The Terrain Effects are calculated as either:– Effective Antenna Height (EAH) Correction

Applies only when there is Line of Sight (LOS) between the Tx & Rx

OR– Knife Edge Diffraction (KED) Correction

Applies only when there is an obstruction in the Fresnel zone or Line of Sight is blocked

Both EAH and KED are independent of the propagation model (i.e. Lee, Hata, COST231)

13

Accounting for Terrain - EAH

• Effective Antenna Height (EAH) Gain/Loss

– It is caused by the reflected waves near the receiver– Reflections are often the result of the local slope

Part of any propagation parameter file in x-Wizard

b

bemEAH h

hEG log

b

bemEAH h

hEG log

Basic Effective Antenna Gain

= Effective antenna height gain (dB),= Effective antenna height multiplier (dB),= Effective antenna height (m or ft),= Physical antenna height (m or ft).

GEAH

Em

hbe

hb

hbe is calculated based on the EAH model you choose (next slide)

14

The Effective Antenna Height (hbe) is the critical factor when calculating EAH correction!

• x-Wizard offers three different ways to calculate EAH– Slope (Shown Below)– Spot or Absolute Spot (Next Slide)

Effective Antenna Height(Gain)

Effect of downward Local Slope Effect of upward Local Slope

BS

MS BS MS

Effective Antenna Height(Loss)

Accounting for Terrain - EAH

15

Effective Antenna Height Spot

• The Spot Method recommended by the (ITU-R). TX

RXhTX-AMSL - hRX-AMSL

hTX-AMSL

hRX-AMSL

hTX-AGL

Sea Level

Line of sight

hTXeff = Effective transmitter antenna height [ft/m]hTX-AGL =Transmitter antenna height above ground level [ft/m]hTX-AMSL =Transmitter antenna height above main sea level [ft/m]hRX-AMSL =Receiver antenna height above main sea level [ft/m]

Absolute Spot MethodEffective antenna height is not limited to hTX-AGL as the mobile height (hRX-AMSL) goes above the base height (H0b).

16

Accounting for Terrain - KED

The affects of Knife Edge Diffraction (KED)– KED is used whenever there is a terrain obstruction

Note: Shadowing behind the obstruction

17

Modeling Knife Edge Diffraction Real obstruction is replaced with a knife edge Replacement allows for an analytical solution for the diffraction

loss

Four different diffraction modelsin x-Wizard:

Picquenard Deygout Epstein-Peterson Japanese Atlas

1d 2d

h

Knife Edge

ActualObstruction


18

DL Model Comparison

• Always searches for the main obstacle first!– Final set of obstacles

more realistic

• Prioritizing obstacles closer to the transmitter (BTS)– ‘Minimum slope’ obstacle

detection– Tends to omit fairly large

obstacles closer to the receiver

O1 O2 O3

TX RX

O4

"LOS"

1st 2nd

3rd

O1 O2 O3

TX RX

O4

"LOS"

1st 2nd

3rdPicquenardPicquenard

O1 O2 O3

TX RX

O4

"LOS"

PrimaryObstacle

1st2nd3rd

O1 O2 O3

TX RX

O4

"LOS"

PrimaryObstacle

1st2nd3rd Deygout Deygout

19

Epstein-Petersen

• Diffraction Models - Epstein-Petersen– Epstein-Petersen is better for wide separate obstacles– Loss is calculated first at each edge then overall loss is calculated by

summing all three losses caused by the three obstacle edges.– d1, d2, d3, and d4 are distances between edge obstacles– h1, h2, and h3 are respectively the effective heights of edge1, edge2,

and edge3 which are determined by drawing line-of-sight between relevant edge obstacles.

20

Japanese-Atlas– Japanese Atlas is improved for closer obstacles with no dominant

obstruction– Similar to the Epstein-Peterson method – Exception: in calculating loss due to each obstruction the effective source is

not the top of the preceding obstruction, but the projection of the horizon ray through that point onto the plane of the transmitter.

A

B

C

TX

RX

Plane of Transmitter

d1 d2 d3 d4

T’

h’

21


– Studies Show that KED models are conservative Loss calculated using theoretical KED model is greater than

reality Regardless of the KED model chosen, a correction factor will

‘add-back’ to the signal

– X-Wizard offers two KED Corrections:

Foose Factor – Applies an additive correction per obstruction Polynomial - More robust multiplicative model

CORRRAWTOT KEDKEDKED CORRRAWTOT KEDKEDKED

22

KED Correction … Foose Factor

• Large Foose Factor– KED correction applied for

obstructed cases Should range 0dB < FF < 6dB

– Optimization may lead to FF of very high values (FF > 6dB) High FF results in signal

amplification when FF > DL Signal re-birth effect

• Throw out optimized values of FF >10 dB

• Be careful if 6 < FF < 10 dB

FFnDLCORR FFnDLCORR

][

,

dBfactorFooseFF

nsobstructioofNumbern

Ripple Effect!

Signal Re-birth

23

KED Correction … Polynomial

• Polynomial KED correction

– Range 0 ≤ A ≤ 1 -10dB ≤ B ≤ 10dB

• Advantages– 2 levels of freedom (multiply A, additive B)

More accurate optimization results

– More robust, yet not completely foolproof Large A,B values may lead to unreasonable prediction

BDLADL RAWTOT BDLADL RAWTOT ][

],[

dBfactorAdditiveB

unitlessfactortiveMultiplicaA

24

Class Agenda - Optimization




25

Accounting for Clutter

• Recall that RSL is calculated as:where CA = clutter adjustment

Clutter defines areas that contain non-terrain obstructions – trees, buildings, etc.

26


Clutter consists of 2 files:• Clutter ID file

– Morphological classification of the propagation environment

Typically 7 to 12 classes

• Clutter adjustment file– Defines losses that signal incurs

while propagating through/over each clutter type

27


• Pass Over– Used for Water only– x-Wizard will attenuate signal as a signal passes over large bodies of

water if Pass Over is checked

• Clutter Height– Defines how high the clutter type is above the terrain– Required if you intent to model pass-through effect

• Receive Height– Used to model bridges and elevated roadways– Defines how high the Rx is above the ground

28


RX

TX

d3d4

d2

ClutterType 1

ClutterType 3

ClutterType 5

ClutterType 2

ClutterType 4

Clutter attenuates the signal as it passes through and arrives at theLocal Bin.x-Wizard models both types of attenuations:

• Local Adjustment – dB loss due to clutter in the bin being predicted

• Pass Through Adjustment – dB loss due to clutter on the way to bin being predicted

Pass-Through Local

Bin being Predicted

29

Class Agenda – x-Wizard Predictions

• Propagation Predictions in x-Wizard– Propagation Predictions

Prediction Hierarchy Propagation Mode

– Old Standard

– New Standard/ Old Turbo

– New Turbo/ Old Radial

– Specific RF propagation models Lee Model Hata-Okamura Model

30

Class Agenda - x-Wizard Predictions

• This section of the class is offered . . .– To explain x-Wizard prediction hierarchy and prediction

modes– To explain the Lee Model (as implemented in x-Wizard)– To explain the Hata-Okamura Model (as implemented in

x-Wizard)

31

Class Agenda – x-Wizard Predictions



– Old Standard



– Specific RF propagation models Lee Model Hata-Okamura Model Modified Lee Microcell

32

Prediction HierarchyPropMod:

Isotropic Path Loss Predictions

SngServ:Antenna Pattern

Predictions

MLCover:Combo of SngServ

Maps most likely server

InterferencePermissions

MatrixOthers

The number of activesites changes

Antenna, Azimuth,Downtilt changes

Will be re-run if:ERP, Tx Ht., Lat/Lonchanges

33




– Old Standard



– Specific RF propagation models Lee Model Hata-Okamura Model Modified Lee Microcell

34

Propagation Mode: General

• PropMod is the single most time-consuming step in any prediction (coverage, interference, permat, etc.)– Few dependencies means we can re-use PropMods– By re-using PropMods, x-Wizard reduces the time for subsequent

analysis runs

• PropMod requires terrain profiles which take a long time to draw– Reduce the number of profiles and you speed up PropMod

35

Propagation Mode: Old Standard

• Profiles are calculated to each bin when using the old Standard Mode– Similar to TV cathode tube beam

scanning

• This mode draws the largest number of radials; therefore the slowest– # of Radials ~ N2 (N is # of ext. bins)– At 100 m terrain and 30 mi Calc Dist

N = 483 bins & # of Rad. = 233,290 radials

– At 30 m terrain and 30 mi Calc Dist N = 1,610 bins & # of Rad. = 2.592 M radials

Tx

c c c c c

c c c c c

c c c c c

c c c c c

ccc c

36

Propagation Mode: New Standard

• Old Turbo Mode is now called ‘Standard’• Profiles are calculated to each exterior bin

when using the new Standard Mode– Profiles are re-used for interior bins– Each bin is calculated using a terrain profile

• Reduces the # of radials (30% to 50% faster than Old Std.)– # of Radials ~ 2 (N+N) (N is # of ext. bins)– At 100 m terrain and 30 mi Calc Dist

N = 483 bins & # of Rad. = 1,932 radials

– At 30 m terrain and 30 mi Calc Dist N = 1,610 bins & # of Rad. = 6,440 radials

Tx

c c c c c

c c c

cc

c c c c c

c

c

c

c

c

cc c c

37

Propagation Mode: New Turbo

The new Turbo Mode (a.k.a. Radial Turbo) allows the User to set the number of radials (i.e. control speed of predictions)

1. This is the most common method in industry (xWizard, Planet, CellPlan, etc)

2. Predictions close to a sector use terrain profiles

3. Predictions farther from the site are interpolated from predictions on either side.

4. Provides a balance between speed and accuracy

interpolation

prediction

38


The new Turbo Mode uses the following equation to interpolate between profiles.

RSLBI = RSLB1 + (RSLB1 - RSLB2) * D1-I / D1-2

Where:

D1-I = Straight line distance from B1 to BI

D1-2 = Straight line distance from B1 to B2

39

The number of interpolated bins is a function of the number of radials and terrain bin size.

30 m terrain - # of bins between radials

90 m terrain - # of bins between radials

5km 10km 15km 20km 25km 30km 35km 40km 45km# of radials # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins

360 2 5 8 11 14 17 20 23 26720 1 2 4 5 7 8 10 11 13

1440 0 1 2 2 3 4 5 5 62880 0 0 1 1 1 2 2 2 35760 0 0 0 0 0 1 1 1 1

11520 0 0 0 0 0 0 0 0 0


5km 10km 15km 20km 25km 30km 35km 40km 45km# of radials # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins # of Bins

360 1 2 3 4 5 6 7 8 9720 0 1 1 2 2 3 3 4 4

1440 0 0 1 1 1 1 2 2 22880 0 0 0 0 1 1 1 1 15760 0 0 0 0 0 0 0 0 111520 0 0 0 0 0 0 0 0 0

40

Propagation Mode: ‘Accuracy’

You can say nothing about the accuracy of an un-optimized model, regardless of which mode you choose.

X-Wizard allows you to optimize the model in ANY propagation mode.

Studies have shown that the optimized models have the same accuracy regardless of which mode you choose.

41

Accuracy Comparison Testing

Test Conditions• Terrain and clutter

at 30 meter resolution.

• Drive test data out to 8000 meters. (Drive data doesn’t often get measured much farther from the site.)

Accuracy Parameters New Standard Mode (1064 radials)

360 Radials

Mean Error 0.1 dB 0.26 dB

Standard Deviation 7.6 dB 7.4 dB

42




– Old Standard




43

Lee Model: General

– One of the most popular macroscopic models in the US– Developed by W.C.Y. Lee in eighties as a result of

extensive propagation studies performed in northeast US Considered a US suburban-type model

– Developed for propagation in 800-900MHz frequency band Lee has been validated at 1900 band Lee has no explicit frequency dependence

44

Lee Model: Parts of Model

= Received signal level (dBm),= Reference distance Intercept (dBm),= Output power at the antenna (ERP in W),= Propagation loss factor (n*10 = SLOPE),= Distance between Tx and Rx (miles),= Reference distance (1-mile),= Tx height correction multiplier (dB),= Effective height of the base station antenna (ft),= Actual height of the mobile antenna (ft),= Tx antenna gain relative to the maximal gain (dB).

RSLPM-Lee

P1-mile

Pt

nRR0

Tmhbe

hm

Gt

Straight Line AssumptionERP Tx/Rx Height

tmbe

Mt

mile Gft

h

ft

hT

miR

Rn

W

PP

10

log10150

log][

log10100

log10RSL0

1Lee-PM tmbe

Mt

mile Gft

h

ft

hT

miR

Rn

W

PP

10

log10150

log][

log10100

log10RSL0

1Lee-PM

45

Lee Model: Optimized Parameters

Slope and Intercept Always Optimized

Effective TX Height Can be Optimized

Always Optimized Diffraction Model

46

Lee Model

The Lee Model does not have an explicit frequency dependency, BUT

Note that the Slope is independent of frequency between 150 MHz and roughly 2.2 GHz

Intercept depends on frequency; can convert from one frequency to another using:

2

11121 log20)()(

f

ffPfP milemile

2

11121 log20)()(

f

ffPfP milemile

47




– Old Standard


– Turbo Radial


48

Hata-Okumura Model: General

• Okumura Model– Developed as a summary of large-scale studies in and

around Tokyo during the 1960’s– Designed to work from 200 to 1920 MHz in mostly urban

propagation environment– Presented in forms of path loss curves

• Hata Model– Developed by fitting empirical equations to Okumura

curves– Hata is the most often used version of the Okumura’s

model

49

Original Okumura Model - Equation

• Path loss between TX and RX is given as:

rutumuFS HHALL 50

Where

50L Median path loss in dB

FSL Free space path loss

muA Basic median attenuation

tuH Transmitter antenna height correction

ruH Receiver antenna height correction

Free space loss is given by

]MHz[log20log20log10log10 fdGGXL rtFS

X is 32.45dB if the distance is expressed in km, and X is 36.58dB if the distance is expressed in miles

50

Basic Median Attenuation

• The change of the environmental attenuation due to the change in operating frequency and TX / RX separation

• Given for reference TX height and RX height

• Reference:RX height = 3m TX height = 200m

51

TX Height Correction

• Used to compensate for different TX heights

• Reference TX height is 200m

• The transmitter height used is the effective TX height calculated as Height Above Average Terrain

52

RX Height Correction

• Used to compensate for different heights of the mobile antenna

• Reference mobile antenna height is 3 meters

53

Height Above Average Terrain HAAT

• Calculate the average terrain between 3 and 10 km from the site

• Subtract the height of the average terrain from absolute height of the radiation centerline

Radiation CenterLine

Effective Antenna Height

3 km 15 km

Height of theAverage Terrain

distance0

54

Okumura Model - More Details

• Due to its simplicity Okumura model is widely used• Some Concerns:

– The curves must be implemented in forms of lookup tables for computer-based models

– Empirical nature of model limits its applicability to nonstandard environments

– There are some ambiguities associated with calculation of effective antenna height when the radius of cell is smaller than 3km or when the height of the TX antenna is lower than average terrain. The Effective Antenna Height (EAH) should be modeled as Spot or Absolute Spot

• The above concerns have led to numerous modifications to the model in its practical implementation- Hata, COST-231, Walfish…etc.

55

Hata-Okamura: Parts of Model

= Received signal level (dBm),= Output power at the antenna (ERP in W),= Constant loss factor (default = 69.55dB),= Log-frequency multiplier (default = 26.60dB),= Tx height multiplier (default = 13.83dB),= (Mobile) Antenna height correction (dB),= Slope (default = 44.90),= Effective antenna height multiplier (default = 6.55)= Distance between Tx and Rx (miles),= Reference distance (0.62mile),= Area correction factor (dB),= Effective height of the base station antenna (ft),= Reference base station antenna height (3.28ft)= Actual height of the mobile antenna (ft),= Tx antenna gain relative to the maximal gain (dB).

RSLPM-HO

Pt

CL

LM

TM (hm)SEm RR0

Aa

hbe

h0

hm

Gt

tabe

mmbe

McMLt GAR

R

h

hEShα

h

hTfLCP

000HO-PM loglogloglogRSL ta

bemm

beMcMLt GA

R

R

h

hEShα

h

hTfLCP

000HO-PM loglogloglogRSL

Intercept

Freq.

Tx/Rx HeightStraight Line Assumption

Slope

56

Hata-Okamura: Optimized Parameters

Always OptimizedDiffraction Model

Always OptimizedEffective Antenna Height MultiplierArea Correction

57

• (Mobile) Antenna height correction is computed as:

• Medium and Small size city

• Large city

• Change using Calculate . . .

• Dependent on City Size

8.0log56.17.0log1.1 fhfh mm

MHz200 1.154.1log29.8 2 fhh mm

MHz400 97.475.11log2.3 2 fhh mm

Hata-Okumura Corrections

58

• Area correction factor is computed as:• Dense urban areas

• Urban areas

• Suburban areas

• Open areas

• Change using Calculate . . .

• Dependent on Area Type

Hata-Okumura Corrections

dB28

log24.52

fAa

dB94.40log33.18log78.4 2 ffAa

dB3aA

dB0aA

59




– Old Standard


– Turbo Radial

– Specific RF propagation models Lee Model Hata Model

60

Class Agenda – Drive Testing

• Drive Test Procedures– Test Site Selection– Drive Route Selection

• Measured Data Integration– Importing drive test data– Associating measured data– Filtering measured data

61


• This section of the class is offered . . .– To explain how best to pick sites for collecting drive test

data

– To explain some considerations when planning drive routes

– To demonstrate how to import drive test data and then associate it with the site that was driven

– To demonstrate different methods of filtering bad data out of a file once it is in x-Wizard

62




63

Drive Testing – Site Selection

• Divide network into areas that are similar – Typically, the common feature is Morphology

Rural, Suburban, Urban

– Terrain may be used to further sub-divide Morphologies Flat Rural and Hilly Rural Flat Suburban and Hilly Suburban

– Vegetation may also be used to sub-divide Morphologies ‘Treed’ Suburban and ‘Open’ Suburban

The Key: Identify sites that cover only one Area Type

64

• Pick sites that represent an area & do not have mixed coverage

Good Suburban Sitemix of residential, treesand commercial areasthat is consistent over the Coverage area

Bad Suburban Sitesmall pocket of residentialmostly rural in Sectors1 & 3; Mixed Coverage


65

• Do not pick sites that are special cases– Both examples are limited by water

Sector 3 may be possible; some limits tothe northSectors 1 & 2 cover too much water; youcan not get enough drive test data

This site covers a barrier island; very fewroads to drive plus you will skew resultswith data on causeway over water


66


• Site configuration and parameters used in x-Wizard MUST AGREE with the site configuration in the field

ERP Antenna type, orientation, and

downtilt Latitude/longitude, radiation

centerline (height)

– This is of extreme importance…it can invalidate the whole study!!

67




68

Local Area Mean(LAM)

Geographical Bin

Drive Route

0 10 20 30 40-82.5

-82

-81.5

-81

-80.5

-80

-79.5

-79

-78.5

-78

Distance in w avelengths

Inst

anta

neo

us

RS

L [

dB

m]

DiscreteMeasurements

Prop. model calculates RSL over small geographical areas called bins

Drive test equipment should average 50 samples every 40 into a LM

After import, the LMs inside a bin are averaged to obtain a LAM

Local Mean (LM)

Drive Testing – Route Selection

69

fc

hhhhd rtrt

c

44

f

c

hhhhd rtrt

c

44

• Drive routes should concentrate on data past ~200 m from site:

RF propagates in a predictable manner

Sets min. dist. for collecting data

• Inside ~200 m, propagation experiences Rayleigh fading

• Min dist. depends on: Frequency Transmitter height Receiver height Local clutter

10-2

10-1

100-100

-80

-60

-40

-20

0

20

distance [km]R

SL [

dB

m] Slope of 20

dB/dec

Slope of 40 dB/dec

Check distance dc


70

• Noise floor Minimum signal level that a receiver can filter out from the

noise Determines MAXIMUM DISTANCE to drive from the test site

– Ways to determine noise floor: Calculation

Equipment manufacturer specifications Measurements

F(kTB) 10log10NF F(kTB) 10log10NF

k=Boltzman’s constant 1.38·10-23 J/KT = environmental temperature, KB = collection bandwidth, HzF = equipment noise figure, dB

Test signal

Noise floor


71

• You need at least 300 data points per TX to perform a statistically valid optimization– This typically requires data out to 3 or 4 miles from site

• Collect data along radial routes and crossing routes– Radials capture Rn relationship– Crossing routes capture general effects of clutter shadowing

• Collect data near and far from the site

• Watch for interfering signals – Should drive only clear channels since co-channel introduction will change the tuned slope


72

Good Example• Good Density provides

>300 data points• Nice mix of radial routes• And crossing routes• Data extends from 200m

to ~4 miles

Good routes


73

Bad Example• Not enough data

– Most data is within 2 mile of site

• Not much ‘crossing’ data– Most data is along Hwy 30

Not enough data


74




75

• File > Import > Measured Data ...

Supported Data TypesAgilent SD5 (Nitro)Berkley Varitronics CHAMPCharacter Delimited ASCIICOMARCODTI ScannerGeneric Measured Data ASCII Grayson CellScopeGrayson PageTrackerGrayson SpectrumTrackerLCC Cellumate and RSATLCC DeskCatMLJ PathViewSAFCO OIFZK Celtest ZK SAM

Drive Testing – Importing Data

76

• File > Import > Measured Data ...

Give same ‘Source Datum’ as project or the drive test data will not match roads in the project.

Select more than one file for import and you have the option to combine all the files into one *.WMD file


*.WMD format preserves each drive test point.Routine aggregates points whendata is displayed.

77

Notes on Format• Samples of all supported formats can be found in the Help >

Index . . . drop down menu– Search for “Generic ASCII”; Display “Preparing Measured Data for

Import” Topic


78

Data Types requiring *.frq table

Berkley Varitronics CHAMPGrayson PageTrackerGrayson SpectrumTracker

Generic Measured Data ASCII

Notes on Format• Some formats require a frequency table that

maps frequency to channel number– Edit “pagetrc.frq” to add frequencies– File is found in the Common directory


79




80

x-Wizard allows you to assign data files to the site(s) that were driven. This enables:– Batch Mode Model Optimization– Clutter Optimization– Quick display of drive data– Aggregation of multiple drive test files when running

optimizations– Good “book-keeping”

Keeps track of what sites have been driven

Drive Testing – Association

81

You can Associate Measured Data:– From the menu, Tools > Associate Measured Data– From the WEX, rt. mouse click the sector you want to

associate data.

Then it is a Four Step Process


82

• Associating Measured data is a step-by-step process

Step One – select the transmitter to which data will be associatedStep Two – select the data file that will be associated

– Note: data must already be imported to x-Wizard– The routine is looking for the *.wmd files found in Project’s

MEASURED directoryStep Three – select the channel to associate (if more than one)


83

Step Four: Filter the Data


Filter based on distance• Set the distance manually• Use ‘Get’ button to have distance

calculated based on the signal threshold

• ‘Draw Boundary’ will display the maximalBoundary for data that will be includedat the site

Use ‘Associate More’ to cycle backto Step 1 and associate data at another site

84

Once data is associated . . .– A new entity displays in the WEX

Measured Data icon is placed under the transmitter

– Right Mouse menu allows you to display the data quickly


85




86

• Bad data can be filtered within x-Wizard using one of three methods:

Model or Clutter Optimization Analysis Dialog

Associated Measured Data Process

Filter Measured Data Utility

Drive Testing – Filtering Data

87

• The Propagation Model and Clutter Optimization dialog allows you to filter data based on:

Distance – set a min/max distance for comparison Accuracy – exclude points where Delta > 30 dB Signal Level – exclude points below a certain

threshold Angle – exclude points based on azimuth, antenna

beamwidth


88

• Some Precautions:– Start with 0.25 mi for min distance; increase if data is bad– Reduce max distance if data strays into a different morphology or

there is interference from a different site– Do not use data from behind a sectorized antenna; use horizontal

beamwidth

• The Propagation Model and Clutter Optimization dialog is useful because:– It can accommodate most situations– It does not delete data points


89

• Associate Measured Data

The last step filters by Max. distance and RSL Optimizations that use Associated Data only have Min.

distance settings in the dialog


90

• Tools > Filter Measured Data This tool allows you to DELETE data from drive test

files– You must re-import the data file to recover the original points


91

• Tools > Filter Measured Data

– Measured Data files are listed along the left pane

– The operation can delete points or modify selected points Add, Subtract, Divide, Multiply or

assign a constant value


92


– Filter on defined coordinates

– Filter on a drawn object– Filter on a range of RSL

– Filter by distance

Note: These changes are permanent!! To recover original data, you must re-import data.


93


– In order to delete data using a drawn object, you must have a pre-existing object prior to entering the dialog.

– All objects are used so be careful! Don’t forget other objects

that may be off screen


Questions???

utf-8_wizard-adv (day one).ppt

Documents

propagation modelsdrive

macrocell propagation

eah model

predictions account

log dist rsl

blockedboth eah

xwizard advanced trainingday

txrx heightsome models