EXPLAIN M06 - 1 Coverage Predictions

1 © NOKIA 6-90202/ COVERAGE PREDICTIONS/ v 1.0

Coverage Coverage Predictions Predictions


Module objectives

DESCRIBE DIFFERENT PREDICTION MODELS

DESCRIBE PREDICTION MODEL TUNING TOPICS

CALCULATE CELL RANGE

At the end of this module you will be able to …


Content of Coverage Predictions

PROPAGATION MODELS

MODEL TUNING


Coverage Predictions

PROPAGATION MODELS

MODEL TUNING


Propagation ModelsUsed in Nokia tools

• Okumura-Hata• The most commonly used statistical model

• Walfish-Ikegami• Statistical model especially for urban environments

• Juul-Nyholm• Same kind of a prediction tool as Hata, but with

different equation for predictions beyond radio horizon (~20km)

• Ray-tracing• Deterministic prediction tool for

microcellular environments

Statistical ⇒to be tuned!

Deterministic


additional attenuation dueto land usage classes

• Adapted for 900 MHz and 1800 MHz

• Different land usage classes

f frequency in MHzh BS antenna height [m]a(hm) function of MS antenna heightd distance between BS and MS [km]

A = 69.55 B = 26.16 (for 150 .. 1000 MHz) A = 46.3 B = 33.9 (for 1500 ..2000MHz)

L A B f h a hh d L

b m

b morpho

= + − −+ − +

log . log ( )( . . log ) log

138244 9 655

Propagation ModelsOkumura-Hata


• Urban• Small cells, 40..50 dB/dec attenuation

• Forest• Heavy absorption; 30..40 dB/dec; differs with season (foliage losses)

• Open, farmlands• Easy, smooth propagation conditions

• Water• Signal propagates very easily ⇒ interference !

• Mountain faces• Strong reflections, long echos

• Etc…• Many morpho types have been defined

Propagation ModelsOkumura-Hata


• Model for urban microcellular propagation

• Assumes regular city layout (“Manhattan grid”)

• Total path loss consists of two parts:

h

w

b

d

NLOS • roof-to-street diffraction and scatter loss • mobile environment losses

LOS • line-of-sight loss

Propagation ModelsWalfish-Ikegami


• Line-of-sight path (LOS)• Use free space propagation• Applicable for microwave & satellite links

• “Non-line-of-sight” path (NLOS)• Heavy diffraction, refraction situations• Many models exist in literature, none is satisfying• Great uncertainties in modeling• Needs detailed building databases (vectorial information)• Use ray-tracing models?

“Manhattan grid”model

Propagation ModelsWalfish-Ikegami


• Deterministic model for microcellular environments• Launch rays into every direction of space• Certain number of rays calculated• Reflections calculated based on dielectric coefficients• Very high computational load

• Mirror image method also possible

εr

“single point”signal source

Propagation ModelsRay Tracing


Coverage Predictions

PROPAGATION MODELS

MODEL TUNING


Model TuningBasics

• It’s aimed to get a more realistic propagation model

• It should be done at the very beginning of a planning project, before any dimensioning activity

• How?• Select typical sites for measurements• Define measurement routes• Tune propagation model to make its predictions match the measurements data


Model TuningMeasurements

• What antenna height should be used?• Typical for the area?

• Model restrictions?

• Okumura-Hata stay above 24 m!

• Keep away from existing antennas

• Mark LOS situations, tunnels, bridges etc.• Take these out of the measurement file

• A power budget is needed. Note down:• TX power, cable and connector losses

• Antenna type, height, direction, tilt

• Site coordinates


• Measure only interference free frequencies

• Measure only in the main lobe of the transmitting antenna

• Avoid or erase line-of-sight measurement points

• Use differential GPS if possible or match the coordinates with the map

• Check coordinate conversion parameters

• Measure all the cable losses (both in transmitting and receiving end)

• Measure the output power of the transmitter

• Check transmitter antenna installation and ensure that there are no obstacles nearby

• Document the measurements very carefully

Model TuningMeasurements


Model TuningOkumura-Hata Measurements

• Measured field strength should be between – 95 dBm and – 60 dBm• Stay in the main coverage area of the selected cell• Not too close to cell edges• Not too close to TX antenna

• Route long enough • Minimum 100 samples are needed

• O-H does not predict LOS situations• Avoid routes with LOS situations

• Make sure all wanted morpho classes and topo types are included

• Which coordinate system?


Model TuningOkumura-Hata Model Tuning

• Import measurement results to a planning tool

• min. distance > 500 m to filter out too close samples

• Tune morpho corrections to best fit

• Tune only factors, which have more than 3%

• Mean value +/- 1 dB

• If a lot of LOS ⇒ negative mean

• Standard deviation ± 8 dB

• Correction factor for urban ~ 0 dB


Model TuningMeasurements ≠ Predictions?

• Why are the predictions and measurements different?• Is the digital map accurate enough?• What is the resolution of the map? • Is the morpho data correct?• Does the measured route match the roads?• Do the measured routes have a lot of LOS situations?


Site and cell data Digital map System information

Calculate measurement route

Map matching

Measurement data

Coordinates

Model tuning

Compare

Analysis

Satisfactory model

End

Field strenght

No

Yes

Model TuningDetailed Process


Prediction model tuning areas

• Propagation slope• Effective antenna height• Morphographic corrections• Calculation distance



Assessment of propagation slope

• Okumura-Hata correction factor C:

dhChDfBA bb 10101010 log)log55.6(loglogL −+−+=


propagation slope,parameter C has to be changedas a function of antenna height andenvironment


Effective antenna height definition

• 0 – 3 km: the average terrain height is calculated from base station to mobile station. The effective antenna height is the difference between the absolute antenna height and the average terrain height.

• 3 – 6 km: the average terrain height is calculated as a sliding average over 3 km from the mobile station towards to the base station.

• 6 – 15 km: the average terrain height is calculated from 3 km (from base station) to the mobile station.

• over 15 km: effective antenna height is the difference between the transmitting antenna and the average terrain height between 3 and 15 km



30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1

Terrain type U U U O O U U U O O O O S S S S P P P P W W W W W S S S S S

Correction factor [dB] 0 0 0 -15 -15 0 0 0 -15 -15 -15 -15 -5 -5 -5 -5 -8 -8 -8 -8 -23 -23 -23 -23 -23 -5 -5 -5 -5 -5

Pixel size: 50 m x 50 m

Morphographic corrections

Example: Morphographic corrections

• The distance between the base station and the mobile station is 1.5 km. On the digital map there are 30 pixels (50 m x 50 m) between the base station and the mobile. Each pixel presents the terrain type within the 50 m x 50 m area.

The following notations are used:U = Urban, S = Suburban, P = Park, O = Open and W = Water.



Morphographic corrections

• The morphographic correction calculated as an average of the pixels between the mobile station and base station

• The average of the correction factors in this example is –9.4 dB

• The basic propagation model is corrected by adding the calculated correction to the prediction result (correction factor Lmorpho in Okumura-Hata model).



Calculation distance

• It is not very likely that the area close to the base station has a great impact on the received power of the mobile station

• The areas close to the mobile are more important for the prediction thus there are ways to weight the areas close to the mobile station

• The calculation distance can be shorter than the distance between the mobile station and the base station

• Only the pixels close to the mobile stations are considered

• In the previous example the calculation distance is changed from 1.5 km down to 500 meters the average of the correction factors is –14 dB. Difference between the corrections is 4.6 dB.




1.01.0

1.02.0

10 9 8 7 6 5 4 3 2 1

Terrain type W W W W W S S S S S

Correction factor [dB] -23 -23 -23 -23 -23 -5 -5 -5 -5 -5

Weights 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

Normalized weights 0.67 0.73 0.80 0.87 0.93 1.00 1.07 1.13 1.20 1.27

Normalized correction factors -15 -17 -18 -20 -21 -5 -5.3 -5.7 -6 -6.3


Linear weights for terrain type correction factors (example). The average of the normalized correction factors is –12.33 dB.



-100

-90

-80

-70

-60

-50

-40

1 51 101 151 201 251 301 351 401 451 501

Measurement points

Sign

al le

vel [

dBm

]

MeasuredPredicted

0

10

20

30

40

50

60

70

80

90

-15 -14 -13 -12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19

dB

Example: Morpho Corrections Tuning


-100

-90

-80

-70

-60

-50

-40

100 1000 10000

Distance [m]

Sign

al le

vel [

dBm

]

Example: Quality of Tuning


Morpho Class Value [dB]

Open -20

W ater -25

Forest -11

Quasi-Open -5

Houses -12

Sub-Urban -10

Urban -2

Buildings 7

Industrial buildings -4

High rise buildings 18

Example: Tuning Results


Exercises / Questions

List different predictions models!

List major tasks in OH - prediction model tuning!

Calculate the coverage for a 900 MHz cell when antenna height is 30 and 50 m. Compare these results to the case of antenna height 30 m and 3 dB improvement in the power budget. Which one is better? (Excel/NetAct Exercise)

Calculate a cell coverage area at 900 and 1800 MHz by using constant power budget? What is the difference? (Excel/NetAct exercise)


References

1. W.C.Y. Lee, “Mobile Communications Design Fundamentals,” John Wiley & Sons, 1993.

2. W.C.Y. Lee, “Mobile Cellular Telecommunication Systems,” McGraw-Hill Book Company, 1990.

3. W.C. Jakes, Jr., (ed.), “Microwave Mobile Communications,” Wiley-Interscience, 1974.

4. J. Lempiäinen, M. Manninen, ”Radio Interface System Planningfor GSM/GPRS/UMTS,” Kluwer Academic Publishers 2001.

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EXPLAIN M06 - 1 Coverage Predictions

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