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Contents
1 UMTS Service Model....................................................................................................................................1
1.1 Service Classification...............................................................................................................................1
1.2 Service Model..........................................................................................................................................2
1.2.1 Classification of Area Types.....................................................................................................2
1.2.2 CS Domain Service Model.......................................................................................................3
1.2.3 PS Domain Service Model.......................................................................................................4
2 UMTS Coverage Estimation........................................................................................................................9
2.1 Radio Propagation Model........................................................................................................................9
2.1.1 Free Space Propagation Loss....................................................................................................9
2.1.2 Propagation Model.................................................................................................................10
2.2 Link Budget............................................................................................................................................12
2.2.1 Basic Link Budget Parameters...............................................................................................13
2.2.2 Unlink Budget.........................................................................................................................22
2.2.3 Uplink/Downlink Balance......................................................................................................22
2.3 Coverage Scale Estimation....................................................................................................................23
2.3.1 Calculation of BS Coverage Radius.......................................................................................23
2.3.2 Calculation of BS Coverage Area..........................................................................................24
2.3.3 Scale Calculation....................................................................................................................25
3 UMTS Capacity Estimation.......................................................................................................................27
3.1 Capacity Estimation Flow......................................................................................................................27
3.2 Estimation Method of Hybrid Service Capacity....................................................................................27
3.2.1 Equivalent Erlang Method......................................................................................................28
3.2.2 Post Erlang-B Method............................................................................................................29
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3.2.3 Campbell Method...................................................................................................................30
3.3 Uplink Capacity Estimation ..................................................................................................................32
3.3.1 Load Analysis for Uplink.......................................................................................................32
3.3.2 Uplink Capacity and Scale Estimation...................................................................................35
3.4 Downlink Capacity Estimation..............................................................................................................37
3.4.1 Analysis of Downlink Load....................................................................................................37
3.4.2 Downlink Capacity and Scale Estimation..............................................................................40
4 Scale Estimation Example..........................................................................................................................43
4.1 Assumed Conditions..............................................................................................................................43
4.2 Estimation Process.................................................................................................................................43
4.2.1 Estimation Flow Chart............................................................................................................43
4.2.2 Uplink Coverage Estimation..................................................................................................44
4.2.3 Uplink Capacity Estimation...................................................................................................46
4.2.4 Downlink Capacity Estimation..............................................................................................48
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Entertainment 64 128
WWW 64 128
FTP 64 128/384
Video streaming 64 384
1.2 Service Model
Service model is the reference for capacity estimation. It reflects the proportion of each
service in hybrid service under various service environments. Based on this proportion,
you can estimate the average traffic or data throughput of a single user. Multiply the
value by the expected number of users in various environments to get the
corresponding total traffic or throughput.
1.2.1 Classification of Area Types
Service model is very important to the UMTS network design because it is the
reference for capacity estimation and determines whether to take future network
service demands into account during planning. On the other hand, service model is
hard to predict. Service model is closely associated with the behavior habits of different
users using different services and users habits of using services are closely associated
with many factors in different areas, such as economy and culture. Therefore, a service
model is inapplicable for the application requirements of different environments.
According to service type distribution, service development policy and user dynamic
distribution as well as consumption behavior features in an area, service distribution
areas are categorized into six classes, downtown area, urban area, suburb area, rural
area, main line of communication/scenic spot and indoor coverage. Table 1.2-1 gives
service distribution features and user density of different areas.
Table 1.2-1 Service Distribution Features and User Density of Different Areas
Area
Service
Distribution
Feature
Site
Classification
User Density
(user/km2)
Population Density
(user/km2)
Downtown area Traffic-intensive
High service rate
requirement
Key area of data
service
Central business
district*
>12000>50000
Irregular
building-
intensive area
>8000 >30000
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Table 1.2-2 Voice Service Model
Area BHCA Call Duration (S) Traffic (Erl/BH)
Downtown
area
Central business
district2.7 60 0.045
Irregular
building-
intensive area
1.8 60 0.03
Dense building
complex area1.2 60 0.02
Urban area 1.2 60 0.02
Suburb area 1.018 60 0.018
Rural area 0.96 60 0.016
Main line of
communication/scenic spot0.9 60 0.015
Table 1.2-3 Video Phone Service Model
Area BHCA Call Duration (S) Traffic (mErl/BH)
Downtown
area
Central business
district0.135 120 4.5
Irregular
building-
intensive area
0.09 120 3
Dense building
complex area0.06 120 2
Urban area 0.06 120 2
Suburb area 0.0509 120 1.8
Rural area 0.048 120 1.6
Main line of
communication/scenic spot0.045 120 1.5
1.2.3 PS Domain Service Model
The data service call model widely differs from the voice service call model. Data call
has the following features:
Conversion between Dormant state and Active state;
Each session of a user can consist of several packet calls and different data service
types and user types have differentiated features;
Data is transmitted in data burst mode;
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international UMTS data service features, parameters of data service ETSI model in
downtown area are given in Table 1.2-5:
Table 1.2-5 Parameters of Data Service ETSI Model in Downtown Area
Service BHSA
Call per
Session
UL/DL
Packet
in a Call
UL/DL
Mean Packet
Size (Byte)
Throughput
UL/DL(kbits)
E-mail 0.3 2/2 15/15 480 34.56/34.56
MMS 0.05 2/2 15/15 480 5.76/5.76
Intranet 0.15 5/5 4/27 480 11.56/77.76
E-
commer
ce
0.05 2/2 10/26 480 3.84/9.98
Info
Services0.08 2/2 5/33 480 6.14/40.69
Entertai
nment0.02 5/5 4/27 480 1.54/10.37
WWW 0.2 5/5 2/15 480 7.68/57.60
FTP 0.15 1/1 8/74 480 4.61/42.62
Because all services will finally come down to the bear rate, Table 1.2-6 provides a
recommended data service model at the early stage of 3G construction based on bear
rate. Where, 384 service is applicable only for downtown and urban areas due to its
great impact on network coverage.
Table 1.2-6 Data Service Model
Bear
Rate
(kbps)
Busy Hour Traffic (kbits)Uplink/Downli
nk ProportionDowntown
AreaUrban Area Suburb Area Rural Area
64/64 80.64 63.04 38.8 15.76 1:1
64/128 161.88 140.3 87.35 34.94 1:7
64/384 112.51 86.8 54.25 21.7 1:10
Note: The data in this table is intended for Class 4 area, which relatively drops behind
Class 1, 2 and 3 areas so that you can multiply the data by 30, 20 and 10 respectively
for these areas. Overseas developed areas are taken as Class 1 areas.
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2 UMTS Coverage Estimation
2.1 Radio Propagation Model
2.1.1 Free Space Propagation Loss
Because of propagation path and landform interference, propagation signals are
decreased, which is known as propagation loss. In the space propagation, many factors
enter into radio wave loss, including ground absorption, reflection, refraction and
diffraction. In the case that radio wave is propagated in free space (homogeneous
medium with isotropy, imbibition and electric conductivity as zero), the above factors
are uncertain. However, it does not mean that there is no propagation loss of radio
wave in free space. After radio wave is propagated for a certain distance, it may also be
attenuated due to radiant energy diffusion (also called attenuation or loss).
When the transmitter whose transmission power is Pt eradiates radio signals through
isotropy antenna with gain as Gt, the signal power density Sr is:
24 dGtPtSr
=
The signal power Pr received by the antenna with gain as Gr is:
ArSr=Pr
Where, Ar stands for the effective receiving area of antenna,
4
2=
GrAr
then, ( )2
2
4Pr
dGrGtPt
=
Pt refers to the power from transmitter to transmit antenna.
refers to the electromagnetic wave length.
d refers to the distance between transmit and receive antennas.
Gt refers to the transmit antenna gain.
Gr refers to the receive antenna gain.
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The propagation loss is defined as the ratio of power from transmitter to transmit
antenna to power received by receive antenna:
( )2
24
Pr
==
GrGt
dPtLoss
Path loss is measured by dB, then space propagation loss (Loss) is:
( )( ) ( )GrGt
d
GrGt
dLoss lg10lg10
4lg20
4lg10
2
2
=
=
Propagation loss of free space (Free Loss) is:
= d
Loss
4
lg20
If and d are measured by Km and f is measured by MHz, the common formula
is:
fdFreeLoss lg20lg2044.32 ++=
From the above formula, we can see that the larger the distance (d) between transmit
antenna and receive antenna, and the larger the radio wave frequency (f), the larger the
free space loss. When d or f is doubled, the propagation loss of free space will be
increased by 6 dB.
2.1.2 Propagation Model
While planning and constructing a mobile communication network, you have to make
detailed study about electric wave propagation features and field strength prediction
before determining frequency band, frequency allocation and radio wave coverage,
calculating communication probability and inter-system electromagnetic interference,
and finally defining radio equipment parameters. The radio propagation model is a
mathematic formula of such variables as radio propagation loss and frequency,
distance, environment and antenna height concluded by theory study and practical test.
In the radio network planning, the radio propagation model presents the designer an
approximate propagation effect in the practical propagation environment to estimate
the space propagation loss. Therefore, the propagation model veracity determines
whether the cell planning is reasonable.
Radio propagation environments on the earth surface diversify a lot and propagation
models in different propagation environments are differentiated a lot, too. Therefore,
the propagation environment plays an important role in setting up a radio propagation
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Chapter 4 Scale Estimation Example
model. The propagation environment in a special region consists of the following
factors:
Terrains (mountains, hills, plain or water area)
Number, height, distribution and material features of buildings
Vegetation features
Weather conditions
Natural or man-made electromagnetic noise
Working frequency of system
Movement of mobile station
Propagation model is usually classified into outdoor propagation model and indoor
propagation model. The frequently-used models are shown in Table 2.1-1.
Table 2.1-1 Common Propagation Models
Model Name Frequency Range
Okumura-Hata 150 MHz1500 MHz macro cell prediction
Cost231-Hata 150 MHz2000 MHz macro cell prediction
Cost231 Walfish-Ikegami 800 MHz2000 MHz micro cell prediction
Keenan-Motley 900 MHz and 1800 MHz indoor environment prediction
General model 150 MHz2000 MHz macro cell prediction
The Cost231-Hata model and the General model used in the network planning software
Aircom are described below.
The Cost231-Hata model is applicable for 150 MHz2000 MHz macro cell prediction.
The urban path loss value can be worked out with the following approximate analysis
formula:
( ) mmbb CAhdhhfPathloss +++= lglg55.69.44log82.13lg9.333.46
Where, f refers to carrier, unit: MHz, applicable for 150 MHz2000 MHz;
bh refers to BS antenna height, unit: m, effective height 30 m200 m;
d refers to the distance from mobile station to antenna, unit: Km;
mAh refers to mobile station antenna height correction factor;
mC refers to city center correction factor, 3 dBm for large cities and 0 dBm for
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Chapter 4 Scale Estimation Example
Table 2.2-1
Parameter Symbol Procedure
Transmitter power (dBm) A
Transmitting antenna gain (dBi) B
Transmitting-end human body loss (dB) C
Transmitting-end feeder loss (dB) D
Transmitting-end effective radiation power (dBm) E E=A+B-C-D
Thermal noise density (dBm/Hz) F
Thermal noise (dBm)G G=F+10*LOG(3840
000)
Receiver noise coefficient (dB) H
Receiver noise (dBm) I I=G+H
Interference margin (dB) J
Service bit rate (kbps) K
Processing gain (dB) L L=10*LOG(3840/K)
Eb/No (dB) M
Receiver sensitivity (dBm) N N=I+J-L+M
Receiver antenna gain (dBi) O
Receiver feeder loss (dB) P
Receiving-end human body loss (dB) Q
Power control margin (dB) R
Soft handoff gain (dB) S
Shadow fading margin (dB) T
Penetration loss (dB) U
Maximum allowed path loss (dB)V V=E-N+O-P-Q-
R+S-T-U
2.2.1 Basic Link Budget Parameters
This section describes basic parameters of the UMTS link budget.
1 Transmitter power:
BS transmitting power:
The maximum transmitting power of BS is 43 dB. The power of the Dedicated
CHannel (DCH) accounts for 63% of the total power. Table 2.2-2 shows the
power distribution of all channels:
Table 2.2-2 Power Distribution of Channels
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Power (dBm) Power (W) Proportion
Max Tx Power: 43.0 20.0 100.00%Pilot Power: 33.0 2.0 10%
PCCPCH(BCH): 30.0 1.0 5%
SCCPCH(FACH): 30.0 1.0 5%
SCCPCH(PCH): 30.0 1.0 5%
AICH: 26.0 0.4 2%
PICH: 26.0 0.4 2%
P-SCH: 29.0 0.8 4%
S-SCH: 29.0 0.8 4%
DCH 41.0 12.6 63%
The BS transmitting power is a system parameter, different for individual services. It
shall be determined in accordance with service type and service coverage.
MS transmitting power:
During link budget, suppose the maximum transmitting power of UE data
service to +21 dBm and that of voice service to +21 dBm.
The BS transmitting power is a system parameter, different for individual services. It
shall be determined in accordance with service type and service coverage. In the
network optimization process, optimization engineers shall adjust power distribution to
all channels in accordance with network quality and service requirement to provide the
whole network with the optimal performance.
2 Human body loss
It is generally 3 dB for voice service and 0 dB for data service.
3 Antenna gain
It is generally 0 dB for the UE.
During link budget, suppose the directional antenna gain of the BS to 17 dBi and
the omni-directional receiving antenna gain to 11 dBi. In practice, different
antennas can be selected in accordance with different region types and coverage
requirements.
4 Feeder loss
It includes the loss of all feeders and connectors between the equipment top and
the antenna connector. For a feeder of 30-40 meters long, suppose the total
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services under different multi-path channel conditions.
Table 2.2-3 Uplink Eb/No Value
UL Eb/No
(dB)
Urban Area Suburb Area
Service type Static TU 3km/h TU 50km/h RA 3km/h RA 50km/h RA 120km/h
AMR 12.2k 4.1 4.2 6.4 4.1 6 6.4
CS 64K 2.5 2.87 4.5 2.8 5.2 5.2
PS 64K 0.9 1.6 4.5 2.7 5 4.9
Table 2.2-4 Downlink Eb/No Value
UL Eb/No
(dB)
Urban Area Suburb Area
Service type Static TU 3km/h TU 50km/h RA 3km/h RA 50km/h RA 120km/h
AMR 12.2k 7.2 7.7 7.1 8.5 8.4 7.2
CS 64K 7.1 7.7 6.7 8.8 8.2 7.1
PS 64K 6.4 7.4 6.2 8 7.8 6.4
PS 128K 5.7 6.4 5.5 7.3 7.3 5.7
PS 384K 6.4 8 5.9 7.7 7.7 6.4
6 Interference margin
Interference margin = )1lg(lg10 , where indicates the cell load.
The UMTS system is of self-interference, and its coverage is closed related to
the system capacity. At earlier network stages, little traffic results in low value of
interference margin. As the traffic load increases, the interference margin
becomes larger and the BS coverage shrinks. With regard to link budget,
therefore, it is necessary to select the maximum uplink load in accordance with
the estimated traffic increasing trend to ensure good coverage.
The value of interference margin in the uplink budget depends on the capacity
requirement in the network design. The interference margin is 3 dB when the
load is taken 50% from the dense urban area or a cell in the urban area, it is 2.2
dB when the load is taken 40% from the suburb area, and it is 1.5 dB when the
load is taken 30% from the rural area.
For the downlink, the relationship between load and interference still exists. The
interference margin shall be determined by emulation because it is hard to make
the theoretic calculation.
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Chapter 4 Scale Estimation Example
7 BS receiving sensitivity
BS receiving sensitivity indicates the minimum receiving level that the servicechannel requires to guarantee the decoding requirement with certain
communication qualities.
From the above deduction of Eb/No:
S(dBm) = Eb/No(dB) + N(dBm) - 10lg(W/R).
N indicates the total noise that the BS receives, that is, N = Noise + Nf + IM.
In the formula:
Noise indicates the thermal noise, caused by electronic thermal movements in
the conductor. It is generated between antenna and receiver as well as in the
damaged component coupler of level 1 of the receiver. In most of
communication systems, the power spectrum density is the same at the fixed
frequency point because the noise bandwidth is far larger than the system
bandwidth. From the DC to the frequency of 1012 Hz, therefore, the noise power
generated by the thermal noise source is the same per unit bandwidth. The
calculation formula of power is:
Noise = KTW (in the unit of W)
K indicates a Boltzmann constant, namely 1.38*10-23J/K.
T indicates the Kelvin temperature, namely 290 K.
W indicates the signal bandwidth, namely 3.84 M.
When dBm is taken as the calculation unit:
Noise = 10lg(KT) + 10lg(W).
10lg(KT) indicates the thermal noise density (in the unit of dBm/Hz).
Nf indicates the BS noise coefficient, defined as the ratio of input S/N to output
S/N. 3GPP does not have specific requirement for the equipment noise. It is
generally taken as 3 dB for link budget.
IM indicates the noise increasing caused by system load.
S(dBm) = Eb/No(dB) + 10lg(KTW) + Nf(dBm) + IM(dBm) - 10lg(W/R).
The formula of BS receiving sensitivity is:
Receiver Sensitivity = 10lg(KT) + Nf + 10lg(Eb/No) + 10lgR + IM.
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UMTS Scale Estimation
10lg(KT) indicates the thermal noise density, namely 174 dBm/Hz.
Nf indicates the BS noise coefficient, namely 3 dB.
IM indicates the interference margin.
8 Soft handoff gain
Here, soft handoff gain indicates the gain to overcome slow fading. When the
mobile equipment is located in the soft handoff region, multiple radio links of
soft handoff receive signals at the same time, which decreases the requirement
for the shadow fading margin. The soft handoff gain is generally taken as 3 dB
for link budget.
9 Power control margin (fast fading margin)
The UMTS system adopts the fast closed-loop power control of 1500 Hz. For a
low-speed mobile terminal, the fast closed-loop power control of 1500 Hz can
fight fast fading and guarantee the demodulation performance. Because of the
features of fast fading, however, the fast power control cannot compensate deep
fading when the low-speed mobile terminal is in deep fading. In this case, the
UE (Node B) needs to fight deep fading by increasing the average transmitting
power. When the UE is located at the edge of a cell, the fast power control
cannot compensate deep fading either. Therefore, it is necessary to reserve a
certain dynamic adjustment scope of transmitting power for the fast closed-loop
power control during link budget. The power control margin is generally taken
as 3 dB.
For a medium-speed or high-speed terminal (moving speed 50 km/hour), the
interleave in the channel code functions to fight fast fading while the fast closed-
loop power control has little function. So it is unnecessary to reserve the power
control margin.
10 Penetration loss
The penetration loss of buildings and vehicles is an important factor that
influences the radio coverage. The penetration loss is related to the specific
building/vehicle type and incident angle of radio wave. Suppose that the
penetration loss complies with lognormal distribution during link budget, and
use the average value of penetration loss and standard deviation to describe it. If
the radio coverage outside buildings is effective, it is enough to set the
penetration loss to 10 dB15 dB. To receive and initiate calls at the core part of a
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UMTS Scale Estimation
represented as:
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UMTS Scale Estimation
2.2.2 Unlink Budget
The parameters taken in the last section can be used to calculate the uplink budget
under different environments and coverage requirements. The following table shows
the calculation process:
Table 2.2-6 Uplink Budget
Parameter Symbol
Maximum transmitting power of UE A
UE antenna transmitting gain B
UE transmitting loss (human body loss) C
Actual maximum transmitting power of UE per
channelD= A +B C
Environment thermal noise power spectrum
densityE
Uplink noise figure F
Uplink receiving noise power spectrum density G = E +F
Uplink noise rise H
Total BS uplink receiving interference power
spectrum densityI = G + H
Uplink signal quality requirement Eb/No J
Uplink service rate K
Uplink receiving sensitivityL = I + 10lg(3.84*106) +(J 10lg (3.84*106/
k ))
BS antenna gain M
BS integrated loss N
Shadow fading margin P
Soft handoff gain Q
Power control margin R
Penetration loss S
Maximum loss T = D -L +M-N-P+Q-R-S
2.2.3 Uplink/Downlink Balance
Different from uplink budget, downlink budget makes all subscribers in the cell share
the BS power at the same time. The BS power distribution aims to make all subscriber
services connected with the BS in the cell match the corresponding service level.
Besides the number of subscribers in the cell, the downlink cell radius is also related to
the location and services of the subscriber.
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Chapter 4 Scale Estimation Example
The following table shows the parameters that cause the maximum allowed path loss
difference between uplink budget and downlink budget. The downlink is usually
limited by the capacity. When the load of the cell increases, the condition of limited
downlink may occur.
Table 2.2-7 Uplink/Downlink Parameter Comparison
Parameter Uplink Downlink
Receiver noise coefficient (dB) 2.2 7
Maximum transmitting power (dBm) 21Depending on the maximum single-
channel transmitting power
Receiving-end Eb/No (dB) (12.2 kbps) 4. 2 7.2
The balance between the uplink and downlink needs the help of planning software for
iterative calculation. The calculation includes the uplink coverage estimation and the
downlink power distribution. It shows link balance if the total power does not exceed
the maximum BS transmitting power. If the total power required by the downlink
exceeds the maximum BS transmitting power, it is necessary to reduce the coverage
area and conduct the downlink power distribution again until the total power is smaller
than or equal to the maximum BS transmitting power.
2.3 Coverage Scale Estimation
2.3.1 Calculation of BS Coverage Radius
After acquisition of the maximum allowed path loss between MS and BS via link
budget, it is easy to estimate the BS coverage radius by combining with the local radio
propagation model. In fact, the radio propagation model describes the relationship
between path propagation loss and coverage distance. The maximum allowed path loss
and radio propagation model that have been known can be used to conversely deduct
the maximum BS coverage radius. If the coverage radius of macro-cell BS is to be
estimated only without considering the topographic features, the macro-cell radius can
be calculated by using the Cost231-hata model.
10=R( ) ( )bmmb hAhChfPathloss lg55.69.44/lg82.13lg9.333.46 ++=
Pathloss indicates the maximum allowed path loss, acquired via link budget.
f indicates the carrier frequency, in the unit of MHz.
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Chapter 4 Scale Estimation Example
D
R
Area =23
8
9R , D = R
2
3
3 Six-sector directional BS
DR
Area =23
2
3R , D = R3
2.3.3 Scale Calculation
The planning region area divided by the single-BS coverage area is the number of BSs
that can cover the region with coverage requirements satisfied.
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3 UMTS Capacity Estimation
3.1 Capacity Estimation Flow
The capacity estimation is another important part of the scale estimation. The purpose
of capacity estimation is to estimate the approximate BS number needed by the
capacity according to the service model and service traffic demand of the network
planning. Similar with the link budget, the capacity estimation should be performed
from the uplink and downlink. For the UMTS system capacity, the interference is
limited in the uplink direction and the BS power is limited in the downlink direction. In
the 2 G CDMA network, the voice service is the main application service with
symmetrical uplink and downlink traffic, the capacity is limited in the uplink direction,
so the uplink capacity calculation is focused on in capacity estimation. However, in the
UMTS network, the data service proportion is obviously increased and the network
uplink and downlink traffic becomes asymmetric generally, and even the downlink
capacity may be limited. Therefore, the UMTS capacity estimation should be
performed from the uplink and downlink respectively. The following steps are involvedin capacity estimation:
1 Hybrid service intensity analysis. The UMTS system can provide multiple
services. The hybrid service intensity analysis makes the system capacity
consumed by various services equivalent to that consumed by a single service.
2 Uplink capacity estimation. Estimate the BS number that meets the service
demand based on the hybrid service intensity analysis.
3 Downlink capacity estimation. It is a verification process. The BS transmission
power formula is used to calculate the channel number that can be provided by
the current BS scale so as to verify whether this channel number can meet the
capacity requirement, and if it cannot, stations need be added.
3.2 Estimation Method of Hybrid Service Capacity
There are multiple services in the UMTS network, their service rates and required
Eb/No are diversified, the effects on the system load and consumed BS resources are
different, so the estimation for the cell capacity cannot adopt the method for estimating
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the cell capacity in a pure voice network. An idea of hybrid service capacity estimation
is to make equivalent among various services to make the system capacity consumed
by various services equivalent to that consumed by a single service. The Equivalent
Erlang, Post Erlang-B and Campbell methods in the hybrid service estimation are
introduced respectively as follows.
3.2.1 Equivalent Erlang Method
The fundamental principle of the Equivalent Erlang method is to make a service
equivalent to another service, calculate the total traffic (erl) of the equivalent services
and count the channel number needed by this traffic. We will give an example to
explain it as below.
Suppose services A and B are provided in the network, where,
service A: each connection occupies one channel and the total is 12 erl;
service B: each connection occupies 3 channels and the total is 6 erl.
If 1 erl service B is equivalent to 3 erl service A, the total traffic in the network will be
12+6*3=30 erl (service A). After querying Table erl-B, we know that altogether 39
channels are needed under 2% blocking rate.
If 3 erl service A is equivalent to 1 erl service B, the total traffic in the network will be
12/3+6=10 erl (service B). After querying Table erl-B, we know that altogether 17
service B channels (equivalent to 17*3=51 service A channels) are needed under 2%
blocking rate.
Upon the above analysis, we know that calculation result through the Equivalent
Erlang method is related to the equivalent mode adopted. The result through the former
equivalent mode is too small (39 channels) which is too optimistic, while the result
through the latter mode is too large (51 channels), which is too pessimistic, as shown inthe following figure:
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Chapter 4 Scale Estimation Example
Capacities meeting the
same GOS are different
Low speed
service
equivalent
2 Erl Low
speed service
1 Erl High
speed service
High speed service
equivalent The calculation
result is related
to the
equivalent
mode
3.2.2 Post Erlang-B Method
The fundamental principle of the Post Erlang-B method is to calculate the channel
number required by each service capacity respectively and add channels in an
equivalent manner to obtain the channel number required by the hybrid service
capacity. We will give an example to explain it as below.
Suppose services A and B are provided in the network, where,
service A: each connection occupies one channel and the total is 12 erl;
service B: each connection occupies 3 channels and the total is 6 erl.
After querying Table erl-B, we know that altogether 19 channels are needed to meet
service A traffic (12 erl) under 2% blocking rate.
After querying Table erl-B, we know that altogether 12 service B channels (equivalent
to 12*3=36 service A channels) are needed to meet service B traffic (6 erl) under 2%
blocking rate.
The two services need 19+36=55 channels totally.
Calculate the network capacity in a special case based on the Post Erlang-B method:
Suppose services A and B are the same kind, where,
service A: each connection occupies one channel and the total is 12 erl;
service B: each connection occupies 1 channels and the total is 6 erl.
After querying Table erl-B, we know that altogether 19 channels are needed to meet
service A traffic (12 erl) under 2% blocking rate.
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UMTS Scale Estimation
After querying Table erl-B, we know that altogether 12 channels are needed to meet the
service B traffic (6 erl) under 2% blocking rate.
Services A and B need 19+12=31 channels totally.
Because services A and B are the same kind, the total traffic is 12+6=18 erl. According
to the currently known method of capacity calculation in single service, after querying
Table erl-B, we know that 26 channels are needed to meet the traffic demand under 2%
blocking rate. This result is correct obviously.
Upon above analysis, we can see that the calculation result through the Post Erlang
method is too pessimistic (31>26). The reason is that the BS channels are shared
among services, however, the Post Erlang method factitiously separates the channels
used by the services, and thus, the BS channel resource utilization ratio is reduced, as
shown in the following figure:
Capacities meeting the same
GOS are different
1 ERL service A
1 ERL service B
1 ERL service A and
1 ERL service B
The
calculation
result is too
pessimistic
3.2.3 Campbell Method
The fundamental principle of the Campbell method is to make all services equivalent to
a virtual service based on certain rules, calculate the total traffic (erl) of this virtual
service, count the virtual channel number needed by this traffic, and convert the
number into the actual channel number that meets the network capacity.
The equivalent principle of the Campbell model:
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Chapter 4 Scale Estimation Example
==
iii
i
ii
aerl
aerlv
c
2
cfficOfferedTra
=
c
aCCapacity ii
)( =
Where, c indicates capacity factor.
v indicates hybrid service variance.
indicates hybrid service mean.
ia indicates the equivalent intensity of service i.
iC indicates the channel number needed by service i.
OfferedTraffic indicates traffic of the virtual service.
Capacity indicates the virtual channel number needed by the virtual traffic.
We will give an example to explain it as below.
Suppose services A and B are provided in the network, where,
service A: each connection occupies one channel and the total is 12 erl;
service B: each connection occupies 3 channels and the total is 6 erl.
Equivalent intensity of service A a1=1 and that of service B a2=3.
The hybrid service mean is =+==i
iiaerl 3036112
The hybrid service variance is =+==i
iiaerlv 663611222
The capacity factor is2.2
30
66===
vc
The virtual traffic is63.13
2.2
30===
cfficOfferedTra
After querying Table erl-B, we know that altogether 21 virtual channels are needed to
meet the virtual traffic under2% blocking rate.
According to formula (), under 2% blocking rate, the channel number needed by each
service is shown as follows:
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UMTS Scale Estimation
Service A:471)2.221(1 =+=C
Service B:
493)2.221(1 =+=C
From the above analysis, compared with results of the Equivalent Erlang and Post
Erlang-B methods, the result of the Campbell method is more credible, so it is a more
reasonable estimation method for hybrid service capacity at present. According to the
Campbell method, under the same requirement of the service level GOS, diversified
channel resources are needed by different services, or, under the same channel
resources, different services obtain diversified service levels. From this point of view,
the Campbell method is more reasonable. However, the Campbell method makes all
services uniformly equivalent as the circuit domain services and uses the Erlang-Bmodel for analysis and calculation. In fact, the features of the packet domain services
are completely different from those of the circuit domain services, and in addition, the
Erlang-B establishment conditions are not satisfied, so this equivalent method has
defects itself. A further research is needed for better hybrid service establishment
model and capacity analysis method.
In the Campbell method, the service equivalent intensity a can be calculated based on
channel number consumed by each kind of service or based on the interference
introduced from the air interface by each kind of service, shown as follows:
1amplitudefor1amplitudeforratebit
serviceforserviceforratebit
amplitudeRelative
0
0
N
E
N
E
b
b
=
If the reference service is the voice service, with its activity at the physical layer
considered, the above formula can be modified to:
for voicevfor voicefor voiceratebit
serviceforserviceforratebitamplitudeRelative
0
0
=
N
E
N
E
b
b
3.3 Uplink Capacity Estimation
3.3.1 Load Analysis for Uplink
In the UMTS system, all users adopt the same carrier and each signal becomes a noise
(interference) for others upon coding. Therefore, each signal is contained in the
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Chapter 4 Scale Estimation Example
UL
NR
=1
1
or)1(10)( 10 ULLOGdBNR =
This equation reflects the thermal noise lifting caused by user interference at the BS
receive end. 3 dB noise lifting corresponds to 50% load factors and 6 dB noise lifting
corresponds to 75% load factors. Generally, the network planning supposes that the
uplink load factor is 50%, in a single service, the channel number provided by each cell
can be calculated through formula (1), and then, the total BS number required by the
uplink capacity demand can be counted further. For the capacity estimation for hybrid
service, the Campbell algorithm should be combined to make the system resources
consumed by various services equivalent to those consumed by a single service. Then,
the channel number provided by each cell can be calculated through formula (1), and
the BS number required by the hybrid service capacity demand can be counted further.
The next section details the capacity estimation flow of the hybrid service.
The uplink noise lifting NR corresponds to the interference margin in the uplink
budget, that is, the coverage is related to the capacity. In planning, the network load
factor should be determined to get the noise lifting corresponding to this load. Then,
the BS radius meeting the uplink capacity requirement can be calculated further
through the link budget.
3.3.2 Uplink Capacity and Scale Estimation
The previous section describes the load factor of uplink, based on which, this section
describes how to estimate the BS quantity satisfying the composite traffic requirements
for uplink. Figure 3.3-1 shows the flow of estimating uplink capacity.
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UMTS Scale Estimation
Calculate equivalent
intensity of services
Calculate the variance,
average value and capacity
factor of the mixed service
Virtual traffic A of the
system
Calculate the quantity
of equivalent voice channels
in a cell
The quantity of virtual
channels in the sell
Virtual traffic B of the cell
Number
of cells
A/B
Error:
Reference source not found
Figure 3.3-1 Flow Chart of Estimating Uplink Capacity
1 Calculate the virtual composite traffic of the system.
Because various services have different effects on system load, such an effect
can be equivalent to the effect of multiple voice channels on system load. The
calculation formula is as follows:
amplitude service= (Rservice x Eb/Noservice x vservice)/ (Rvoice x Eb/Novoice
x voice)
Where, R represents service rate.
Eb/No represents quality factor of the service.
v represents the activation factor of the service at the physical layer
According to the Campell theory, the virtual composite traffic of the system can
be calculated.
2 Calculate the quantity N of equivalent voice channels provided by a cell.
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Chapter 4 Scale Estimation Example
the location of users. For the average value of cell load factors, adopt its similar
average value in the whole cell, that is:
=
+=
N
j j
jjDL i
RW
NoEbv
1
])1[(/
)/(
Where, represents the average quadrature factor in a cell. Generally, it is 60% for
the multipath channel and 90% for the non-multipath channel. i represents the
average ratio of the BS power received by the user from other cell to that from this cell.
Generally, it is 55% for the omni antenna macro cell and 65% for the three-sector
antenna macro cell.
During the analysis of downlink capacity, estimation of BS transmitting power is the
most important. The estimated BS transmitting power is average power not peak power
at the cell boundary, because the transmitting power distributed by the BS for each user
is determined by the average loss from the BS to the mobile station and the sensitivity
of the mobile station. On the actual network, users are distributed randomly in a cell,
not at the cell boundary, therefore, the average path loss value, not the maximum path
loss value estimated for the link, should be adopted when BS transmitting power is
calculated. In a macro cell, the difference between the maximum path loss and the
average path loss is usually 6 dB.
The total BS transmitting power can be expressed by the following formula:
DL
N
j j
j
jrfRW
NoEbvLWN
TxPBS
==
1
/
)/(
_1
Where, rfN
represents the noise power spectrum density on the front of the mobile
station receiver, and it can be calculated by the following formula:
)290(sup0.174 KposeTNFdBmNFKTNrf
=+=+=Where, NF
represents the noise coefficient of the mobile station receiver with the typical value of 5
dB to 9 dB.
L represents the average path loss, which is evaluated by subtracting 6 dBm from the
maximum path loss.
vj represents activation factor of the user j.
Rj represents bit rate of the user j.
In the case of a single service, evaluate the channel quantity provided by every cell
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UMTS Scale Estimation
under the maximum allowed transmitting power according to the formula (2) and
further evaluate the total number of BSs satisfying downlink capacity requirements.
In fact, the analysis of uplink and downlink link performances is a hard process.
Because the performance of downlink depends on many basic elements very much, its
analysis cannot be streamlined like the analysis of uplink. The Eb/No value range of
downlink is a parameter changing greatly with moving speed and multipath condition.
In addition, the mobile station receiver does not use antenna diversity. The reason why
the required Eb/No value changes with the mobile station is that at least two paths
cannot be ensured unless it is clearly known that the mobile station is in soft handoff or
softer handoff statuses. Such a change, randomicity of mobile station location and
interference level from the surrounding cell make the analysis of downlink
performance complicated. In designing, a very conservative conclusion can be gotten
in the case the worst condition is considered. Generally, estimate capacity after
analyzing the channel quantity required by uplink capacity, and observe whether the
downlink can support the mobile station to work in the designated coverage area and
its channel quantity reaches the channel quantity generated by the uplink.
3.4.2 Downlink Capacity and Scale Estimation
Downlink estimation is a verification process. The process of downlink capacity and
scale estimation is as follows: First calculate the quantity of equivalent voice channels
to be provided by this cell in the current service model, and then calculate the quantity
of equivalent voice channels availably provided by the cell according to the downlink
power calculation formula, and subsequently compare these two results. If the quantity
to be provided by the cell is less than that availably provided by the cell, it indicates
that downlink power is enough and the current scale satisfies system capacity
requirements. If the former is larger than the latter, it indicates that downlink capacity
is limited. To make downlink power enough, add some BSs.
1 Calculate the quantity of equivalent voice channels to be provided by every cell.
Under the precondition of known reverse capacity and scale, you can evaluate
the traffic of various services in every cell under such a scale. Then, according to
the equivalence of voice channels, you can evaluate the quantity of equivalent
voice channels to be provided by every cell. This quantity can be calculated by
following several steps below
1) Calculate the average traffic of various services in every cell according to the BS
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Chapter 4 Scale Estimation Example
quantity of uplink and total traffic of downlink.
Average traffic of various services in a cell=
3ntityStationQuaUplinkBase
inkTrafficTotalDownl
Where, the BS quantity is the larger value between estimated uplink coverage
and estimated capacity result.
2) According to the Campell theory, calculate the virtual Erlang traffic in every cell.
The calculation method in this step is the same as that of uplink.
3) Look up Table Erl B according to the virtual Erlang traffic in every cell
evaluated in step 2, and calculate the quantity of virtual channels in every cell.
4) According to the quantity of virtual channels evaluated in step 3 and the
following formula
c
aCCapacity ii
)( =
you can evaluate the quantity of equivalent voice channels to be provided by
every cell.
2 Calculate the quantity of equivalent voice channels availably provided by thecell.
According to the forward power formula
])1[(/
)/(*1
/
)/(***
1
1
jj
N
j j
jj
N
j j
jjN
RW
NoEbv
RW
NoEbvLP
P
+
=
=
=
Where, PN represents the noise power spectrum density on the front of the
mobile station receiver, and it can be calculated by the following formula:
)290(sup0.174 KposeTNFdBmNFKTPN =+=+= ,
NF represents the noise coefficient of the mobile station receiver with the typical
value of 5 dB to 9 dB.
L represents the average path loss, which is evaluated by subtracting 6 dBm
from the maximum path loss. j represents the average quadrature factor.
Generally, it is 0.6 for the multipath channel and 0.9 for the non-multipath
channel.
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Input:system load requirment and
coverage requirement
Uplink coverage
estimation
Quantity of BSs
satisfying uplink
coverage
Downlink coverage
estimation
Quantity of BSs
satisfying downlink
coverage
Compare the results
and evaluate the
larger one
Uplink capacity
estimation
Quantity of BSs
satisfying uplink
capacity
End
Based on traffic type Based on power
Quantity A of
channels to be
provided by every cell
on the downlink
Quantity B of
channels availably
provided by every
cell on the downlink
AddBSs
No
Yse
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Chapter 4 Scale Estimation Example
loss (dB) + BS receiving antenna gain (dBi) + soft handoff gain (dB) building
or car body penetration loss (dB) slow fading margin (dB) power control
margin (dB) interference margin (dB) BS receiving sensitivity (dBm)
Values in the following table can be obtained according to parameters in Section
4.2.1:
Voice CS64 PS64 PS64/128 PS64/384
Transmitting
end
Maximum transmitting
power (dBm)21 21 21 21 21
Antenna gain (dBi) 0 0 0 0 0
Human body loss (dB) 2 0 0 0 0
Effective transmitting power 19 21 21 21 21
Receiving
end
Thermal noise power
spectrum density (dBm/HZ)-174 -174 -174 -174 -174
Thermal noise power (dBm) -108 -108 -108 -108 -108
Receiver noise coefficient
(dB)2.2 2.2 2.2 2.2 2.2
Receiver noise (dBm) -105 -105 -105 -105 -105
Interference margin (dB) 3 3 3 3 3
Bit rate (kbit) 12.2 64 64 64 64
Processing gain (dB) 24.98 17.78 17.78 17.78 17.78
Receiving Eb/No (dB) 4.2 2.87 1.6 1.6 1.6
Receiver sensitivity -124 -118 -119 -119 -119
Antenna gain (dBi) 17 17 17 17 17
Line loss 4 4 4 4 4
Others
Power control margin 3 3 3 3 3
Soft handoff gain 3 3 3 3 3
Shadow fading margin 10.3 10.3 10.3 10.3 10.3
Penetration loss 20 20 20 20 20
Maximum allowed path loss 125.34
121.4
7
122.7
4 122.74 122.74
2 Calculate the cell coverage radius according to a specific propagation model
Here, we adopt a universal propagation model of Aircom to calculate:
Path loss = k1 + k2log(d) + k3Hms + k4log(Hms) + k5log(Heff) +
k6log(Heff)log(d) + k7(diffraction loss) + clutter loss
Use parameters in the following table
k1 152.4
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UMTS Scale Estimation
k2 44.6
k5 -13.82
k6 -6.55
Heff 30
K1 and K2 parameters have greater effect on the budget result. While, K3 and K4 have
less effect, so their values are 0.
Obtain the BS coverage radius after adopting the maximum path loss:
Voice CS64 PS64 PS64/128 PS64/384
Radius (Km) 0.65 0.5 0.54 0.54 0.54
3 Calculate the number of BSs required by uplink
From the result in the previous step, we see that the uplink coverage is limited
by the CS64kps service, so the BS radius satisfying successive coverage of
CS64kps is adopted when the number of BSs is calculated.
If the coverage area S of the three-sector BS =23
8
9R = 1.95 0.52= 0.488
Km2
The number of BSs satisfying uplink coverage requirement is 40.8/0.488 = 84
For downlink budget, because all users in the cell share BS power simultaneously, the
cell radius on the downlink is not only related to the number of users in the cell, but
also related to user location and services used by users. The balance between the uplink
and downlink should be calculated iteratively with the planning software. First predict
coverage area for the uplink, and then allocate power for the downlink. If the total
power does not exceed the maximum transmitting power of the BS, links are balanced.
If the total power required by the downlink exceeds the maximum transmitting power
of the BS, coverage area should be reduced and power should be re-allocated to the
downlink until the total power is less than or equal to the maximum transmitting power.
4.2.3 Uplink Capacity Estimation
1 Calculate the virtual composite traffic of the system.
1) Equivalent service intensity of each service
According to the formula
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Chapter 4 Scale Estimation Example
1amplitudefor1amplitudeforratebit
serviceforserviceforratebit
amplitudeRelative
0
0
NE
N
E
b
b
=
obtain
voice: 1
CS64: 64 x 1 x 100.287/12.2 x 0.67 x 100.42 = 5.76
PS64/64: 64 x 1 x 100.16/12.2 x 0.67 x 100.42 = 4.3
PS64/128: 64 x 1 x 100.16/12.2 x 0.67 x 100.42 = 4.3
PS64/384: 64 x 1 x 100.16/12.2 x 0.67 x 100.42 = 4.3
2) Calculate the mean of composite traffic
=++++==i
iiaerlmean 1.57663.423.453.410067.540013000
3) Calculate the variance of composite traffic
=++++==i
iiaerliance 1823.423.453.410067.540013000var2222
4) Calculate the capacity factor
capacity factor= variance/mean = 3.17
5) Calculate the virtual composite traffic of the system
composite traffic = mean/capacity factor= 5766.1/3.17 = 1818.96 (Erl)
2 Calculate the quantity N of equivalent voice channels availably provided by the
cell
According to the uplink load formula
+
+=
N
j
o
bj
N
EvR
Wf
1*
1*1
1*)1(
Where, %50= and 65.0=f
get the quantity of equivalent voice channels N = 54
3 Calculate the quantity of virtual channels in every cell
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UMTS Scale Estimation
According to
c
aCCapacity
ii )(
=
get the quantity of virtual channels in the cell = (54 1)/3.17 = 16
4 Look up Table Erl B according to the quantity of virtual channels evaluated in
step 3, and get the quantity of virtual traffic in every cell, that is 9.83 Erl.
5 Calculate the number of cells
Number of cells = Virtual traffic of the system/virtual traffic of every cell =
1818.96/9.83 = 186
The number of required three-sector BSs = 186/3 = 62
After the above calculation, we know that 84 stations are required for uplink
coverage. The evaluated number of stations is less than 84, so it meets both
coverage and capacity requirements.
4.2.4 Downlink Capacity Estimation
Downlink capacity estimation is a verification process. With the downlink power
formula, verify whether the number of BSs evaluated from uplink coverage and
capacity budget meets the power requirement. Add BSs until downlink power meets
the requirement.
1 Calculate the quantity of equivalent voice channels to be provided by every cell.
1) Calculate the average traffic of various services in each cell according to the BS
quantity of uplink and total traffic.
Average traffic of various services in every cell is:
Voice: 3000/84/3 = 11.9 Erl
CS64: 400/84 = 1.59 Erl
PS64/64: 100/84 = 0.4 Erl
PS64/128: 35/84 = 0.14 Erl
PS64/384: 20/84 = 0.079 Erl
2) Calculate the virtual Erlang traffic in every cell.
Equivalent service intensity of each service on the downlink
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Chapter 4 Scale Estimation Example
Voice: 1
CS64: 64 x 1 x 10
0.77
/12.2 x 0.67 x 10
0.77
= 7.8
PS64/64: 64 x 1 x 100.74/12.2 x 0.67 x 100.77 = 7.3
PS64/128: 144 x 1 x 100.64/12.2 x 0.67 x 100.77 = 13.1
PS64/384: 144 x 1 x 100.8/12.2 x 0.67 x 100.77 = 50
The mean of composite traffic is
Mean = 11.9 1 + 1.59 7.8 + 0.4 7.3 + 0.14 13.1 + 0.079 50 =
33.04
The variance of composite traffic is
Variance = 11.9 1 + 1.59 7.82 + 0.4 7.32 + 0.14 13.12 + 0.079
502 = 355.19
Capacity factor = variance/mean = 355.19/33.04 = 10.75
Virtual traffic of the cell
composite traffic = mean/capacity factor = 33.04/10.75 = 3.07 (Erl)
3) Check Table Erl B and obtain that the quantity of virtual channels required by
every cell is 7
4) Calculate the quantity of equivalent voice channels required by each cell.
According to the formula
c
aCCapacity ii
)( =
evaluate the quantity of equivalent voice channels is: 7 10.75 + 1 = 76.
2 Calculate the quantity of equivalent voice channels actually provided by every
cell.
According to the downlink power formula
])1[(/
)/(*1
/
)/(***
1
1
jj
N
j j
jj
N
j j
jjN
RW
NoEbv
RW
NoEbvLP
P
+
=
=
=
Where, P represents the maximum service transmitting power, which is 13 W.
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UMTS Scale Estimation
PN represents the noise power spectrum density on the front of the mobile station
receiver, and its value is -169 dBm.
L represents average path loss, which is evaluated by subtracting 6 dBm from
the maximum path loss.
j represents average quadrature factor, which is 0.6 for the multipath channel.
j represents interference factor from an adjacent cell. It is 0.65 for the three-
sector antenna macro cell.
Obtain that the quantity of equivalent voice channels actually provided by every
cell is 71.
3 Comparison
Through downlink budget, the quantity of channels required by every cell is 76
when there are 84 BSs in a network. However, according to the power formula,
the quantity of channels actually provided by every cell under the current scale
is 75. That is, downlink power cannot meet the requirement. To meet such a
requirement, add some BSs.
Obtain the following table through successive iterative calculation:
BS Quantity Required Channel Quantity Provided Channel Quantity
83 76 71
84 76 71
85 76 71
86 76 71
87 76 71
88 65 71
If there are 88 BSs, the uplink and downlink coverage capacity requirement can be
met.
In the case, the BS coverage radius is 488.095.1/88/8.40 = Km