Appendices

Data for network planning

Table A.1: Traffic scaling factors against original datafor different traffic intensities and service mixes

traffic intensity

service mix low medium high

Berl in Speech On Iy 3.2051Video On Iy 4.1 768All Services 0.6000

Lisbon Speech Only 1.7862Video Only 2.2833All Services 0.3259

Table A.2: Additional parameters

parameter

4.27355.56900.8000

2.74033.45960.4938

5.34196.96131.0000

4.38455.53540.7901

unit value

maximum load DL p:naxl p:naxmaximum load UL

minimum Ec level »«minimum Ec/lo level fl Ee/ Ia

common pilot power p(p)

slow fadi ng standard deviation

0/0 700/0 50

[dBm] -105[dB] -15

[dBm] 30[dB] 8

156

Table A.3: Antenna models used for case studies

App. A - Datafor network planning

elec. opening angle gain

model scenario ti It horizontal vertical [dBi]b

Kathrein 742212 Berlin 0-8° 63° 6.5° 18.0Kathrein 742265 Lisbon 0-6° 65° 6.0° 18.5Kathrein 741 784

} Turina0-8° 60° 6.0° 18.0

Kathrein 742213 0-6° 65° 4.0 ° 19.5Kathrein 742271 0-6° 56° 7.0° 18.5"60 deg sector" Vienna 0° 58° 15.0° 15.0

a Type 742213 is used predominantly (302 out of 335 sectors)b Amplification of the signal in direction of the main lobe as compared to a

perfectly isotropic radiator (in dB)

Figure A.1: Key geographical data, Berlin scenario

55

terrainheight[m]

30(b) Traffic distribution (normalized DL user load

intensity)

App. A - Datafor network planning 157

Figure A.2: Key geographical data, Turin scenario

250

terrainheight[m]

225

600

•

•

•

~km

•

• •

• • •• •.. .0.-: •• ·a';J ••••

. ~. () .

••

• •• •

• ••• •

••

~

•• • •• •

•(a) Terrain height and site candidate position

-;. -.i \ ,' . .: ". .', ..

~. .. ..

'. . ;. , ".~.

ee ....

~m

2.8

o(b) Traffic distribution (normalized DL user load intensity)

158

Figure A.3: Key geographical data, Vienna scenario

(a) Terrain height and site candidate position

(b) Traffic di stribution (normalized DL user load intensity)

App. A - Datafor network planning

• •• •1:11 . • •

• •• ~. ~. ~ • • ••

~• ••

• •• ()

•

•

•••• 600

0

• terrain

• 0 height[m]

~lkm 225

6.4

o

App. A - Datafor network planning 159

Table A.4: Scenario data

height [m] extension [km] area

min max x y [km2]

Berlin 32.0 55.0 7.5 7.5 56.25Lisbon 0.0 106.0 4.2 5.0 21.00Turin 222.0 1 164.0 17.9 15.4 274.00Vienna 224.0 988.0 23.0 19.0 437.00

no. of no. of sector antenna height [m]

sites sectors [0] min avg max

Berlin 68 204 90 23.0 35.7 70.0Lisbon 60 164 0 7.0 24.5 39.0Turin 111 335 30 20.0 30.1 48.0Vienna 211 628 30 27.0 29.5 32.0

resolu- avg. ortho- total avg. user loadtion [m] gonality user load intensity [km -2]

Berlin 50 0.414 51.64 0.92Lisbon 20 0.339 52.45 2.50Turin 50 0.633 96.40 0.35Vienna 25 0.600 97.43 0.22

Table A.5: Service parameters and traffic mix for MORANS scenarios (Turin and Vienna)

BLER data rate activity CIR target [dB]a share"[%] [kbps] factor [%] min avg max [%]

Turin Voice 1 12.2 0.5 -15.2 -14.8 -14.1 48.7Video 1 64.0 1.0 -11.7 -11.2 -10.4 44.4Data 1 32.0 1.0 -14.8 -14.3 -13.6 6.9

Vienna Voice 1 12.2 0.5 -15.2 -13.7 -12.7 48.4Data 1 10 128.0 1.0 -9.0 -7.6 -6.6 28.1Data 2 1 64.0 1.0 -11.7 -10.0 -8.9 23.4

a The CIR target depends on the user's velocityb Percentage of overall traffic load

~

Tab

leA

.6:

Ser

vice

para

met

ers

and

tra

ffic

mix

for

MO

ME

NT

UM

scen

ario

s(B

erlin

and

Lisb

on)

I~

BLER

data

rate

"a

ctiv

ity

fact

or"

CIR

targ

et[d

B]C

shar

e[%

]d

[%]

[kbp

s]m

inav

gm

axm

inav

gm

axB

erlin

Lisb

on

Voi

ce1

12.2

0.50

0.50

0.50

-17

.5-1

7.3

-16

.818

.718

.2V

ide

o1

64.0

1.00

1.00

1.00

-12

.1-1

2.1

-12

.114

.314

.4S

trea

min

g1

64

.0-1

28

.01.

001.

001.

00-1

2.1

-9.8

-9.6

59.3

59.5

EM

ail

103

2.0

-12

8.0

0.83

0.91

0.95

-15

.6-1

2.3

-8.4

0.1

0.1

Do

wn

loa

d10

64

.0-3

84

.00.

440.

880.

90-1

2.5

-12

.1-6

.56.

97.

1M

MS

103

2.0

-12

8.0

0.82

0.90

0.95

-15

.6-1

1.8

-8.4

0.3

0.2

WW

W10

32

.0-3

84

.00.

360.

730

.87

-15

.6-1

1.5

-6.5

0.5

0.5

aD

ata

user

sm

aybe

assi

gned

dif

fere

nt

bear

ers

acc

ord

ing

toR

RM

po

licy

and

ava

ilab

ility

bF

orda

tase

rvic

es,

the

act

ivit

yfa

ctor

isad

apte

dto

the

assi

gned

bear

er;

for

ah

igh

er

con

ne

ctio

nsp

eed,

less

act

ivit

yis

assu

med

CT

heC

IRta

rget

depe

nds

onth

eas

sign

edbe

arer

and

onth

eus

er's

velo

city

dP

erce

ntag

eof

over

all

tra

ffic

load

~ ~ ~ I t:J i::l £" ~ ~ ;::s ("

\) 8" Q *"\3 ~ ;::s ;::s ~.

App. A – Data for network planning 161

Figure A.4: Antenna diagrams of most frequently used antennas

0 dB −20 dB

0◦ electrical tilt6◦ electrical tilt

(a) Kathrein 742 265, horizontal plane

0 dB −20 dB

(b) Kathrein 742 265, vertical plane

0 dB −20 dB

0◦ electrical tilt6◦ electrical tilt

(c) Kathrein 742 213, horizontal plane

0 dB −20 dB

(d) Kathrein 742 213, vertical plane

0 dB −20 dB

(e) “60 deg sector”, horizontal plane

0 dB −20 dB

(f) “60 deg sector”, vertical plane

162 App. A – Data for network planning

Figure A.5: Smoothed antenna diagrams used in the MOMENTUM scenarios

0 dB −20 dB

0◦ electrical tilt8◦ electrical tilt

(a) Kathrein 742 212, horizontal plane

0 dB −20 dB

(b) Kathrein 742 212, vertical plane

0 dB −20 dB

0◦ electrical tilt6◦ electrical tilt

(c) Kathrein 742 265, horizontal plane

0 dB −20 dB

(d) Kathrein 742 265, vertical plane

Additional detai Is on computational resu Its

Table B.1: Estimation of other-to-own-cell interference ratio, network "Berlinopt."

no shadowing shadowing

intensity speech video all speech video all

low mean rei. error 0.062 0.104 0.111 0.332 0.342 0.3631-correlation 0.005 0.041 0.011 0.146 0.167 0.170

medium mean rei. error 0.031 0.078 0.073 0.305 0.286 0.2971-correlation 0.002 0.025 0.012 0.188 0.200 0.246

high mean reI. error 0.029 0.062 0.062 0.286 0.279 0.2871-correlation 0.001 0.012 0.011 0.180 0.225 0.277

Tab

le8.

2:A

ppro

xim

atio

nof

cove

rage

prob

abil

ity

Spe

ech

Vid

eoA

ll

inte

nsit

yne

twor

kop

t.th

r'op

t.ag

r"em

.ag

r"op

t.th

r'op

t.ag

r"em

.ag

r"op

t.th

r'op

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r"em

.ag

r"

Low

reg.

-14

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.99

70.

984

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84-1

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0.9

940.

984

opt.

1-1

4.5

0.99

90.

988

-14

.70.

995

0.98

3-1

5.0

0.99

40.

982

opt.

2-1

4.4

0.99

50.

972

-14

.20.

992

0.97

4-1

4.2

0.99

20.

972

opt.

3-1

4.3

0.97

90

.948

-14

.50.

984

0.95

7-1

4.3

0.98

40.

959

Med

ium

reg.

-13

.10.

955

0.95

2-1

3.2

0.95

60.

953

-13

.20.

958

0.95

4op

t.1

-12

.80

.917

0.91

6-1

2.9

0.9

300

.928

-12

.90

.934

0.9

30op

t.2

-12

.60.

899

0.89

9-1

2.6

0.9

07

0.90

7-1

2.7

0.90

80.

908

opt.

3-1

2.4

0.8

97

0.89

4-1

2.5

0.90

40.

901

-12

.60.

906

0.90

4

Hig

hre

g.-1

2.6

0.92

20.

921

-12

.50.

924

0.92

3-1

2.5

0.92

40.

924

opt.

1-1

2.3

0.87

80.

869

-12

.40.

885

0.88

3-1

2.4

0.8

87

0.88

6op

t.2

-12

.10.

884

0.86

1-1

2.3

0.88

40.

867

-12

.20.

884

0.86

9op

t.3

-12

.10

.885

0.8

57

-12

.10.

884

0.86

2-1

2.0

0.88

50.

864

aT

hres

hold

for

best

agre

eme

nt

bet

wee

nsi

mu

latio

nre

sult

and

appr

oxim

atio

n[d

B]

b/c

Fra

ctio

nof

corr

ectl

yp

redi

cted

pix

els

for

opt

ima

lth

resh

old

/for

com

mo

nth

resh

old

of-

12.7

dB

~ s ~ ~ lJj I ~ ~ ~ o' ;::s r2..~ ~ ¥r. ei

) a ;::s (j a ~ '\3 ~ B" 6' ;::s r2.

.~ V

J E.. Cf;

App. B - Additional details on computational results 165

Table B.3: Effect of refined estimation on the prediction accuracy for grade of service

exp.-coupl ing estimate refined estimate

intensity speech video all speech video all

low max underestimation 0.000 0.000 0.000 0.000 0.000 0.000max overestimation 0.001 0.033 0.042 0.001 0.010 0.012max reI. error 0.001 0.035 0.044 0.001 0.010 0.013mean reI. error 0.000 0.002 0.003 0.000 0.001 0.0011-correlation n/a" n/a' n/a" 0.002 0.014 0.016

medium max underestimation 0.015 0.070 0.073 0.006 0.046 0.049max overestimation 0.045 0.076 0.076 0.007 0.004 0.005max reI. error 0.048 0.089 0.093 0.008 0.059 0.063mean reI. error 0.005 0.017 0.020 0.001 0.004 0.0051-correlation 0.055 0.238 0.258 0.001 0.002 0.003

high max underestimation 0.016 0.063 0.072 0.008 0.032 0.039max overestimation 0.037 0.079 0.079 0.006 0.003 0.004max reI. error 0.039 0.087 0.098 0.012 0.045 0.054mean reI. error 0.006 0.023 0.026 0.001 0.009 0.0101-correlation 0.003 0.026 0.030 0.000 0.001 0.001

* All estimates are invariant at 100 0/0, so correlation is undefined

Figure B.l: Grade-of-service estimates, medium traffic intensity

0.9

grade of service

1.0--0

- - - - - -

0

- - , \

\\0.8 0.8

- estimate

• simulation

est.loadfactor 1.00.7 "----'0"'------- ----'----- --'-------_-----'----_

(b) All services

est.loadfactor 1.00.7 "----'0"'------- -----"--- ------'---__---"-----

(a) Speech service only

166 App. B - Additional details on computational results

Figure 8.2: Influence of shadowing on estimates for grade of service(medium load level, complete service mix)

grade of service1.0 --··_·---4.~....c--..----=-----'

,~:...., ,tI •. . !,..-- .0.9 • ••.. .=.: ..

0.8 0.8- estimate

• refined est.

est.loadfactor 1.0

(b) Precise expected-coupling calculation

0.7 L---'0"'------ ----'---- --"------_------'---_

est.loadfactor 1.0

0.7 L...>0~ -----"---- -----"----__,--------

(a) Medians of attenuation

Table B.4: Performance of discrete load-control methods for Berlin network:avg. transmit power

speech service all services

intensity method 0/0 hi" f2f ov? f2f und" f2f all d 0/0 hi" f2f ov" f2f und" f2f all d

low Rnd. Act. 46.43 0.447 0.399 0.000 62.59 3.171 2.588 0.108Rnd. Order 14.29 0.198 0.233 0.000 4.94 0.606 1.999 0.071Knapsack 35.71 0.091 0.124 0.000 23.07 0.583 0.499 0.019Mult. Knaps. 0.00 0.000 0.663 0.000 0.00 0.000 4.096 0.151

mid Rnd. Act. 52.57 0.840 0.802 0.130 58.04 4.708 2.889 0.732Rnd. Order 5.92 0.117 0.304 0.048 2.74 0.569 2.149 0.411Knapsack 58.94 0.195 0.134 0.027 28.70 0.536 0.442 0.089Mult. Knaps. 0.00 0.000 0.730 0.121 0.00 0.000 4.259 0.834

a Percentage of load-controlled cells exceeding load limit

b/c Average difference of cell power to pfnax of load-controlled cells exceeding/observing load limit [W]d Average absolute difference of power values for perfect and discrete load control [W]

App. B - Additional details on computational results

Table B.5: Performance of discrete load-control methods for Berlin network:fraction of served traffic in load-controlled cells

speech service all services

intensity method 0/0 hi" f2f ov" f2f und" 0/0 hi" f2f ov" f2f und ':

low Random Activation 57.14 0.011 0.014 62.68 0.053 0.078Random Order 10.71 0.014 0.010 12.13 0.027 0.063Knapsack 32.14 0.012 0.011 25.06 0.029 0.037Multiple Knapsack 0.00 0.000 0.022 1.68 0.008 0.109

mid Random Activation 52.69 0.020 0.023 57.70 0.063 0.087Random Order 30.47 0.010 0.014 18.13 0.030 0.062Knapsack 55.81 0.032 0.020 33.51 0.040 0.040Multiple Knapsack 12.24 0.005 0.017 5.69 0.011 0.082

a Percentage of load-controlled cell s serving more traffic than expectedb Average over-service (percentage points)C Average under-service (percentage points)

Table B.6: Parameters and interference ratiofor benchmark configurations

167

BerlinLisbonTurinVienna

site dist. [m] ti It [0]

1343 8870 6

1173 41550 8

intf. ratio [0/0]

66.352.4

135.7141 .4

Tab

leB

.7:

Co

mp

lete

ne

two

rksc

ore

card

sre

sulti

ngfr

omsi

mp

lifie

dM

on

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arlo

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ua

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up

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Ber

linpr

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098

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177

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11

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op

t10

0.0

99.8

99.8

99.8

22.9

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66

0.7

30

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0.0

MIP

100

.099

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.899

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064

7.9

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98.1

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Acronyms and Symbols

Notation that is not listed here is defined where it is used. Plain numbers refer topages of introduction, bracketed numbers to definitions.

Acronyms

2G/3GBLER

CDMA

CIR

C.O.V.

CPICR

dBdBmDL

DSL

Eb

Ee

FDD

GPRS

GSM

RSPA

10

MIP

NoOFDM

RNC

RRM

TCP

UL

UMTS

UTRA

W-CDMA

WLAN

WWW

XML

2nd/3rd generation (telecommunications system)block error ratecode division multiple access, 11carrier-to-interference ratio, 15coefficient of variation, 71common pilot channel, 14decibel (dimensionless), 11decibel referenced to one milliwatt (power unit), 11downlink directiondigital subscriber linereceived bit energy, 15received chip energy, 14frequency division duplex, 12general packet radio serviceglobal system for mobile communicationshigh speed packet accessinterference and noise spectral density, 14mixed integer (linear) programinterference and noise spectral density (including orthogonality), 15orthogonal frequency division multiplexingradio network controller, 8radio resource managementtransmission control protocoluplink directionuniversal mobile telecommunications systemUMTS terrestrial radio accesswideband code division multiple access, 11wireless local area networkworld wide webextensible markup language

170

Symbols

.I 1.1

x,x,X

I'I ~IB(Xm

AAiA(c)

A(Ec )

A (Ecl1o)

A(rr)

A (SHO)

f3c,cT.

1)

1Ci j

e1/e1

V ijdiag(x)Fj(c) (z)

'YJ(- )I 'Y[ (-)t(- )

I I 1'Ymi 'YimIIIIs

-1/-1li l

IT1

IIK(eov)

LilL£l /£~AiXJimMIMiJiEci 10

V·1

Acronyms and Symbols

quantity defined in uplinkI downlinkscalar, vector, matrix, 25

area weighted by normalized user load intensity, (3.48b)indicator function of set B, 59activity factor for user m, 21

complete scenario area, 19best server area of cell i, (4.1)covered area, (3.51)Ee-covered area, (3.49)Ee/lo-covered area, (3.50)pilot-polluted area, (3.53)soft handover area, (3.52)weight for combining objective approximations, 119coverage set of configuration i, (5.2)

uplink interference coupling coefficient between cells i and j, (3.3)

downlink interference coupling coefficient between cells i and j,(3.11)uplinkI downlink interference coupling matrix, 38I 40dominance set of i over j, (5.9)diagonal matrix with the elements of the vector x on the diagonalfeasible network designs, 111coverage level of network design z, (5.7)

path loss component of channel gain to I from cell i, A ----7 [0,1], 20shadowing component of channel gain, A ----7 IR>o, 20

end-to-end channel gain between mobile m and cell i, 20

identity matrix of matching dimension, 25set of all potential antenna configurationsI configurations for sector8, 111

average other-to-own-cell interference ratio in cell i/in planningarea, (3.37)/(3.47b)other-to-own-cell interference ratio at cell iaverage other-to-own-cell interference ratio in uplink, (3.47a)reference coverage value, 120cell load I average cell load, (3.41)-(3.45)

uplinkI downlink user loading factor for user m, (3.2)I (3.9)traffic scaling factor I grade of service for cell i, 44total grade of service (network aggregate), (3.46)CIR target for user m, 20

all mobiles/mobiles requesting service by cell i, 19

Ee110 coverage threshold, 24price of selecting configuration i, 112

Acronyms and Symbols 171

N1J~/1J1(.)

171nNm ax

NRT1

NR i

W(·)/Wmp

(c)Pi

(r-)Pi-1Pi

1n:p:naxp:naxp~rj)

n Ee

tPp~:~

pJnax- TPiplR+/R>op(X)y.1

1

T

Tj /T]Uia

V~j)ia

;r(E~)~mm

Yaz,

set of cells, 19

noise at mobile m/noise function, Def. q, 22

noise at cell i, 21

number of cells, 19limit for network cost, 119

noise rise at cell i, (2.5)

average noise rise, (3.42)orthogonality loss function/factor for mobile m, Def.a, 21

subdivision of the planning area ("pixels"), 113, 116

Total common channel power of cell i, 22

Pilot power of cell i, 24

average total transmit power of cell i, (2.4)

Power emitted by cell i on the link to mobile m

maximum nominal output power for cell i, 23

maximum average output power for cell i, 23

downlink noise load of cell i, (3.12)Ee coverage threshold, 24vector of capacity limits, 119

maximum output power of mobile m, 23

maximum average received power at cell i

average total received power at cell i, (2.2)

power emitted by mobile m in uplink, 21

Nonnegative/positive real numbersspectral radius of matrix X (largest modulus of an eigenvalue)

downlink traffic loading factor of cell i, (3.15)

user intensity function, A ----+ R+, 29

normalized uplink/downlink user load intensity function, (4.2)service variable for pixel a and configuration i, 116

interference variable for server i, pixel a, and interferer j, 116

minimum fraction of reference coverage to be attained, 120

coverage variable for pixel a, 113selection variable for antenna configuration i, 111

Index

admission control, 17, seealso load controlalgorithms, see optimization methodsantenna configuration, 96-98antenna diagram, 96-97, 123antenna height, 96azimuth, 97

optimization, seecapacity optimization

Ec 110, 87-88indoor vs. outdoor, 134-137optimization, 94, 114, 120, 125uplink, 23,45

data scenarios, 5, 122-124downlink, see link direction

heuristic optimization methods, 99-101hierarchical optimization, 103, 125HSPA,28

linear complementarity problem, 48-49link direction, 8

and performance optimization, 137bottleneck, 27, 77, 122

load balancing, 24, 115, 131, 144-147load control, 17

in static models, 31-32perfect, 42-46perfect vs. classical, 45-46, 50-52, 78­

81,88-89load factor, 42, 53-54, 69-73, 143-147

fast fading, II, 16, 18, 20frequency reuse factor, 52, see also other­

to-own-cell interference ratio

interference, 9-10, 12bounds on, 143-147coupling, see coupling matrixintra- vs. inter-cell, 13, 38, 40, 52, 57,

73, 119, 144reduction, 112, 115, 120, 125, see also

capacity optimization

capacity optimization, 93, 94, 114-119, 125bounds for, 143-147case studies in, 128-139downlink vs. uplink, 137running times, 138-139

CDMA,ll-12cell, 8cell area, 8, 68, 115-116cell load, 56-57CIR,15

average, 21, 23equation, 20-23target, 20, 30

combinatorial optimization, 98-101complementarity system, 45

deduction, 41-43solving, 46-50

congestion control, 17, 28, 31, seealso loadcontrol

coupling matrix, 37-41expected, 68-69, 115in optimization model, 116-118

coverage, 15,58-59Ec, 128E, vs. E, 110, 15, 24-25, 112, 124

best server, 41, 67-68 Eb/No, 15blocking, 27,44, 72-73, 84-85, 148, see also Ec, Ec/Io, 15, 24-26, see also coverage

load control

174

critical, 53-55, 71, 82-85local search, 100, 110, 126-127

search space, 139-141vs. MIP k-opt, 127, 130-143

mixed integer programming, 100k-opt heuristic, 127vs .local search, seelocal search vs. MIP

k-optmulticriteria optimization, 101-103

of network performance, 107-109, 124-127

network cost, 95, 112, 120, 125Neumann series, 37, 115noise rise, 23-24, 57

optimization methodsemployed here, 124-127in literature, 110-111overview, see combinatorial optimiza­

tionorthogonality, 40, 41, 54, 76

in static models, 21-23orthogonal codes, 13-14

other-to-own-cell interference ratio, 52-54,57-58,69-71,87,114-115,119,129

outage, 27, 31 , 45

path loss, seepropagation modelsperformance indicators, 56-60

accuracy of estimates, 69-73, 81-90estimating, 67-69, 73-77stochastics of, 66-67

pilot channel, 14-15, 24-25pilot power

and soft handover, 98optimization, 98pollution, 60

pixel, 69, 112-113Poisson point process, 29, 31, 68pole equation, 41-43, 52-55, 119

generalized vs. classical, 55-56power control, 16-17

in optimization models, 107perfect, 20

Index

power limits, 23-24, 44propagation models, 10, 20, 123

radio network, 8, 26radio network planning

data for, see data scenariosdecisions, 95-98, 123-124objectives, 94-95, 124overall process, 2

service, 16, 30service mix, 77

and perfect load control, 78-81and performance estimates, 81-88

shadow fading, II, 20, 66, 112and performance estimates, 85-88models for, 30

signal to interference ratio, 8, 16, see alsoCIR

simulationconvergence, 65dynamic vs. static, 18-19static Monte Carlo, 27-28, 64-67

site location, 95-96snapshot, 18,19,26

average, 110random distribution on, 29-31,68, 109-

110soft capacity, 23-24, 46soft handover, 15, 19, 60static model, 19-27

in performance optimization, 105-107in simulation, 18, 27-28

test mobile, 54, 58tilt, 97

electrical vs. mechanical, 97, 124optimization, seecapacity optimization

tilt distribution, 132traffic, seeuser load

uplink, see link directionuser load

intensity, 29, 122normalized intensity, 68

W-CDMA, 13-17

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