CW Test and
Propagation Model Tuning
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Oct 2011
Introduction
CW test (Continuous Wave test) is
an important step of Propagation
Model Tuning. According to the CW
test data (including latitude /
longitude and received signal level)
and corresponding Digital maps, we
can get the accurate Propagation
Model through tuning.
Objectives
Know principle of propagation model
tuning
Know the procedure of CW test
Know the procedure of tuning propagation model
Contents
1 Principle of Model Tuning
2 CW Test Flow
3 Pre-processing of CW Test Data
4 Propagation Model Tuning
Radio Propagation Model

Propagation model is used to predict the effect of
terrain, obstacle and artificial environment on the
path loss.
WCDMA common propagation models
Common Radio Propagation Models
Based on Statistics
Based on theory analyses
 Okumura/Hata model
 Ray Tracing model
 For: 900M－1500MHz
 COST231-Hata model
 For: 1500-2000MHz
 COST231 Walfish-Ikegami model
 For: 800M-2000MHz
Keenan-Motley model
 For indoor propagation
 SPM model in U-Net
 For macro cell on 300M－2000M
 Volcano model
 WaveSight model
 WinProp model
Radio Propagation Model in Atoll
 SPM model (Standard Propagation Model):
PathLoss = K1 + K2log(d) + K3log(HTxeff) + K4*Diffraction loss +
K5log(d)×log(HTxeff) + K6*(HRxeff) + Kclutter*f(clutter)
K1: constant (dB)
K2: multiplier factor of log(d)
d: distance between Tx antenna and Rx antenna (m)
K3: multiplier factor of log(HTxeff)
HTxeff: effective height of Tx antenna (m)
K4: multiplier factor of diffraction loss, which must be a positive number
Diffraction loss: diffraction loss through the path with barriers (dB)
K5: multiplier factor of log(HTxeff)log(d)
K6: multiplier factor of HRxeff
HRxeff: effective height of Rx antenna (m)
Kclutter: multiplier factor of for f(clutter)
f(clutter): average weighted loss caused by clutter
With a set of K parameter, we can make prediction for the planning area.
Typical Radio Propagation Environment
Name
DenseUrban
Urban
Sub-Urban
Description
Therearedensebuildingsinthecity,normallymostofthe
buildingsaremorethan10floorshigh.
Normalareaincities.Buildingsarenotsodense.Normally
therearestreetsorplantingareasbetweenthem.Andfew
buildingsaremorethan10floorshigh.
Buildingsaresparselydistributed,andmainlylowbuildings.
Country
Village.Buildingsaredistributedverysparsely,andmainly
houses.
Special
Includingmountainarea,seasurface,highway,indoor,
tunnel,etc.
Different radio scenario adopts different propagation model.
Principle of Propagation Model Tuning
Target Propagation
Environment
Setup a Model
Collect data
from field test
Set the model
Parameter
Actual PathLoss
Prediction PathLoss
Compare
Meet the precision request?
Y
End
N
Propagation Model Tuning working flow
1. Decide the propagation environment
2. Acquire site, setup the simulation site,
transmitting continuous wave (CW)
signal
3. Drive test on the pre-planned route,
collecting enough data
4. Post process the data, compare test
results with prediction results, and then
tune the propagation parameters (K1,
K2, …Kclutter)
GPS Satellite
Basic Principle of CW Test
 Typification
 The CW test data must represent the characteristic of
electromagnetic wave in this area.
 Balance
 The CW test data must represent the characteristic of
electromagnetic wave by the proportion of different clutters in
this area.
Contents
1 Principle of Model Tuning
2 CW Test Flow
3 Pre-processing of CW Test Data
4 Propagation Model Tuning
Contents
2 CW Test Flow
2.1 Decide the Propagation
Environment
2.2 Site Selection
2.3 Setup Test Platform
2.4 Plan the Drive Test Route
2.5 Drive Test
2.1 Decide the Propagation Environment
 Firstly, decide if it’s necessary to separate the planning area to
several propagation environments, such as Dense Urban,
Urban, Sub-Urban or Rural Area, etc.
 Then for each environment, set proper initial propagation model
parameter, and perform dedicate CW test and propagation
model tuning.
2.2 Site Selection – Principles

Number of sites: It is usually agreed that a minimum of 5 sites should be
tested in large and dense city, and one site is enough for normal city, which
mainly depends on antenna height and EIRP.

Representation: Site selection should aim to cover all types of clutter
(from the digital map) in the coverage zone.

Multiple models: Define the corresponding zone of each model if the test
environment requires multiple models to describe its propagation
characteristics.

Overlap: Increase measurement overlap area between each site as much
as possible. But reasonable inter-site distance should be ensured.

Obstacle: The data should be filtered in the subsequent processing if
obvious obstacle exists.
2.2 Site Selection – Standards
1. Antenna height of the CW transmitter should be greater than 20m.
2. Antenna of the CW transmitter should be at least 5m higher than the
obstacle objects nearby within 50m far.
5m
Note: Here the obstacle mainly refers to the highest building on the
rooftop where the antenna is installed. The building where the site is
located should be higher than average height of surrounding buildings.
2.3 Setup Test Platform (1)
 CW Transmitter: Tx antenna, feeder, RF signal source and
antenna pole
 CW Receiver: test receiver, GPS receiver, test software and laptop
Tx antenna
RF
Signal
Source RF cable 1
CW Transmitter
Power
Booster
Power
supply
RF cable 2
Rx antenna
Drive test
tool
(GPS Build-in)
CW Receiver
Laptop
2.3 Setup Test Platform (2)
TX
Antenna
CW
Transmitter
CW
Receiver
Mobility
Power
Supplier
2.3 Setup Test Platform (3)
 Record the gain or loss of all the RF parts:
a) TX power of the CW transmitter
b) Loss of the RF cables
c) Gain of TX antenna
d) Loss of the connectors
e) Gain of Rx antenna
Then with a, b, c and d, we can get the EIRP.
2.4 Plan the Drive Test route (1)
 Rules to plan the route
 Landform: The route must cover all main landforms in the area.
 Height: The test route must cover landforms with different height in
this area if the landforms are up-and-down.
 Distance: The route must cover near and far to the site. But
normally no need to test in areas more than 2R far away to the site.
– R: Future cell radius in this area.
 Direction: The route must be consistent on the horizontal and
vertical route.
 Length: The total distance of one CW test route should be longer
than 60km.
 Number of test samples: The more, the better. (At least 10,000
samples, and at least 4 hours test time)
2.4 Plan the Drive Test route (2)
 Rules to plan the route
 Overlap: Overlap the test route in different sites as much as
possible to enhance the reliability of models.
 Obstacle: Shadow areas behind walls should be avoided when
antenna signals are obstructed by the wall.
Such areas as under viaducts or in tunnels should be avoided. If
have to pass through such areas, data should be filtered after test.
 If a directional antenna is adopted for a CW transmitter, the test
route should be planned within the main lobe coverage area of the
antenna (don’t plan route in area behind the antenna).
2.5 CW Drive Test – Limitation of the speed
 CW drive test data contains results affected by slow fading
(shadow fading) and fast fading (Raileigh Fading).
 To tune a model, only the effect by slow fading will be accept,
but not fast fading.
 To get rid of the effect caused by fast fading, enough samples
are need in a certain distance.
 Lee criteria says the request for sampling:
 At least 50 samples on 40λ range, then the difference between
mean value of test data and actual value can be less than 1dB
– λ: wavelength of the RF signal
 Then the maximum vehicle speed: Vmax= 0.8λ*f
– f: samples per second of the receiver
2.5 CW Drive Test - Equipment
 Scanner – DTI (GPS build in）
 GPS antenna
 RF antenna of scanner
 Cables for data and power
 Laptop
 Probe and Dongle
Contents
1 Principle of Model Tuning
2 CW Test Flow
3 Pre-processing of CW Test Data
4 Propagation Model Tuning
Contents
3 Pre-processing of CW Test Data
2.1 Data Filtering
3.2 Data Dispersion
3.3 Data Binning
3.4 Format Conversion
3.1 Data Filtering
 Six kinds of data should be filtered:
1. Data tested in places where GPS is unable to
locate accurately (such as under the viaduct,
in the tunnel)
2. Data obtained when the distance to antenna
is too near or too far
3. Data obtained with too weak signals
4. Error data caused by inexact antenna pattern
5. Data with a loss exceed over 15~30 dB but
no reasonable reason
6. Other data inconsistent with the requirements
during the route planning of CW test
3.2 Data Dispersion (1)
 Principle:
 Sampling speed of the receiver is much more higher than that of the
GPS. So there are many receiver samples stored together on each
GPS sample. Actually these receiver samples should be distributed
one by one in time sequence between every two GPS samples.
 Between two GPS sample, vehicle speed is regarded uniform, so the
time intervals between every two adjacent receiver samples are same.
3.2 Data Dispersion (2)
 Data Process:
 Equally distribute the receiver samples to the route section between
two GPS points in time sequence so that there will be sufficient
points in every 40λ range on test route.
3.3 Data Binning (1)
 Objective:
 Keep the impact of slow fading but eliminate the fast fading
 According to Lee criteria: At least 50 samples on 40λ range, then
the error between the mean value of the data on this 40λ range
and the actual value can be less than 1dB.
 Methods:
 Method 1 (Grid Binning): Divide the whole area into 40λ*40λ
grids, take the average value for data located in each grid, and
take the center of each grid as the new location.
3.3 Data Binning (2)
 Methods:
 Method 1 (Grid Binning): Divide the whole area into 40λ*40λ grids,
take the average value for data located in each grid, and take the
center of each grid as the new location.
 Method 2 (Distance Binning): Divide the drive test route into
sections with 40λ length, take the average value for data located
on each section, and take the center of each section as the new
location.
40λ
 Tool: TEMS Investigation, or CW Data Editor
3.4 Format Conversion
 The data exported by TEMS is a .txt file with format:
X (Longitude)
Y (Latitude)
Power (dBm)
 Data imported to Atoll is a .dat file
 Format conversion can be implemented manually (save as .dat
file)
Contents
1 Principle of Model Tuning
2 CW Test Flow
3 Pre-processing of CW Test Data
4 Propagation Model Tuning
Contents
4 Propagation Model Tuning
4.1 Basic Knowledge
4.2 Model Tuning by U-Net
Procedure of Model Tuning
CW data
SPM
Model
Set Model
Parameter
Perform Appropriate
Filtering
SPM Calibration
YES
NO
Is Filtering
Necessary
Analysis Results
NO
Goto Next
Parameter
Error
Satisfactorily
Low?
YES
Original Data is
Unreasonable.
Need to retest.
All Parameters
finished
Calibration?
YES
End
NO
Criteria to evaluate the model (1)
 The main idea to evaluate the model is to compare the
predicted value to the actual test value for a certain area,
then get a statistics result of the errors.
 Suppose the error of sample
E(i)
[dB]
i is:
Ppredicted
P
measured


[dBm]
[dBm]
Criteria to evaluate the model (2)
Mean Deviation
RMS Deviation
Standard Deviation
Correlation
Coefficient
Corr.Coeff .
E
1 n Ei
dB n  i 1dB
ERMS  1 n E2i

dB n i1 dB
1
E 
dB n1
((P
(P
 Ei
E 

  i 1 dB dB 
2
n

measured
measured

(i)Pmeasured).(P Predecited(i)P predicted))

(i)Pmeasured) .(P Predecited(i)P predicted)2
2

Criteria to evaluate the model (3)
 A model is reasonable if the statistics of the error between the
predicted results and the actual results meet the following
requests:

Mean Deviation
2dB  E  2dB
Standard Deviation
 8dB
Correlation
Coefficient
Corr.Coeff .0.8
Contents
4 Propagation Model Tuning
4.1 Basic Knowledge
4.2 Model Tuning by U-Net
4.2.1 Establish a Project
4.2.2 Establish a Propagation Model
4.2.3 Create the Transmitter
4.2.4 Import the CW test data &
Digital Map correction
4.2.5 CW data Filtering
4.2.6 Implement the Tuning
4.2.7 Evaluate the Turned Model
Model Tuning Operation flow on Atoll
4.2.1 Establish a Project for Model Tuning
 Create a new project
 Select ―UMTS‖ in the dialog of ―Project type‖ selection
 Set the coordinate system
 Set the coordinate system according to the digital map.
―WGS84 UTM Zones‖ is widely used.
 Import digital map
 Import antenna pattern data
4.2.2 Establish a Model to be turned (1)
 Create a new SPM model by duplicate
 Create a new ―copy of standard propagation model‖ by
duplicating on a exist ―standard propagation model‖. Then
rename is if necessary.
 Set initial parameters for the new model
 General Parameter
 Common Parameter
– Select the effective antenna height.
– Select calculation method of diffraction loss
 Clutter Parameter
4.2.2 Establish a Model to be turned (2)
 Initial K parameters of SPM model in normal Urban city
Frequency(MHz)
450
900
935
1805
2110
K1
4.3
12.1
12.6
22
24.3
K2
44.9
K3
5.83
K4
0.5
K5
-6.55
K6
0
4.2.3 Create the CW Transmitter
Two way to create CW transmitter:
 By head file —— Suitable for batch importing the transmitters
 Head file is a text file with extension name .hd, it contains basic
information for a CW transmitter
e.g.：test.dat DATE test 741790 32 54 0 0 0 23.04499751 113.7509966 Survey 0
GPS 0 0 0 0 hard
 Be aware to import the antenna before the head file
 Be aware to import the CW data manually after the head file
 Manually create —— It is more flexible for single CW transmitter
 As normal U-Net project, one by one set the antenna, site and
transmitter, etc. Pay attention to the latitude and longitude, EIRP, all
the feeder loss and connecter loss.
4.2.4 Import the CW data
 Pre-process on the CW test data
 For model tuning, U-Net only need latitude, longitude ant the
corresponding measurement power. Combine all data for one transmitter
to one .txt file, then import to U-Net or by copy and paste
 Import the CW data
 Method 1: Right click on the “CW measurements‖ in “Explorer‖，then
select ―New‖, then paste the CW data into the sheet. (By this method
there should not any blank tail in each row, otherwise U-Net will give a fail
result.)
 Method 2: Similar to method 1, select ―Import‖ from the context menu,
then browse to the CW data file. By this method, we can import several
files simultaneously.
4.2.4 Digital Map correction
 Reason:
 GPS locating in CW test usually adopts WGS-84 and UTM projection.
However, some digital maps in some country (e.g. China) do not use
such projections. Correct digital maps if CW test data does not
correspond to them.
 Correction method:
 Correct four parameters on rectangular coordinates in a digital map to
realize the optimal match with the test data.
 The four rectangular coordinates parameters are stored in files
“index.txt‖
4.2.5 CW data Filtering (1)
 Data filtering:
 By distance:
– Recommended：delete data in range r<0.1r or r>2r ( typically r = 1500m)
 By signal strength:
– Recommended: delete data with Signal>-40dBm或Signal<-110dBm
 By Clutter:
– Recommended: delete clutters with number of samples less than 300
4.2.5 CW data Filtering (2)
Select ―Filtering Assistant...‖ on properties of the data.
4.2.5 CW data Filtering (3)
In the clutter list, the un-checked clutter will be deleted.
4.2.6 Implement Tuning (1.1)
U-Net 2.1 (Build 2050)：
Right click on the model, select ―Automatic Calibration‖
4.2.6 Implement Tuning (1.2)
U-Net 2.2.1（Build2613）：
Right click on the model, select ―Calibration…‖, then select
―Automatic Calibration‖
4.2.6 Implement Tuning (2)
Select the parameters to be tuned. Normally only tune K1 and K2
must be tuned.
4.2.6 Implement Tuning (result)
Check if the Standard Deviation less than 8dB
4.2.6 Implement Tuning (an example)
KParameter
Reference
K1
23.2
K2
44.90
K3
5.83
K4
0.5
K5
-6.55
K6
0
4.2.7 Evaluate the model (1)
Parameter
Minimal
Typical
Maximum
K2
20
44.9
70
K3
-20
5.83
20
K4
0
0.5
0.8
K5
-10
-6.55
0
K6
-1
0
0
Check if any K parameter exceed out of the scope.
4.2.7 Evaluate the model (2)
U-Net 2.1
Bulid 2050
Calculate
prediction with
the tuned model
• Compare the test results
to the prediction ones.
• Red is test value, blue
one is prediction value.
4.2.7 Evaluate the model (2)
U-Net
2.2.1 Bulid
2613
CW
CW
Calculate
prediction with
the tuned model
• Compare the test results
to the prediction ones.
• Red is test value, blue
one is prediction value.
4.2.7 Evaluate the model (3)
1. Create a link budget project by RND to estimate
the cell radius
2. Compare the result to radius in similar cities
3. If they are quite different, it means something is
wrong with the tuned model, we must find the
reason.
Summary
 Principle of model tuning
 Procedure of CW test
 Procedure of model tuning by Atoll
Thank You
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