02 mn1790 coverage planning ww fh

8/3/2019 02 MN1790 Coverage Planning WW FH

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Coverage Planning: ContentsCoverage Planning: Contents

Definition of Terms

Characteristics of Radio Wave Propagation

Radio Wave Propagation Models

Suitable prediction models for Macro-, Micro- and Pico-cells

Location Probability

Link Budgets

Fading

Fast Fading

Rice Fading

Rayleigh Fading

Slow Fading Jake's Formula

Interference Margin

Noise Figure calculations

Amplifier Noise


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Coverage Planning: ContentsCoverage Planning: Contents

Path Loss Balance

Cell Coverage Calculation

Basics about Digital Map Data

Principles of Planning Tools and their usage

Measurement Tools supporting Cell Planning

Cell Types

Omni versus Sector Cells

Exercises


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Definition of TermsDefinition of Terms

To achieve coverage in an area, the received signal strength in UL and DL must be above the so

called receiver sensitivity level:

Coverage: RX_LEV > (actual) receiver sensitivity level

No Coverage: RX_LEV < (actual) receiver sensitivity level

The minimum receiver sensitivity levels in UL and DL are defined in GSM 05.05:

- for normal BTS : -104 dBm

- for GSM 900 micro BTS M1 : -97 dBm- for GSM 900 micro BTS M2 : -92 dBm- for GSM 900 micro BTS M3 : -87 dBm- for DCS 1800 micro BTS M1 : -102 dBm

- for DCS 1800 micro BTS M2 : -97 dBm

- for DCS 1800 micro BTS M3 : -92 dBm

- for GSM 900 small MS (class 4, 5): -102 dBm

- for other GSM 900 MS: -104 dBm

- for DCS 1800 class 1 or class 2 MS : -100 dBm- for DCS 1800 class 3 MS : -102 dBm


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Maximum output power for MS of different power classes:

+/- 2 dB29 dBm5

+/- 2 dB33 dBm4

+/- 2 dB36 dBm37 dBm3

+/- 2 dB24 dBm39 dBm2

+/- 2 dB30 dBm-1

ToleranceGSM 1800 MSGSM 900 MSPower Class


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Maximum output power (before combiner input) for normal BTS / TRX of different power classes:

2.5 (


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Maximum output power (per carrier, at antenna connector, after all stages of combining) for microBTS / TRX of different power classes:

>0.05 0.16 W>0.01 0.03 WM3

>0.16 0.5 W>0.03 0.08 WM2

>0.5 1.6 W>0.08 0.25 WM1

GSM 1800

micro-BTS

GSM 900

micro-BTS

TRX power class


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The reference sensitivity performance as defined in GSM 05.05 for the GSM 900 system fordifferent channel types and different propagation conditions:


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Characteristics of Radio Wave PropagationCharacteristics of Radio Wave Propagation

Physical Reasons

Diffraction

Reflection

Scattering

Absorption

Doppler shift

Technical Problems

Distance attenuation

(Path Loss)

Fading

Inter-symbol Interference

Ducting

Frequency shift /

broadening


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Characteristics of Radio Wave PropagationCharacteristics of Radio Wave Propagation

Exercise:

Which physical phenomena is sketched in the following pictures?


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Radio wave propagation:

The radio wave propagation is described by solutions of the Maxwell equations.

Exact solutions of the Maxwell equations are not accessible for real space environment with

obstacles which give rise to reflections and diffractions.

However, the full information provided by an exact solution (e.g. exact polarization and phase ofthe field strength) is mostly not needed.

What is needed is the the received power level.

What a propagation model should provide is the attenuation of the power level due to the fact thatthe signal propagates from the transmitter to the receiver.



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Empirical models and deterministic models:

Empirical models are based on measurements. Some empirical models (like the ITU model) arecurves derived from measurements. Others summarize the measurements in formulas (like theOkumura Hata model) which fit the measured data.

Such models are very simple to handle but also usually rather imprecise. They are limited toenvironments similar to the one where the measurements were performed.

Deterministic models are based on simplifying assumption for the general problem. This can be a

mathematical approximation of the original problem (like the finite difference model). Or it can be asimple model for a special situation of the general problem (like the knife edge model).

Deterministic model can reach a very high precision, but they suffer from a very high complexity.

Semi empirical models are a combination of empirical models with deterministic models forspecial situations (like knife edge models).



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Empirical models

Log distance path lossITUOkumura HataCOST Hata

Diffraction models

Epstein PetersonDeygoutGiovanelli

Semi empirical models

Okumura Hata & knife edgeCOST Hata & knife edgeCOST Walfisch Ikegami

Deterministic models

Ray launching, ray tracingFinite difference


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Received power:

PT: Transmitted powerPR: Reveived power

nTR dcPP =

)lg()lg()lg(lg dAdncLP

P

T

R =+==

101010Path loss:

d: distance


n

T

R dc

P

P =

0

0.2

0.4

0.6

0.8

1.0

2.5 5.0 7.5 10.0


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0 . 0 0 0 1

0 . 0 0 1

0 . 0 1

0 .1

1

1 2 5 1 0

n = 4n = 3n = 2

0

0 . 2

0 . 4

0 . 6

0 . 8

1 . 0

2 . 5 5 . 0 7 . 5 1 0 . 0

n = 4n = 3n = 2

Received power level

as function of distance don linear scale.

nR dP 1

Received power level

as function of distance don log scale.

nR

dP 1



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2

4

dP

R

Example: Free space propagation

?: wavelength in vacuum; , speed of light in vacuum

f: frequency in MHzd: distance in km

The influence of the surface is neglected completely

f

c=s

mc 81099792 = .

( ) ( )dfL lglg. 20204432 ++=


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Example: 2 ray model

d1

d2a

d2b

d

hBS

hMS

( )( )

( )( )

d

hhdd

d

hhdhhdd

ddd

d

hhdhhdd

MSBS

MSBS

MSBS

ba

MSBS

MSBS

2

2

2

12

2

22

2

222

2

22

1

=

++++=

+=

++=


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d

hhk

dd

e

d

eP MSBS

ikdikd

R

2

22

21

2

444

21

sin

( ) ( )

++=

d

hhkdfL MSBSsinlg.lglg. 2002620204432

( )dhhLMSBS

lg)lg()lg( 402020120 +=

dc

hhf

d

hhk

d

hhkhhkd

c

fk

MSBSMSBSMSBS

MSBS

2

2

=

>>

=

sinfor large

f: frequency in MHz

d: distance in km

hBS: height base station in m

hMS : height mobile station in m

The ground is assumed to be flat and perfectly reflecting.

The model is valid for hBS> 50mand din the range of km or for LOS microcell channelsin urban areas.


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80

100

120

140

1601 10 100

900MHz1800 MHz

path loss in dB

distance in km


hBS = 50m

hMS = 1.5m



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Log-distance path loss model:

n

R

d

dP

0

+=

0

100 d

dnLL

dlg

d0: reference distance ca. 1km for macro cells or in the range of 1m -100m for micro cells;

should be always in the far field of the antennaLd0: reference path loss; to be measured at the reference distance.

2-3Obstructed in factories

4-6Obstructed in building

1.6-1.8In building LOS

3-5Shadowed urban area

2.7-3.5Urban area

2Free space

Exponent nEnvironment


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Okumura Hata model:

Based on empirical data measured by Okumura in 60s Hata developed a formula withcorrection terms for different environments.

The Okumura Hata model assumes a quasi flat surface, i.e. obstacles like buildings are not

explicitly taken into account. Thus the Okumura Hata model is isotropic. The different types ofsurfaces (big cities, small cities, suburban and rural) are distinguished by different correctionfactors in this model.

Parameter range for this model:

Frequency f= 150 1500MHz

Height base station hBS

= 30 200m

Height Mobile station hMS= 1 10m

Distance d= 1 20km


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[ ]

[ ] [ ]

[ ]

=

++=

974751123

805617011

556944821316265569

2

.).lg(.

.)lg(..)lg(.

)(

)lg()lg(..)()lg(.)lg(..

MS

MS

MS

BSMSBSurban

h

fhf

hd

dhchdhfL

small cities

big cities (f>400MHz)


Okumura Hata model:

f: frequency in MHz

d: distance in km

hBS: height base station in m

hMS : height mobile station in m

( )[ ] 94403318784

4528

2

2

2

.)lg(.lg.

.lg

+=

+

=

ffc

fc suburban areas

rural areas


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+=

+=

00010

0020

223542126

.

.

)(

)lg(.)(.

MS

MSurban

hd

dchdL

small cities

big cities


Okumura Hata model:

For f= 900MHz, hBS= 30m, hMS= 1,5m the formula reads:

d: distance in km

5128

949

.

.

=

=

c

c suburban areas

rural areas


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COST Hata model:

The Okumura Hata model cannot be applied directly to systems like GSM 1800/1900 or DECT.Therefore it was extended to higher frequencies in the framework of the European researchcooperation COST (European Cooperation in the field of scientific and technical research).



Height base station hBS= 30 200m


Distance d= 1 20km

[ ]

[ ] [ ]805617011

5569448213933346

.)lg(..)lg(.)(

)lg()lg(..)()lg(.)lg(..

=

++=

fhfhd

dhchdhfL

MSMS

BSMSBSurban


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COST Hata model:

suburban areas

rural areas

city center

The major difference between the Okumura Hata model is a modified dependence onfrequency and additional correction factor for inner city areas

For f= 1800MHz, hBS= 30m, hMS= 1,5mthe correction term for the dependence on hMScan again be neglected. For the other terms of COST Hata model the insertion of the valuesserves:

)lg(.. dcLurban

+= 223524136

( )[ ] 94403318784

4528

2

3

2

2

.)lg(.lg.

.lg

+=

+

=

=

ffc

fc

c


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ConsultingBoth models, the Okumura Hata model and the COST Hata model can lead locally

to substantial deviation from the measured attenuation since these models are

isotropic. Local properties of the surface (big buildings, hills etc.) are not taken intoaccount.

9231

141

3

.

.

=

=

=

c

c

c

COST Hata model:

suburban areas

rural areas

city center



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ITU model:

The ITU (or CCIR) model was originally developed for radio broadcasting. It is based onmeasurements in the UHF and VHF range which are summarized in graphs

(ITU-R 370-7, ) for the field strength.The different topographic situations are described by the parameters hBSeff andh.

The ITU model describes the radio wave propagation for the rangesf= 30... 250 MHz and 450... 1000MHz

d=10... 1000km

Definition:hBSeff is the antenna height above the mean elevation of the terrain measured in a range from 3kmto 15 km along the propagation path.h is the mean irregularity of the terrain in the range from 10km to 50 km along the propagationpath, i.e. 90% of the terrain exceed the lower limit and 10% of the terrain exceed the upper limit of

the band defined by h.

The curves for the field strength are given for different hBSeff andh = 50m. The correction forother values ofh is given in an additional graph.Since local effects of the terrain are not taken into account the deviation between predicted and

actual median field strength may reach 20dB for rural areas. In urban areas this value may be wellexceeded.



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ITU model:


hBSeff

h

3km 10km 15km 50km

90%

10%

0km


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Correction to the ITU model: clearance angle method

An improvement of the ITU model is obtained by considering the maximum of the angle (clearance

angle) between the horizontal line and the elevations in the range of 0 to 16km along thepropagation path. The correction to the field strength ITU model (with h=50m ) is give as graphsfor the clearance angle. The clearance angle correction applies to both the receiving and thetransmitting side.


16km

MS, BS Position


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COST Walfisch Ikegami model:

For a better accuracy in urban areas building height and street width have to be taken intoaccount, at least as statistical parameters. Based on the Walfisch Bertoni propagation model for

BS antennas place above the roof tops, the empirical COST Walfisch Ikegami model is ageneralisation including BS antennas placed below the roof tops.



Height base station hBS= 4 50m


Distance d= 0.02 5km

Further parameter:

Mean building height: hin m

Mean street width: win m

Mean building spacing: bin m

Mean angle between propagation path and street: in


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b w

dBS

MS

hhBS

hMS



BS

MS


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With LOS between BS and MS (base station antenna below roof top level):


)lg()lg(. dfLLOS

2620642 ++=

With non LOS:

++

=,

,

0

0

L

LLL

L

msdrts

NLOS

0

0

+

>+

msdrts

msdrts

LL

LL

free space propagation:

rtsL roof top to street diffraction and scatter loss:

+

+

+++=

,..

,..

,.

)lg()lg()lg(.

114004

075052

354010

201010916MSrts

hhfwL

00

00

0

9055

5535

350


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msdL multiscreen diffraction loss:

)lg()lg()lg( bfkdkkLLfdamsdmsd

91

+++=

hhBS

>

( )

+

+

=

=

=

+

=

,.

,.

,

,

,.

)(.

),(.

,

,

),lg(

1925

704

1925

704

1518

18

508054

8054

54

0

1181

f

f

k

h

hhk

dhh

hhk

hhL

f

BSd

BS

BSa

BS

msd

hhBS

hhBS

>

hhBS

>

hhBS

hhBS

hhBS

50.>d

and

and

50.d

Medium sized cities and suburban centres

with moderate tree density

Metropolitan centres


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Although designed for BS antennas placed below the mean building height the COST WalfischIkegami model show often considerable inaccuracies.

This is especially true in cities with an irregular building pattern like in historical grown cities. Alsothe model was designed for cities on a flat ground. Thus for a hilly surface the model is notapplicable.


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Lee micro cell model:


This model is based on the assumption that the path loss is correlated with the total depth B ofthe building blocks along the propagation path. This results in an extra contribution to the LOS

attenuation

)()( BdLLLOS

+=

)(dLLOS

)(BFor both and can be read off graphs based on extensive measurements.

This model is not very precise and large errors occur in the following situation:

When the prediction point is on the main street but there is no LOS path

When the prediction point is in a side street on the same side of the main street as the BS.


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Diffraction knife edge model:

Diffraction models apply for configurations were a large obstacle is in the propagation path and theobstacle is far away from the transmitter and the receiver, i.e.: and 21 ddh ,h

The obstacle is represented as an ideal conducting half plane (knife edge)

hMShBS

d1

h

d2

Huygens secondary source


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Huygens principle: all points of a wavefront can be considered as a source for a secondary waveletsum up the contributions of all wavelets starting in the half plane above the obstacle

Phase differences have to be taken into account (constructive and destructive interferences)

Difference between the direct path and the diffracted path,

the excess path length

Phase difference: with Fresnel Kirchoff diffraction parameter.

Note: this derivation is also valid for

( )

21

21

2

2 dd

ddh +

2

2

2

== ( )

21

212

dd

ddh

+=

0


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Diffraction loss:

+=

=

du

uii

E

EL D

D

22

12020

2

0

explglg)(

0E

DE

field strength obtained by free field propagation without diffraction (and ground effects).

diffracted field strength

Shadow border region:

+

)lg(.)(

20513

0D

L,

,

0

0

>>


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Fresnel Zone:

Condition for the nth Fresnel Zone:

d1 d2

r Fnl1 l2

22121=+ nddll

Fnrdd >>

21,

Fn

Fn

r

hn

ndd

ddrddll

2

22

1

21

212

2121

=

=

++

The diffraction parameter can be rewritten with quantities describing the Fresnel zonegeometry.

For obstacles outside the 1st Fresnel zone:

For obstacles outside the 5th Fresnel zone:

dBLD

112 .)( =


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Diffraction multiple knife edge Epstein Petersen model:

The attenuation of several obstacles is computed obstacle by obstacle with the single knife edgemethod, i.e. first diffraction path: l1l2, second diffraction path: l2l3.The model is valid for . ji dh


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Diffraction multiple knife edge Epstein Petersen model:

.

( )

21

21

11

2

dd

ddh

+=

)()(21

DDDtotal

LLL +=

The Fresnel integral is replaced by an empirical approximation:

( )[ ]

+++

110102096

0

2

..lg.)(

DL

..

,.

780

780

>N

R

PV

( )

=

N

RR

N

R

P

VV

PVf

22

12

1exp)(


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Rice Fading

0

0.1

0.2

0.3

0.4

0 2 4 6 8 10

Absolute value of signal amplitude in V

Probability

Eample: Gauean distributed signal for: VVR

51

=


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Rayleigh Fading

Rayleigh fading is the other important special case of the Ricean fading. Rayleigh fadingdescribes the situation were there is no dominant path, i.e. a non LOS situation.

All contribution to the received signal are comparable in strength and arrive statistically distributed.

with : averaged field strength, and :

=

2

2

22

R

R

R

R

R

V

V

V

VVf exp)(

RV

=

0

0

0

0

1

P

P

PPf exp)(

2

0

2

1R

VP = averaged receive power:


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0.001

0.01

0.1

1

-30 -20 -10 0 10 20

Power / averaged power in dB

Integrated probability for the power to be below a fading marging fora Rayleigh distribution

Probability

Rayleigh Fading


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Fast Fading

All described types of fast fading have as characteristic length scale the wavelength of the signals.

To combat Fast Fading:

Use frequency hopping

Use antenna diversity


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Slow Fading

XdLdL += )()(

Slow fading denote the variation of the local mean signal strength on a longer time scale.The most important reason for this effect is the shadowing when a mobile moves around (e.g. in a

city).

Measurements have shown that the variation of the the mean receive level is a normal distributionon a log scale log normal fading.

The fading can be parameterized by adding a zero mean Gaussian distributed random variable .X

Let Pm be a minimal receive level, what is the probability that the receive level is higherthan the minimal receive level, i.e. ?))(Pr( =>

mRPdP

Pr

The has to be determined by measurements.

( )

=

2

2

22

1

PPPX exp)(


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Slow Fading

To compute the probability that the receive level exceeds a certain margin the Gaussian

distribution has to be integrated. This leads to the Q function:

)(1)(

21

2

1

2exp

2

1)(

2

zQzQ

zerfdx

xzQ

z

=

=

=


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Slow Fading

0.001353.00.022752.00.158661.00.500000.0

0.000053.90.001872.90.028721.90.184060.9

0.000073.80.002562.80.035931.80.211860.8

0.000113.70.003472.70.044571.70.241960.7

0.000163.60.004662.60.054801.60.274250.6

0.000233.50.006212.50.066811.50.308540.5

0.000343.40.008202.40.080761.40.344580.4

0.000483.30.010722.30.096801.30.382090.3

0.000693.20.013902.20.115071.20.420740.2

0.000973.10.017862.10.135671.10.460170.1

Q(z)zQ(z)zQ(z)zQ(z)z

Tabulation of the Q function


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Jakes Formula

Jakes formula gives a relation for the probability that a certain value Pm at the cell boundary atradius R is exceeded and the corresponding probability for the whole cell. It is based on

the log distance path loss model:

+=

0

0 lg10)()(d

dndLPdP TR

+=

22

11

21exp)(1

2

1)(Pr

b

aberf

b

abaerfPmcell

)(Prmcell

P

( )2

)(RPP

aRm

= 2

)lg(10 en

b =


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Log-normal FadingLog-normal Fading

In a shadowing environment, the probability of a certain level as function of the level value followsa Gaussian distribution on a logarithmic scale.

In general, a Gaussian distribution is described by a mean value and the standard deviation.

Level [dBm]

Probability

Level [dBm]

Probability


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From measurements the standard deviation1 sigma ( LNF ) in a certain environment.

Typical measurement values (outdoor, indoor) are given in the following table:

9 dB

9 dB

8 dB

LNF(i)

10 dB

8 dB

6 dB

Dense urban

Urban

Rural

LNF(o)Environment


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To achieve a certain cell edge probability LNF must be multiplied with a factor given in thefollowing table:

(Cell edge probability means the probability to have coverage at the border of the cell)

0.000

0.126

0.253

0.385

0.524

0.674

0.842

1.036

1.2821.645

1.751

1.881

2.054

2.326

50

55

60

65

70

75

80

85

9095

96

97

98

99

Factor for calculation of

lognormal fading margin

Cell edge probability in %


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Integrating the Gaussian distribution function over the whole cell area delivers cell areaprobabilities. Some example results are given in the following table:

77

91

97

99

50

75

90

95

Cell area probability in %Cell edge probability in %


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Interference MarginInterference Margin

An interference margin can be introduced in the link budget in order to achieve accurate coverage

prediction in case that the system is busy.

This margin in principle depends on the traffic load, the cell area probability and the frequency

reuse. The required margin will be small if interference level decreasing concepts like frequencyhopping, power control and DTX are used.

Typically, a margin of 2 dB is recommended.


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Noise Figure calculationsNoise Figure calculations

Thermal Noise:

Every object which is at a temperature T > 0K emits electromagnetic waves(thermal noise). Therefore, electromagnetic noise can be related to a temperature.

P = s * e* A * T4

Noise Factor:

The Noise Factor can be calculated from the Noise Temperature as follows:

Noise Factor = Noise Temperature / 290K + 1

Noise Figure:

The noise figure is the value of the Noise Factor given in dB:

Noise Figure = 10 * log (Noise Factor)


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Conversion table:

4384.02893.01702.0751.0

4223.92752.91591.9670.9

4063.82632.81491.8590.8

3903.72502.71391.7510.7

3743.62382.61291.6430.6

3593.52262.51201.5350.5

3443.42142.41101.4280.4

3303.32022.31011.3210.3

3163.21912.2921.2140.2

3023.11802.1841.170.1

NoiseTemp.

NoiseFigure

NoiseTemp.

NoiseFigure

NoiseTemp.

NoiseFigure

NoiseTemp.

NoiseFigure

Noise figure in dBNoise Temperature in K

Noise Figure calculationsNoise Figure calculations


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Amplifier NoiseAmplifier Noise

Amplifier:

An amplifier amplifies an input signal, as well as the noise of the input signal. It adds its own noise, which is also amplified.

GTin

Tnoise

G * Tin + G * Tnoise


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Cascade of amplifiers:

G1Tin

Tn1

G1* Tin + G1 * Tn1

G2

Tn2

G2 * (G1 * T in + G1 * Tn1) + G2 * Tn2

= G1*G2* (Tin + Tn1 + Tn2/G1)

= G * (Tin + Tnoise)

With Tnoise = Tn1 + Tn2 /G1 andG = G1 * G2

GTin

Tnoise


Equivalent to cascade of amplifiers


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Friis formula:

Tnoise = Tn1 + Tn2/ G1 + Tn3/ (G1*G2) + ...

GTin

Tnoise


Equivalent to cascade of amplifiers

Tnoise = Tn1 + Tn2/G1

G = G1 * G2


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Example:

G1Tin

Tn1

G1* Tin + G1 * Tn1

G2

Tn2

G1*G2* (T in + Tnoise)

With

Tnoise = Tn1 + Tn2/G1

Assumptions:

G1 = 16 Tn1 = 28KG2 = 20 Tn2 = 200K

Result:

Gain = 320Tnoise = 40.5K

Assumptions:

G1 = 20 Tn1 = 200KG2 = 16 Tn2 = 28K

Result:

Gain = 320Tnoise = 201.4K

Consequence:

Position of amplifier in chainis very important


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Exercise 1:

Calculate the noise temperature of the following system:

G Tnoise ?

Antenna cableLoss 10 dB

Amplifier in BTSGain 25 dBNoise temperature 240K


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Exercise 2:

Calculate the noise temperature of the following system:

Tnoise ?

Cable to antenna mastLoss 10 dB

G

Amplifier in BTSGain 2 dBNoise temperature 290K

G

Mast Head AmplifierGain 28 dBNoise temperature 260K


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Path Loss BalancePath Loss Balance

Since the coverage range in UL should be the same as the coverage range in DL, the radio linkmust be balanced:

Maximum allowable path loss in UL = Maximum allowable path loss in DL

Considering the link budget, usually the UL is the bottleneck, i.e. the maximum allowable path lossis determined by the UL and not by the DL, although:

The BS receiver sensitivity is usually better than the MS receiver sensitivity.

Diversity is usually only used in the receive path.

In case of an unbalanced link with weak UL, the UL sensitivity and therefore also the UL coveragerange can be increased by using tower mounted amplifiers.


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Cell Coverage CalculationCell Coverage Calculation

From consideration of link budget Maximum allowable path loss

Using radio wave propagation formulas (e.g.Hata) Maximum cell size

Exercise:

Consider a class 4 MS of height = 1.5 m. The BTS height = 30 m. Assume Hata

propagation conditions and a cell area probability of 97%. What is the maximum outdoor,

indoor cell radius and in-car cell radius:

a) In a dense urban environment ( LNF,o= 10 dB; LNF,i= 9 dB )?

b) In a suburban environment ( LNF,o= 8 dB; LNF,i= 9 dB)?

c) In an open area ( LNF,o= 6 dB; LNF,i= 8 dB)?

Assume an in-car penetration loss of 6dB.


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Basics about Digital Map DataBasics about Digital Map Data

The cell planning tools require as one input digital map data (which are often based on papermaps, satellite photos,). These digital map data should contain information about, the land

usage ( so called Clutter information), about the height of obstacles and they should also containso called vector data (like rivers, streets,).

A digital map is an electronic database containing geographical information.

The smallest unit on such a map is called a pixel. The typical edge-length of such a pixel isranging from several meters to several hundred meters. A digital map is often subdivided intoseveral blocks consisting of many pixels. The different layers of information in one block alwaysuse the same resolution, whereas different blocks can have different resolutions.

Each pixel should contain information about:

Land usage (Clutter information)

Height data

Vector data (like rivers, streets,)

Before working with these digital data, some pre-processing of the data may be required. Some

ideas are sketched on the following pages.


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Definition of terms

Geoid

Spheroid / Ellipsoid

Geodetic Datum / Map Datum / Datum

Projections

Are used to transfer the 3 dimensional earth to a 2 dimensional map

Nobody is perfect

No projection is at the same time exact in area, exact in angle and exact in distance.


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Geodetic datum simplified mathematical representation of the size and shape of the earth

1. Local geodetic datum best approximates the size and the shape of the particular part of

the earth

2. Geocentric datum best approximates the size and shape of the earth as a whole

spheroidgeoid

The GPS uses a geocentric datum to express its position because of its global extent.



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Two coordinates systems are implicitly associated with a geodetic datum:

a. Cartesian coordinate systemb. Geodetic (geographic) coordinate system

A third coordinate system is provided by a map projection.



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1. reference surface

2. mapping surface

3. projecton plane

Map projections:



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Cylindrical projection true at the equator and distortion increases toward the poles

1. Regular cylindrical projections

a. Equirectangular projection

b. Mercator projection

c. Lamberts cylindrical equal area

d. Galls sterographic cylindrical

e. Miller cylindrical projection



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2. Transverse cylindrical projections

a. Cassini projection

b. Transverse Mercator

c. Transverse cylindrical equal area projection



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3. Oblique cylindrical projections



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Conic projections true along some parallel somewhere between the equator and a pole anddistortion increases away from this standard

1. Lambert conformal conic

2. Bipolar oblique conic conformal

3. Albers equal-area conic

4. Lambert equal-area conic

5. Perspective conic

6. Polyconic

7. Rectangular polyconic



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Azimuthal projections true only at their centre point, but generally distortion is worst at theedge of the map

1. The Gnomonic projection

2. The azimuthal equidistant projection

3. Lambert azimuthal equal-area

4. etc.



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Compromise projection

1. Galls projection

2. Miller projection

3. Robinson projection

4. Van der Grinten Projection



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For transformation of parameters (Latitude and Longitude) from the 3 dimensional representation into

a 2 dimensional rectangular system often a combination of WGS-84 ellipsoid & UTM rectangular

coordinate system is used (like e.g. for GPS).UTM (Universal Transverse Mercator) system defines 2 dimensional positions using zone numbersand zone characters for longitudinal and horizontal scaling:

UTM zone number (1-60):longitudinal strips: range: 80south latitude - 84north latitude, width: 6 degree

UTM zone characters (using 20 characters, also called designators):horizontal strips: range: 180east - 180west longitude, width: 8 degree



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Hints concerning the usage of maps:

Avoid in any case the referencing of geodetic co-ordinates to a wrong geodetic datum.Referencing to a wrong datum can result in position errors of several hundred meters! (In

the meantime people agreed to use in the future the World Geodetic System 1984

[WGS-84] for all maps.)

Remember that e.g. different nations may use different geodetic datum.

If a datum conversion is necessary a careful transformation of seven parameters is necessary:

3 for translation, 3 for rotation, 1 for scaling

For daily work, try to use the same geodetic datum: in your planning tool(s), for your

GPS systems, and for your paper maps.

Prefer the following map scales:

1:50000 (for rural areas and 900 MHz cell planning)

1:20000 (for rural areas and 1800/1900 MHz cell planning)

1:10000- 1:5000 (for urban areas and for micro cell planning)

In the maps, height information should be included as contour lines.



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Principles of Planning Tools and their usagePrinciples of Planning Tools and their usage

Main Task of radio network planning tools:

Coverage planning

Capacity planning

Frequency planning

Link Budget calculations

Propagation predictions

Propagation model fine tuning

Co- and adjacent channel interference analysis

Macro, micro cell planning

Handling of multi-layer structures

Repeater system handling

Microwave planning


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Remarks to radio network planning tools and required digital map data:

Tools using empirical propagation models require map data with less resolution compared to toolsworking with deterministic propagation models.

In case empirical propagation models are used:

Typical pixel size: 50m x 50m to 200m x 200m

Using statistics, the signal variation around the mean value is taken into account

In case that the BS antenna is higher then the surrounding, the clutter correction term of the

target pixel contain most propagation effects. For the clutter boundaries often several pixelsbefore the target pixel are taken into account.

In case deterministic propagation models are used:

Digital data with high resolution are required (often very expensive)

Typical pixel size: 2m x 2m to 10m x 10m

Mostly used for big cities only


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Remarks to tools and required computational time:

Depending not only on the hardware used but also on the algorithms behind the software,

the computational time required by different tools varies significantly.


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Planning tools do not run fully automatically but always require some input and anintelligent and creative usage.

Remember:

Garbage in Garbage out


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Measurement Tools supporting Cell PlanningMeasurement Tools supporting Cell Planning

Fine tuning (calibration) of propagation models:

Why? When? How?

Since propagation models does not necessarily describe exactly the real situation, a fine tuning

of the models is necessary (e.g. clutter data may vary from country to country).

This tool tuning should be done in the start phase of the network planning (i.e. before a detailedplan is performed).

A test transmitter is located at typical site locations, a test receiver measures the RX_LEValong predefined measurement routes. These measured values are taken as input for the tool finetuning.


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Cell TypesCell Types

Omni-Cell Sector-Cells

Exercise:

Compare the coverage of an omni-cell (antenna gain = 10 dBi) and the coverage of a three sector-cell configuration (antenna gain 18 dBi).


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Omni versus Sector CellsOmni versus Sector Cells

Omni sites:

J Advantages of omni sites:

Trunking gain (especially interesting for those networks having only a few frequencies)

Omni antennas are usually less bulky than sector antennas

Suitable in those areas, where the surrounding terrain limits the coverage (before the

maximum omni cell radius is reached)

L Disadvantages of omni sites:

In case of horizontal antenna diversity: Diversity gain depends on direction

Greater reuse distance required

Less flexibility in network optimization (concerning antenna tilt, power control

parameters, handover parameters)

TX/RX antenna separation difficult (usually TX/RX antennas are mounted on different

vertical levels to achieve sufficient separation)

Limited mounting positions: no wall mounting possible


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ExercisesExercises

1) Consider:

an extended cell with 100 km cell radius covering a sea area (clutter term: 30 dB),

a 900 MHz mobile station of power class 4,

a BS with the GSM minimum receiver sensitivity,

an (BS) antenna gain of 15 dBi.

What should be the height of the BS antenna?

2) Consider:

a mobile station with 2 Watts output power maximum,

a BS receiver sensitivity of 104 dBm,

an (BS) antenna gain of 15 dBi.

For a satellite carrying the BS, what would be the maximum radius for the satellite orbit.

3) How many sites can be saved in principle if TMAs with 6 dB gain are used in the

network? Use typical values and Hatas propagation formula for calculation.

02 mn1790 coverage planning ww fh

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