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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
t.ag
r"em
.ag
r"
Low
reg.
-14
.40
.99
70.
984
-14
.00
.995
0.9
84-1
3.7
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
teC
arlo
sim
ula
tion
cove
rage
pilo
tq
ua
lity
do
wn
link
perf
orm
ance
up
link
perf
.
IA(E
c)I
IA(E
c/I
O)I
IA(C
)IIA
(C)I
~IA
(SH
O)I
IA(P
P)I
2:iP
;[W]
[1X
l[1
[I
XI
Ber
linpr
ep.
100.
098
.698
.698
.623
.91.
177
3.2
35.9
94.0
11
4.7
16.3
100.
0l-
op
t10
0.0
99.8
99.8
99.8
22.9
1.0
66
0.7
30
.797
.991
.215
.110
0.0
MIP
100
.099
.899
.899
.822
.91.
064
7.9
30.1
98.1
89.2
15.0
100
.0
Lisb
onpr
ep.
98.4
99.9
98.3
98
.723
.80.
94
69
.824
.597
.581
.811
.110
0.0
l-o
pt
98
.710
0.0
98.6
99.1
22.0
0.8
42
2.9
22.1
99.0
65.7
10.4
100.
0M
IP9
8.7
100.
09
8.7
99.1
22.2
0.7
42
2.6
22.1
99.0
65.8
10.4
100.
0
Tur
inpr
ep.
84.2
99.6
83.8
64.9
20.7
1.0
19
99
.429
.999
.02
09
.035
.191
.4l-
op
t84
.299
.683
.864
.92
0.7
1.0
1995
.629
.999
.020
8.9
35.1
91.4
MIP
84.1
99.6
83
.764
.620
.40.
91
83
8.7
27.5
99.4
196.
134
.192
.1
Vie
nna
prep
.71
.099
.970
.994
.816
.40.
822
57.1
31.3
98.4
191.
611
.110
0.0
l-o
pt
70.9
99.9
70.8
94
.716
.20.
82
18
3.7
30.3
98.8
175.
310
.710
0.0
MIP
70.9
99.9
70.8
94
.716
.20.
82
17
3.6
30.2
98.9
173.
010
.610
0.0
All
units
inp
erc
en
tun
less
stat
edo
the
rwis
e.
For
the
sym
bo
lsus
edfo
rp
erf
orm
an
cein
dic
ato
rsan
dth
eir
de
fin
itio
ns
see
Sec
.3.4
.
~ 0'\
00
-
I[I
66.8
54.5
53.1
54.5
44
.84
4.9
61.6
61.4
55.1
79.5
73.4
I~72
.7lJ
j I ~ ~ ~ Q'
;::s r2..~ ~ ¥r. ei
) a ;::s (j a ~ '\3 ~ B" 6' ;::s r2.
.~ V
J E.. Cf;'
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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