Rf planning umts with atoll1

3 Radio planning with Atoll.
The purpose of this paper is to provide the plan and design a UMTS mobile
communications network to give coverage to the town of Seville.

We used the software tool Atoll radio planning and simulation, developed by the
company Forsk. With the help of this tool will determine the design parameters of
the network and relevant simulations will be performed to verify that the
objectives have been achieved quality.

3.1 About Atoll.
Today is no longer regarded the implementation manual or any programming of
all necessary calculations for radio planning as described in Chapter 2 of this
document.In a professional environment they are always planning tools, except
in very simplified.

ATOLL is a radio planning environment based on windows, easy to use, supports
wireless carriers throughout the lifetime of the network. From initial design to the
optimization phase and during the various extensions [2].

More than an engineering tool, ATOLL is a technical information system open,
scalable and flexible that it can be easily integrated into other
telecommunications systems, increasing productivity and reducing development
time.

ATOLL allows a wide variety of deployment scenarios. From a single server, up
configurations using parallel and distributed computing.

The main features of Atoll are:

· Advanced properties in network design: a tool for calculating
propagation of high-performance, multi-network support and hierarchical
traffic shaping, and automatic frequency planning and network
optimization codes.It supports GSM / TDMA, GPRS, EDGE, IS-95 CDMA,
W-CDMA / UMTS, CDMA 2000. Allows network planning technologies (GSM
/ UMTS, GSM / GPRS, CDMA/CDMA2000 ...).

· Open and flexible architecture: it supports multi-user environments
through architecture innovative databases that can share data, manage
the integrity of the data and easy integration with other
telecommunications systems.Allows the integration of proprietary modules
(AFP propagation models) through a set of programming interfaces (APIs).
It also allows the integration of macros.

· Parallel and distributed computations: ATOLL allows the distribution of
computation among multiple workstations and supports parallel

computations in multiprocessor servers, dramatically reducing the time of
simulation and prediction, taking full advantage of hardware.

· Art GIS, geographical data ATOLL supports multi-format and multi-
resolution and integration with GIS tools. Allows loading complex
databases and display geographic information interactively with multiple
layers, including engineering studies and prediction.Includes raster and
vector editor.

ATOLL is composed of a core module that can add modules such as UMTS
module (allowing projects CDMA / CDMA 2000) specifically for the analysis and
network planning W-CDMA/UMTS, the Measures module allows you to import
and manage specific measures CW or test data mobile routes, Module Automatic
Frequency Planning for the optimization of frequency plans GSM / TDMA and
Microwave Planning module. This module allows users to plan and analyze
microwave links.

The advantages for our purposes is obtained from this application are based
mainly on three aspects:

· Allows us to have databases of high resolution topographic and access
to them for terrain profiles and data to be used for calculations of
propagation.

· We can use methods of predicting the radio propagation more
elaborate and much more laborious calculations, which would be
impossible to perform manually.

· It also allows us to have databases with existing or planned
equipment.This makes it easier to compare different potential sites,
antenna height, power equipment, etc. We have therefore a much higher
range of possibilities and simplifies the process of network optimization.

Atoll is based on digital terrain maps.The program can perform calculations on
information extracted from these maps and databases that the engineer
generates information on the network. Maps, databases and

the results of these calculations are grouped into program files called "projects."

3.2 Traffic modeling.
The first objective is to model in some way the traffic generated by the user
population of the city of Seville [1] [2], [7].

We create a UMTS-type project (File | New) by selecting the template UMTS
HSDPA. The first is to import the maps for the city of Sevilla (File | Import),
select the index files of different folders that are grouped charts: Heights (map
type altitudes) Clutter (clutter type classes) , Ortho (image) and Vector (lineare).

The resolution of the maps that we use is 25 m, which in principle is sufficient
because the target area topography is fairly uniform and regular.

The map is a map of heights and contains altimetry and topographic relief of the
work area.The information contained in this map is used for the calculation of
coverage and spread. Altimetry map we use for our study is shown in Figure 10.

Figure 10: Map of altimetry Seville.

The clutter map is the map of land uses and in it, each type corresponds to a
color field.The clutter that we will use is shown in Figure 11.

Figure 11: Map of land use (clutter classes) in Seville.

As shown in the legend, in the case of Sevilla have 12 types of zones: the open
(OPEN), water (INLAND_WATER), residential (RESIDENTIAL), urban average
(MEAN_URBAN) urban sprawl (DENSE_URBAN), buildings (BUILDINGS), village
(VILLAGE), industrial (INDUSTRIAL), opened in town (OPEN_IN_URBAN), forest
(FOREST), parks (PARKS) and dispersed urban (SCATTERED_URBAN).

Ortho map is simply an aerial photo of the city. Is shown in Figure 12:

Figure 12: orthophoto map type.

Finally, the map identifies Vectors roads, rivers, railway lines, etc. Vectors map
we will use is shown in Figure 13.

Figure 13: Map type Vectors of the city.

The layers of different maps overlap each other. Order can be changed by
moving the mouse for almost all visible simultaneously. We will arrange to
appreciate all the time clutter maps, orthophoto and vectors. The result of this
overlap map shown in Figure 14:

Figure 14: Overlay of all city maps.

To model the traffic generated by the city are going to define user profiles, and
each one will assign a number of UMTS services with certain parameters that
indicate the user traffic generated by each service.We are only going to include
in the model of services: voice, MMS, Internet access and video conferencing. It
was not deemed necessary to modify the default values for these services Atoll,
as are typical for UMTS planning in cities.

The service features are included in Table 1.

Service Name Voice MMS Internet Video
conference
R99 Bearer LCD12 UDD64 UDD384 LCD64
Service Type Circuit mode Packet mode Packet Circuit
mode Mode
Soft handoff allowed Yes No No Yes
Priority 2 0 0 1
Factor activity in the UL 0,4 0,75 0,75 1
Factor activity in the DL 0,4 0,75 0,75 1
Average date rate in the UL 12.2 kbps 64 kbps 64 kbps 64 kbps
Average date rate on the DL 12.2 kbps 64 kbps 384 kbps 64 kbps
Lost by the body 3 dB 0 dB 0 dB 0 dB

Table 1: Characteristics of UMTS services.

These services can be obtained from different types of terminals. We will
consider two different types of terminals: mobile phone and PDA. The terminal
characteristics are those that have default Atoll, and are listed in Table 2.

Terminal Minimum power Maximum Noise Active set size
Type (dBm) power (dBm) Figure (dB)
Telephone -50 21 8 3
PDA -50 25. 7 1

Table 2: Characteristics of UMTS terminals.

User profiles with their services and associated terminal types listed in Tables 3-
8.These values are set with reference to other studies dimensioning of UMTS
networks to which access has been [1], [4].

· Adolescent (10-20 years):

Service Terminal Calls per Call duration Volume of data Data volume in
Type hour (sec) in the UL DL (Kbytes)
(Kbytes)

Voice Telephone 0,25 250 - -
Mobile 0 - 150 150
MMS Telephone
Mobile 0 - 200 6.000
Access Telephone
The Internet Mobile 0,005 125 - -
Video Telephone
Conference Mobile

Table 3: Traffic generated by the user Adolescents.

· Young (20-30 years).

Type hour (Sec) in the UL DL
(Kbytes) (Kbytes)
Voice Mobile 0,25 275 - -
Phone
MMS Mobile 0 - 200 200
Phone

Internet Mobile 0 - 300 7.000
Access Phone
Video Mobile 0,005 150 - -
Conference Phone

Table 4: Traffic generated by young users.

· Middle-aged (30-50 years).

(Kbytes)
Phone
MMS Mobile 0,005 - 100% 100%
Phone
Internet Mobile 0 - 200 6.000
Access Phone
Video Mobile 0,025 100% - -
Conference Phone

Table 5: Traffic generated by the user Median age.

· Middle age (50-65 years).

Service Terminal Calls per Call duration Volume data in Data volume in
Type hour (sec) the UL (Kbytes) DL (Kbytes)
` Mobile 0 120 - -
Phone
MMS Mobile 0,001 - 100% 100%
Phone
Internet Mobile 0,0025 - 200 6.000
Access Phone
Conference Phone

Table 6: Traffic generated by the user age.

· Elderly (+65 years).

(Kbytes)

Phone
MMS Mobile 0,0005 - 100% 100%
Phone
Internet Mobile 0,00125 - 100% 3.000
Access Phone
Conference Phone

Table 7: Traffic generated by the user person further.

· Business Person.
Service Terminal Calls per Call duration Volume of Data volume in
Type hour (sec) data in the UL DL (Kbytes)
(Kbytes)
Phone
MMS Mobile 0 - 200 200
Phone
Internet Mobile 0,25 - 500 10.000
Access Phone
Video Mobile 0 200 - -
Conference Phone
Voice PDA 0,5 350 - -
MMS PDA 0 - 200 200
Internet PDA 0,25 - 500 10.000
Access
Video PDA 0 200 - -
Conference

Table 8: Traffic generated by the user person business.

The next step for modeling the traffic generated by the city is to define a series
of "environments" type, each of which will assign a population density of users
associated with their mobility.

Later on the map available generate an environment map, which is only noted on
the map to that type of environment is for each pixel of the map.

The types of mobility (Table 9) are those set by default Atoll, as they are
considered typical values of UMTS in cities.

Average speed mobility rate Eo / Io Threshold
(Km / h) (dB) HG-SCCH Ec / Nt (dB)

Pedestrian 3 -14 -9
50 Km / h 50 -14 -9
90 Km / h 90 -14 -9

Table 9: Types of mobility

And finally we define the environments. Each environment is characterized by a
series of pairs "user profile" mobility "and a population density associated with
each of them. Environments are defined as set out in Table 10. The densities
were chosen by reference to demographic studies which have been accessed [7],
[11].

Type of environment Population density (hab/Km2) Density of subscribers
(ab/Km2)
Open 400 100
Urban 20000 4000
Dense urban 30000 6000
Residential 5000 1000
Industrial 10000 2000
Great Buildings 40000 8000

Table 10: Types of environments from the city of Seville.

Is to size the network assuming that pays a 20% of the inhabitants of the city.
Percentage is quite optimistic, which may take a long time even achieved or not
achieved, but ensures that the network does not saturate easily.

Then we estimated the density associated with each environment for each user
group, again taking as reference demographic studies of the National Institute of
Statistics [11].The results are shown in Table 11.

Type Teenage Young Medium older other Business
environment
Open 8 21 39 21 9 2
Urban 425 eight 1.200 eight 700 75
hundred. hundred.
Urban dense eight 1200 1800 1200 900 100%
hundred.
Residential 150 200 275 200 150 25.
Manufacturing 75 400 1000 400 75 50
Buildings 1.050 1.600 2.400 1.600 1.200 150

Table 11: Densities and types of users associated with Sevilla environments.

Finally, we must define what percentage of each user densities associated with
the environment presented by each type of mobility.

For this open environment is shown in Table 12:
User type Mobility Pedestrian 50 Km/h 90 km/h
Teen 2 3 3
Young 7 7 7
Median age 13 13 13
older 7 7 7
other 3 3 3
Business 0 1 1

Table 12: Types of users and mobility associated with the open environment

Table 13 shows what we have estimated for an urban environment:
User type/Mobility Pedestrian 50Km/h 90km/h
Teen 375 25 25
Young 700 50 50
Medium 1000 100 100
Older 700 50 50
Other 40 40 620
Business 50 13 12

Table 13: Types of users and mobility associated with the urban environment.

For a dense urban environment has been a percentage of subscribers in much
lower vehicle, being mainly the old town area, which is intended to restrict
vehicle access in the near future.Densities associated with the binomial type of
user-mobility are shown in Table 14:

User Type /Mobility Pedestrian 50Km/h 90km/h
Teen 780 10 10
Young 1170 15 15
Median 1760 20 20
Older 1170 15 15
Other 880 10 10
Business 95 3 2

Table 14: Types of users and mobility associated with dense urban environment.

For the residential environment are also considered low densities for cases 50 km
/ h and 90 km / h, as they are considered low-traffic areas.The associated
densities are given in Table 15:
user type /Mobility Pedestrian 50 Km / h 90 km / h
Teen 140 5 5
Young 180 10 10
Middle 250 13 12
Older 180 10 10
Other 140 5 5
Business 20 3 2

Table 15: Types of people associated with residential mobility.

All these parameters can be completed in the UMTS parameters folder in the
data tab of the browser window.You can delete and add entries for folders:
Environments, User Profiles, Terminals, Mobility Types, Services and within each
entry you can change various settings for each input.

The next step is to create a traffic map. To do this, on a digital map of Seville we
will define a number of areas and each of them we assign one type of
environment (environment map or raster).

The map of environments we will generate a similarity of map of land uses which
have the city of Seville.The land use map or clutter classes each zone shows a
different color.

To create a traffic map Atoll Geo select the tab of the browser window, create a
new road map, scenario-based or raster, and we mark on the map kind of
environment that belongs to each zone. The result is shown in Figure 15

Open
Residential
Urban
Dense urban
High buildings
Industrial estates
Parks

Figure 15: Map of surroundings of the city of Seville.

3.3 Propagation model.
It will use the propagation model Cost-Hata. Hata formula is specially designed
for applications in mobile communications in any environment (COST231 is only
for urban environments) and on the other hand, the Okumura-Hata method is
only for frequencies below 1500 MHz Cost-Hata (or Hata, COST231) is a variation
of the Hata formula for systems operating at 1,800 MHz and 2,000 MHz [4], as is
the case at hand.

Propagation Models folder in the Modules tab of the browser window assign a
different formula for each type of clutter map area.

The allocation formula is that of Table 16:
Zone Type Cost-Hata formula
Field (OPEN) Rural (open area)
Water (INLAND_WATER) Rural (open area)
Residential (RESIDENTIAL) medium-sized city and suburban
Urban average (MEAN_URBAN) Metropolitan Center
Urban sprawl (DENSE_URBAN) Metropolitan Center
Buildings (BUILDINGS) Metropolitan Center
Pueblo (VILLAGE) medium-sized city and suburban
Industrial (INDUSTRIAL) Metropolitan Center

Open city (OPEN_IN_URBAN) Rural (almost open)
Forest (FOREST) Rural (almost open)
Parks (PARKS) Rural (almost open)
Dispersed urban (SCATTERED_URBAN) medium-sized city and suburban

Table 16: Allocation of Cost-Hata formulas to different types of environment.

The terms set out in the Atoll database for this method are:

· Metropolitan Center:

Lu = 49.3 + 33.9 log f - 13.82 log Hb + (44.9 to 6.55 log Hb) gives log (M r) =
(1.1 log f - 0.7) H r - (1.56 log f - 0.8)

Total = Lu - a (H r)

· Medium-sized city and suburban:

Lu logf = 46.3 + 33.9 - 13.82 logHb + (44.9 to 6.55 logHb) logd to (H r) = (1.1
logf - 0.7) H r - (1.56 logf - 0.8)

Total = Lu - a (H r)

· Rural (almost open):

logf - 0.7) H r - (1.56 logf - 0.8)

Total = Lu - a (H r) - 4.78 log 2 logf f + 18.33 - 35.94

· Rural (open area):

logf - 0.7) H r - (1.56 logf - 0.8)

Total = Lu - a (H r) - 4.78 log 2 logf f + 18.33 - 40.94

Finally, define Predictions folder as the default method of propagation Cost-Hata
with a resolution according to the resolution of the maps (25 m) and a terminal
height of 1.5 m. This value for the height of the terminal is a typical value used
for such studies and that implies that all active users are at ground level, ie in the
worst case (further away from the base station) .

3.4 Network equipment.
We will introduce information about the technical characteristics of the computer
in your network. These specifications pertain to the equipment described in
Chapter 4. We will try to model with these teams Atoll as realistic as possible so
that the results of the simulations are close to reality as possible.

3.4.1 Antennas.

The description of the antennas are going to use is found in paragraph

4.1.4.1 of Chapter 4.

Atoll contains a database with some antennas defined by default. We will create
a new antenna from scratch, which is as close as possible to our actual antenna.

To do this we create a new folder antenna Antennas Data tab of the browser
window.The characteristics of the antenna set are shown in Table 17. The
patterns of horizontal and vertical filing of the antenna are shown in Figures 16
and 17 respectively.

Name UD01P_D18BB
Manufacturer Kathrein
Gain 18 dBi
Power Tilt 4º
Beamwidth 63 º
maximum frequency 2,170 MHz
Minimum frequency 1920 MHz

Table 17: Properties of the antenna Atoll.

Figure 16: horizontal radiation pattern of the antenna UD01P_D18BB in Atoll.

As described in Chapter 4, the antenna has a beamwidth of 63 ° in the horizontal
plane (3 dB drop at 63 º) the attenuation is 10 dB at 120 º and the attenuation
of the lateral lobes (90 º) is 20 dB (see Figure 16).

Figure 17: Radiation pattern of the antenna vertical UD01P_D18BB in Atoll.

On the vertical beamwidth is 6.5 degrees and has introduced a power tilt 4 º (see
Figure 17).

3.4.2 Base Station.

The base station model chosen is the IN-60 from Nortel, whose main
characteristics will be found in Chapter 4.

The characteristics of the base station is included in Atoll in the corresponding
deployment template. In the radio toolbar, select manage staff, make a copy of
an old template and fill it with the specifications of our base station. The selected
parameters are those of Table 18:

Number of sectors 3
Antenna model
UD01P_D18B
B 2 Frequency Band ,170 MHz
Height 30 m

base station Noise figure 5 dB
Pilot Channel Power 33 dBm
SCH Power 21 dBm
Power other CCH 30 dBm
AS Threshold 5 dB
Maximum power 43 dBm
Maximum load on the DL (peak) 75%
The maximum load on the UL 50%
Maximum date rate per user at 1,000 Kbps
DL
Maximum date rate per user at 1,000 Kbps
UL
Maximum number of CEs in the DL channel 256
Maximum number of CEs in the UL 256

Table 18: Table of characteristics of the base station Atoll.

3.5 Deployment planning.
Once we have modeled the traffic of the city of Seville can begin to locate the
sites and have run simulations to achieve quality objectives.

In principle we will look quality objectives in Table 19:
Service Probability of service denial or delay
Voice 2%
MMS 5%
Internet access 10%
Video Conference 2%

Table 19: Quality objectives.

We set a target of availability of Voice and Video Conferencing as telephone
networks are usually designed for a 2% chance of rejection. We have set a
quality goal of 5% for MMS because it has a lower priority than those of the
services operating in circuit mode (it is considered less critical) and not a delay-
sensitive service. Internet access service is the lowest priority and is also the
most penalized other services, it is likely therefore to be the most likely to be
rejected by the network and we may be difficult to obtain high levels of
availability .

We will begin the deployment of sites using the available templates. As most of
the target area is urban type, we will use the urban insole to begin the
deployment and conduct the first simulations and assessments.

The template urban uses hexagonal cells, with 550 m cell radius and a single
carrier.

We deployment of Node Bs throughout the target area, the result is shown in
Figure 18:

Figure 18: Deployment design and hexagonal cell radius 550 m.

With an array of these features can cover the city's urban core with 36 locations.
We will perform a first simulation to gauge whether the cell size and number of
carriers is adequate or not.

Atoll UMTS simulations are based on a Monte Carlo simulator [1].Since the user
distributions of traffic map Atoll generates a population of users on the map and
for each of these users the simulator executes a power control algorithm for the
uplink and downlink.The objective of the algorithm is to minimize interference
and maximize network capacity.This will restrict the connection to the network
users who use low-priority services and generate a lot of interference.This
process creates a snapshot of the UMTS network, the result is a distribution of
users with different network parameters: level of interference, the terminal state
(connected, connection refused ...), load factor for each cell, etc.

In UMTS each mobile station receives interference from base stations other than
their own cells, but not other phones, and all base station receives interference
from their cell phones and other cells, but not the other base stations.

We have already said that UMTS capacity depends on the total received
interference. Atoll simulates the power control mechanism using an iterative
algorithm in each iteration, all the population of mobile users generated try to be
connected, one by one, to the network. If certain users penalize others too
mobile, they are rejected, with the decision of rejection correlated with service
priority.In Atoll distinguished the following reasons for rejection:

a) The signal quality is poor:

· The carrier / interference in the DL is below the threshold (Ec / Io <Ec
/ Io min).

· It exceeds the maximum power available for traffic channels in the DL
(PTCH> PTCH max).

· Exceeding the maximum power that can transmit moving in the UL
(Pmob> Pmob max).

b) If the above restrictions are observed, the rejections are caused by network
congestion:

· It exceeds the load factor (in admission or congestion).

· Have been exhausted channel elements per site.

· Not enough power to transmit cell.

· Have exhausted the spreading code.

A portion of the transmitter power is intended to pilot channel, another to the
synchronization channel, another to control channels and the rest is shared
among the traffic channels. Unlike the pilot channel and synchronization and
control channels, the number of traffic channels and their powers depend on the
data traffic, and is one of the parameters in the simulations is determined
through the control algorithm power. The minimum and maximum power of
traffic channels for each service are detailed in Table Services for UMTS
Parameters.The sum of the power of traffic channels, control, synchronization,
and pilot can not exceed the maximum power transmitted per cell.

Instead of sticking to the results of a single simulation, we will perform a group
of several simulations and study the results statistically. By running 10
simulations with all restrictions and value the results of the simulation average.

The results obtained (on average) are shown in Tables 20-22 (in parentheses
indicates the standard deviation):

Traffic requested:
Users Active Active Active Inactive

on the DL in the UL DL+ UL

Total 3.684,8(68.6) 1.483,8 846 461.4 893.6

Voice 2.480,6(57.85) 595.3 593.6 398.1 893.6

MMS 136.8(8.28) 67.6 69.2 0 0

Internet access 1.005,6 (18.17) 820.9 183.2 1.5 0

Video Conference 61.8(9.04) 0 0 61.8 0

Table 20: Traffic demand at a given instant.

Simulation results (16.5 iterations on average per simulation):

Number of users rejected 1867.9 (50.7%)

Exceeding the maximum power of the terminal in

the UL (Pmob> Pmob max) 1.2

It exceeds the standard maximum power available for traffic

Channels in DL (PTCH> PTCH max) 134.9

The carrier-interference in the pilot channel (DL) is below

threshold (Ec / Io <Ec / Io min) 1086

Saturation loading in the 635.6 DL

Refusal of admission 10.2

Table 21: Breakdown of rejected connections as the cause of rejection.

Broken down by services,
Users online online online online

on the DL in the DL DL+UL

Services

Total 1816(49.3%)(44.4) 459.2 448.4 300.6

Voice 1689.5(68.1%)(50.55) 398.1 413.9 268.8

MMS 17.1(12.5%)(4.93) 7.5 9.6 0

Internet access 78.7(7.8%)(8.94) 53.6 24.9 0.2

Video Conference 31.6(51.1%)(6.76) 0 0 31.6

Table 22: Breakdown of courses by the service connections

We can also study these models in a more graphic. Figure 19 shows the position
of all the terminals at the time of the simulation are trying to access a service
and the state found. In this case we see those red and black line that are being
rejected or delayed.

Connection
Rejection

Figure 19: Snapshot of the state of the network terminals.

Visually, the results are consistent with the tables drawn from the simulations,
we can see that about half of the users are being rejected.

The simulation results are far from the established quality objectives.We see that
indeed most penalized services are the lowest priority (MMS and Internet access)
and more specifically the penalty is Internet access, which is what generates
more interference. As the service requires the highest date rate, is the most
traffic demand and therefore more traffic channels required and the cell that
needs more power (generating interference in other phones).

Looking at Table 18, we see that the second cause of rejection is the saturation
on the DL. That is, we do not have sufficient traffic channels to meet demand. In
principle, the easiest way to increase the number of traffic channels is adding
new carriers.

And adding more transmitters also helps that there is more power to distribute
among the traffic channels and may help to improve the quality of the signal,
which would also be attacking the main cause of rejection (the carrier
interference pilot channel (DL) is below the threshold (E c / I o <E c / I or min)).

We add two carriers to each cell of the network to check if this cell size can meet
the quality objectives. If amply fulfilled, we can reduce the number of carriers in
the cells, to allow for future network expansions. Are met by a small margin, it
would be advisable to reduce the cell size, not to have too tight design.

The results of repeating the previous simulations, but with 3 carriers per cell are
shown in Tables 23-25.

Traffic requested:
Users Active Active Active
Inactive
In the DL in the DL DL+ UL
Total 3.700,1 1.493,2 864.2 454.1 888.6
(43,56)
Voice 2.467,3 592.6 593.4 392.7 888.6
(54,02)
MMS 131 65.4 65.6 0 0
(12,03)
Access 1.041,3 835.2 205.2 0.9 0
Internet (14.86)
Video 60.5 0 0 60.5 0
Conference (7.76)

Table 23: Demand for a given traffic.

Simulation results (14.7 iterations on average per simulation):
Number rejected 756.7 users
(20.5%)
Exceeding the maximum power of the terminal in the UL (Pmob> Pmob max) 1.4
It exceeds the standard maximum power available for traffic channels
in DL (PTCH> PTCH max) 106.2
The carrier-interference in the pilot channel (DL)
is below the threshold (Ec / Io <Ec / Io min) 161.1
Saturation load on the DL 487.9
Refusal of admission 0.1


Broken down by services:
Services
Total 2943.4(79.5%)(53.1) 905.7 735.7 440.6
Voice 2393.3(97%)(58.71) 574.7 575.5 381.7
MMS 75.3(57.5%)(9.49) 36.4 38.9 0
Internet Access 416.1 (40%)(9.61) 294.6 121.3 0.2
Video Conference 58.7(97%)(7.79) 0 0 58.7

Table 25: Breakdown of courses by the service connections.

In this case we can represent the map of Seville on the results of these
simulations (Figure 20).

Connection
Rejection

Figure 20: State of the terminal cells of 550 m radius and 3 carriers.

In this case shown on the map in Figure 20 the result of several simulations
simultaneously. We see that the connection terminals are clearly more numerous,
but the rejection rate remains high.

The results are greatly improved but still inadequate, we must rule out possible
to cover UMTS to Seville with the cell size.

Let's try using the following template available for deployment of UMTS Atoll in
areas with high population density. The template dense urban target area divided
into cells of 350 m radius, the result of covering the urban area of Seville with
cells of this size would be the one shown in Figure 21:

Figure 21: Deploying UMTS cells 350 m radius.

In this case the number of sites has increased significantly to 82.

Initially we will size the network to its maximum capacity, ie, with three carriers
per cell. If we find that the cell size is sufficient we can begin to reduce the
number of carriers at less charged cells, to give him room for network growth
and lower the initial cost of deployment.

The simulation results are shown in Tables 26-28:

Traffic requested:

Users Assets Assets Assets in Inactive
in DL in UL DL + UL
Total 3.669,9 1.471,2 847 462,3 889,4

(38,96)
Voice 2.476,2 603,2 584,1 399,5 889,4
(41,11)
MMS 134,8 67,5 67,3 0 0
(10,04)
Access 997,2 800,5 195,6 1,1 0
The Internet (18,82)
Video 61,7 0 0 61,7 0
Conference (5,06)


Simulation results (18 iterations on average per simulation):
Number rejected users 263.3 (7.2%)
Exceeding the maximum power
terminal in the UL (Pmob> Pmob max) 0
It exceeds the standard maximum power
available for traffic channels in the DL (PTCH> PTCH max) 30
The carrier-interference
pilot channel (DL) is below the threshold (Ec / Io <Ec / Io min) 3.1
Refusal of admission 0

Table 27: Breakdown of rejected connections as the cause of rejection.Broken
down by services:

On the DL in the DL DL+UL
Services
Total 3406.6(92.8%)(46.39) 1.239,5 816.5 461.7
Voice 2474.9(99.9%)(41.05) 603 583.6 399.4
MMS 120.2(89.2%)(10.14) 59.4 60.8 0
Internet Access 750.1(75.2%)(15.31) 577.1 172.1 0.9
Video Conference 61.4(99.5%)(5.12) 0 0 61.4

simulations (Table 23):

Connection
Rejection

Figure 22: State of the terminal cells of 350 m radius and 3 carriers.

The results are still not achieving the quality objectives, so let's try to reduce a
little the size of the cell.

Predefined templates Atoll UMTS cell sizes do not allow minors. This is explained
we've made a pretty optimistic traffic modeling (from the point of view of the
operator) to cover our backs and make sure that the network later on staying
small.

We will define a template image of the dense urban, but with a cell size of 200 m
3 carriers. After making the deployment on the map the result is shown in Figure
22:

Figure 23: Deployment of UMTS cells of 200 m radius.

The simulation results shown in Tables 29-31:

Traffic requested:

Users Claims on Active in Active in the Inactive
the DL the UL DL + UL

Total 3.684 1.488,33 830,33 470,67 894,67
(57,35)
Voice 2.495,67 602,33 583,67 415 889,4
(16,65)
MMS 125,33 62,33 63 0 0
(13,72)
Access 1.008,33 823,67 183,67 1 0
The Internet (29,69)
Video 54,67 0 0 54,67 0
Conference (4,78)


Simulation results (17.33 average per simulation iterations):
Number of users rejected 97 (2.6%)
terminal in the UL (P mob> P mob max) 0
It exceeds the standard maximum available power
for traffic channels in the DL (P tch> tch P max) 13.33
is below the threshold (E c / I o <E c / I or min) 0
Denial of admission 0


Services
Total 3587(97.4%)(43.18) 1.398,67 823 470.67
Voice 2495.67(100%)(16.65) 602.33 583.67 415
MMS 122.33(97.6%)(13.72) 61 61.33 0
Internet access 914.33(90.7%)(15.37) 735.33 178 1


simulations. The state of the network shown in Figure 24:

Connection
Rejection

Figure 24: State of the terminal cells of 200 m radius.

As expected, virtually all of the requested connections have been accepted.

These results if they meet the quality objectives set initially, we even have some
room to try to minimize the cost of the network (number of sites) and reduce the
number of carriers in some transmitters to provide a network for further margin
expansion.

To obtain these results are needed 250 locations.However, many of them are on
the edges of the target area and only use 50% of the surface of some of their
cells. It is expected that these sites are not providing service to many users and
the traffic of these users can be taken up by neighboring cells without the degree
of saturation increased significantly.

Similarly, there are areas of the map with a density of users / traffic much
smaller, so small cells do not need to support this traffic.200 m cells are essential
in urban, dense urban buildings and in fact, in previous simulations most of the
rejected users come from these areas.

We rely on that to assume that if we remove the border sites to cover small
target area and eliminate some sites open and industrial areas, the probability of

rejection need not be accepted.We dimensioned the network to the rejection in
urban areas is acceptable, but in doing so we have oversized the network in
other areas.

After you delete and add sites several times and repeat the simulations as often
as necessary were obtained the configuration of Figure 25:

Figure 25: Deployment of final locations of the UMTS network.

We see that we have eliminated most of the sites on the edge of the target area
and those in which only one cell was missed we reoriented the antenna to give
coverage within the area of interest.

We have also eliminated some sites of the environments with lower traffic
density (open area and industrial area). In residential and industrial areas that
are surrounded by dense areas and have maintained those sites that serve as
reinforcement to support the traffic of the surrounding areas.

We have also reoriented the antenna sites within the village that gave coverage
to low traffic areas (such as parks, open type), to strengthen coverage of the
surrounding areas more densely populated.The final configuration results are
shown in Tables 32-34:
Assets Assets Assets in Inactive
Users
in DL in UL DL + UL
Total 3.647,25 1.460,75 841,75 446,75 898
(32,85)
Voice 2.463,25 577,75 601 386,5 898

(34,37)
MMS 122,5 64,75 57,75 0 0
(12,09)
Access 1,004 818,25 183 2,75 0
The Internet 12.1
Video 57,5 0 0 57,5 0
Conference (8,08)


Simulation results (16.75 average per simulation iterations):
Number of users rejected 98 (2.7%)
terminal in the UL (P mob> P mob max) 0
It exceeds the standard maximum available power for channels
Traffic on the DL (P tch> tch P max) 13.25
is below the threshold (E c / I o <E c / I or min) 0
Refusal of admission 0


In the DL in the DL DL+UL
Services
Total 3587(97.4%)(43.18) 1.398,67 823 470.67
Voice 2463.25(100%)(34.37) 577.75 601 386.5
MMS 120.25(98.2%)(11.37) 63 57.25 0
Internet access 908.25(90.5%)(4.66) 729 177 2.25


Reducing the number of sites by approximately 25% have achieved similar or
even better for some services (MMS). This shows that some of the projected sites
added nothing to the network and that something as simple as redirecting some
antennas to areas of high traffic density can increase the network capacity.

This is also confirmed in Figure 26, showing where the terminals are located
rejected the previous simulations. We see that areas with higher density of sites
are still the highest density of terminals has rejected, while the industrial area
just west of the river has a dozen rejections with only 7 base stations.

Connection
Rejection

Figure 26: Location of the connections rejected.

3.6 Establishment of neighborhoods.
Atoll is possible to establish automatically neighborhoods by imposing some
restrictions on certain cells that may be part of a neighborhood. Once established
neighborhood relations, Atoll easy viewing of neighboring cells on the map, which
allows easy management.

The algorithm for automatic assignment of neighboring cells is based on the
following parameters:

· -Max neighboring cells.It can be set globally or individually in the table
cells.

· Inter-Site-Max distance is the maximum distance that can exist
between the reference cell and a cell candidate neighbor.

· -Overlap between the coverage areas of the reference cell and a cell
candidate neighbor.The concept of coverage here refers to the level of the
pilot channel, or its signal to interference (Ec / Io).

· -Power which contributes to the total interference.

Additionally you can set the following additional restrictions:

· "Forcing all cells of the same site are neighbors.

· -Force that are geographically adjacent neighboring cells.

· Forcing symmetry-neighborly relations.

· -Establish exceptional couples.

To perform automatic assignment of neighboring cells we will Automaticac
allocation option, which is in Neighbours option within the cells of the folder
option transmitters of the data tab of the browser window.

We will impose the following restrictions on the establishment of neighborhood
algorithm:

Distance between neighboring sites: 1,200 m: in urban areas the distance
between adjacent sites is around 600 m.But sites that cover open or industrial
areas are more isolated, more than about 1,000 of the closest locations. This
restriction aims at limiting the number of residents in such locations.Setting a
maximum distance of 1,200 meters to ensure that these are neighboring sites
only closer.

Maximum number of neighbors: 20: This restriction is intended for sites in the
most populated areas.Each cell is surrounded by a maximum of 6 other cells.If
each physical cell Atoll are 3-cell (cell = torque transmitter / carrier) we will have
6 x 3 = 18 + 2 (the others carry the same physical cell) = 20. With this
restriction we make sure that even if more than 20 pairs of transmitter / carrier
that are less than 1,200 meters these are not considered neighbors.

Atoll generates a huge table with all the neighbors of each cell. As such
information becomes unmanageable will be included in Table 36, which shows
only few cells have a given number of neighbors to see which is approximately
the average number of neighbors per cell

Number of neighbors Number of cells
13 6
January 2005 9
10 26
9 13
8 54
7 137

6 1032
5 205
4 91
3 17
2 3

Table 35: Number of cells with a given number of neighbors.

3.7 Allocation of primary scrambling codes.
The randomization codes allow you to separate from other cells. It is advisable to
assign different codes to a given cell and all cells belonging to its list of
neighbors. The assignment can be done manually for each cell, or automatically
on all cells or a group of cells. Depending on the allocation strategy may be
imposed various restrictions on code groups and domains, defining exceptional
couples, distances and neighborhoods. At all times you can check the consistency
of the current code assignment on the network under study.

In UMTS there are 512 scrambling codes that are distributed in 64 clusters of 8
codes. The clusters are numbered from 0 to 63, and codes from 0 to 511.The
code assignment can be done either manually or automatically. In the second
case, Atoll provides a mapping tool based on an algorithm that takes into account
the definition of groups and code domains, as well as additional restrictions
based on the list of neighboring cells, second neighboring cells, criteria and
minimum distance pairs exceptional.

First let's create a code for domain Atoll. In the browser window, we will
Transmitters | Cells | Primary Scrambling Codes | Domains and call codes Sevilla.

It is essential that a cell and its neighbor does not have the same code as the
maximum number of neighbors that we introduced in the calculation algorithm
neighborhoods is 20 going to try initially to run the algorithm with 20 codes to
see what it gives. In addition, we have seen that 20 is the number of cells in the
space adjacent to another cell in the area of highest density of sites, so it seems
a reasonable value to start. Table 36 lists the 20 codes are initially elected, in 4
groups of 5.

Groups Minimum Maximum Step
Group 1 0 4 1

Group 2 32 36 1
Group 3+ 64 68 1
Group 4 96 100% 1

Table 36: Codes of randomization initially elected.

Before running the algorithm we have to go to the table cell (Cells Transmitters |
Open Table) and fill the field Scrambling code domain with the domain created:
Codes Sevilla.

We can run the allocation algorithm. This option is in the browser window, in
Transmitters | Cells | Primary Scrambling Codes | Automatic allocation.The
associated dialog box, you can select the parameters that the algorithm takes
into consideration:

· -Existing Neighbours: using the table of neighborhoods, a cell can not
have the same scrambling code to its neighboring cells, and between all
codes must be different.

· -Second Neighbours: the previous condition spreads to neighboring
cells to their neighbors.

· -Additional Ec / Io conditions: all stations belonging to the active set
of the reference cell in the area where it provides the best signal, they
must have different codes.

· "Reuse Distance: Minimum distance from which codes can be reused.

We follow the same criteria to choose the number of codes. If forced to use
different code to the neighbors of neighbors to 20 codes was too weak. It does
not seem advisable to abuse of the codes that way in such a large network.
Activate only as constraints

Neighbours and Additional Existing Ec / Io conditions.

On the other hand, we have seen that there is distance between neighboring
sites if up to 1,200 m. Since it is very critical that we have in our network signals
with power levels of the same order of magnitude using the same code in the
same cell, we will be very restrictive in this regard and set a manifestly greater
reuse distance: 2,000 m.

The first execution of the algorithm given error, it was impossible to enforce
these restrictions by using only 20 codes.So groups of 5 were added to the
domain code of codes until the algorithm converged to reach a total of 55 codes.
The codes used are those in Table 37.

Groups Minimum Maximum Step
Group 1 0 4 1
Group 2 32 36 1
Group 3+ 64 68 1

Group 4 96 100% 1
Group 5 128 132 1
Group 6 160 164 1
Group 7 192 196 1
Group 8 224 228 1
Group 9 256 260 1
Group 10 288 292 1
Group 11 320 324 1

Table 37: Codes of randomization used.

With the results of the algorithm, Atoll generates statistics that show the number
of times the algorithm has assigned a specific code (Figure 27) and the number
of times you have used a code for a given cluster (Figure 28 .)

Figure 27: Allocation of randomization codes for UMTS network.

We have 177 sites, each with 3 sectors and 3 carriers per sector, which makes a
total of 1,593 cells, for which we assigned 55 codes, which gives an average of

28.96 cells per code. We see that the code assignment revolves around the
aforementioned value, indeed of the 11 sets of codes we see that there are 6 in
all codes exceeded that average and 5 in which none does.

Let us now use the cluster:

Figure 28: Use of cluster codes for our UMTS network.

UMTS has 64 clusters of 8 codes each. We have defined a code domain
consisting of 11 groups of 5 codes, each group therefore a distinct cluster. We
then used 11 clusters, each with 3 free codes. Could therefore be added to the
network 33 new codes without the need for a new cluster

3.8 Study coverage
In this section we will perform a series of studies on the deployed network
coverage. The aim of these studies is to document graphically the network and
verify that the design is adequate.

Coverage studies provide us with information on the status of the network at all
locations of the target area. The different types of site surveys that can be
performed in Atoll are:

· Study coverage signal level.

· Study transmitter coverage.

· Study overlap.

· Study of noise on the DL.

· Study of signal to interference in the pilot channel.

· Study of the service area on the DL.

· Study of the service area in the UL.

· Study of effective service area.

· Handover study.

See the results of different studies:

Study coverage signal level.

The study provides a graphical representation of the signal level received by the
terminal (downlink coverage.)

The site survey performed by the signal level shown in Figure 30.

Figure 30: Study level of signal coverage.

We have already said that UMTS is an interference limited radio system, so that
the signal level who is not in principle limited coverage.

In any case we have a signal level of -90 dBm over the entire target area
(including interiors). Taking a value of a typical sensitivity of -105 dBm mobile
terminal we have 15 dB of gross margin for fading, so in principle, the signal
level should not be a problem for our network.

Study transmitter coverage.

This study will cover a different color mark the footprint of each transmitter in
this case we used 10 colors and have been alternating for treating adjacent
transmitters that do not match the same color. The result of the study are shown
in Figure 31.

Figure 31: Study transmitter coverage.

We see the sites in the village, the coverage area roughly coincides with the
corresponding cell, while more isolated sites provide coverage to some areas
significantly higher.

Study overlap.

This study shows the number of base stations that each point on the map above
the threshold power at the reception.

The results of the study conducted overlap shown in Figure 32:

Figure 32: Study overlap.

Study the level of interference in the DL.

This study evaluates the total interference received in the downlink. All types of
predictions that we will henceforth always refer to a simulation or set of
simulations is performed for a terminal, service and mobility determined.

We will conduct two studies on the level of interference, one for the majority
case, telephone and voice terminal and one for the most critical case: terminal
telephone and Internet access.

These studies are done to the population generated by the simulation average of
10 made for the final configuration of the above.The study for the voice service
and telephone terminal shown in Figure 33.

Figure 33: Study of the noise level of the Voice of the terminal telephone service.

We see that the total interference level generated is significantly higher than the
signal level of the site survey in Figure 30.Anyway it should not worry, because
as explained in Chapter 2, UMTS systems are resistant to interference and due to
the CDMA technology is easy to discriminate between the receptor interference
and the desired signal. As discussed in the study of signal-interference in the
pilot channel, to overcome a certain threshold of Ec / Io (UMTS typical value is -
14 dB) is sufficient to discriminate signal and interference, and as will be seen in
Figures 35 and 36 this occurs for almost the entire target area.

The same goes for the Internet access service, but in this case the noise levels
are even higher. This is because Internet access service requires a higher
bandwidth and therefore needs more power transmission in the downlink. The
results of the study for this service are shown in Figure 34.

Figure 34: Noise Study service Internet access to your terminal.

Study of signal to interference in the pilot channel.

This study places a test terminal type selected in each pixel and analyzes the
relationship between E C / I O of the received signals.As in the previous case we
have chosen the population generated by the simulation average of 10
simulations.

Just as before, we will conduct a study to the most common (and your voice) and
for the most critical case (telephone and Internet access).

The results of the study for voice service and telephone terminal are the 35Figura

Figure 35: Ec / Io in the pilot channel for voice service telephone terminal

Table 9 is set threshold E C / I O for all mobilities in -14 dB. We see that virtually
the entire target area will have values above -15 dB, so in principle confirms the
results of the simulations and we should not just rejection by poor signal quality
for this service.

We can see the results of the study to the Internet access service in Figure 36:

Figure 36: Ec / Io in the pilot channel for Internet access service telephone
terminal.

The results are very similar to the voice service, which is logical since the
transmission power in the pilot channel is the same and the interference is the
same for all services.The findings are equivalent to the previous case, we have
an Ec / Io above -15 dB throughout the target area, so it is likely that there just
rejections due to poor signal quality, confirming the results of simulations.

Study of the service area on the DL.

This study evaluates whether the test terminal can obtain service in the
downlink, taking into account the limited traffic capacity based or active bases.

This study is very interesting because it is the mobile that checks are rejected
because of network congestion.We know that the power intended for traffic
channels depends on the amount of traffic that has to be handed-over, and if at
some point we have to transmit more power than the maximum, then there is
traffic that has to be rejected, for which a running Atoll power control algorithm

that determines how much power goes to each connection and power
connections are not (are rejected).

This study places a test terminal at each location of the target area and see if
you can get service or according to the results of simulations.

The results for the telephone and voice terminal are shown in Figure 37.

Figure 37: Study of the service area on the DL for the terminal voice phone
service.

We see that we can get service at all locations of the target area. This is
consistent with the results of simulations and for the voice service had no
rejections.

We must remember that this does not mean never going to have rejections for
this service. This means that in 10 (which are the times you have repeated the
simulation) we have made snapshots of the network with traffic demand within
the normal range, there were no rejections.

In exceptional situations, where demand for passenger traffic to grow, such as
disasters, Fair, Easter, New Year ... it certainly will be significant even rejection
rates for voice service.

The results of the study for the terminal telephone and Internet access are
shown in Figure 38.

Figure 38: Study of the service area on the DL for the Internet access service
telephone terminal.

We see that most of the target area can get service, but especially in dense
urban areas, there are some locations where our connection attempts would be
rejected.This confirms the results of the simulations, they gave us half a rejection
rate of 9.5% for this service.Of course, the majority of these rejections would
occur in the area of greatest density.

Study of the service area in the UL.

It is analogous to the above but for the uplink, taking into account the limited
power of the mobile terminal.

The results of the study for the terminal telephone and voice are as shown in
Figure 39.

Figure 39: Study of the service area in the UL for voice service telephone
terminal

In other mobile communications systems such as GSM or TETRA uplink is usually
more limiting than the downward, as the need to take small, manageable
terminals forces us to take power in the upstream transmission very low and not
get compensated designing high sensitivity receivers in base stations.

However, our UMTS network behaves the opposite. As seen in Figures 39 and 40
get service in the increase in all locations of the target area, which agrees with
the results of the simulations, which gave us 0 rejections excess load on the
ascendant. This is logical because the Internet access service has a very
asymmetric traffic with a high demand in the downstream and far less on the up,
it makes sense that the network has to reject many more connections than the
other.

Figure 40: Study area in the UL service for Internet access service telephone
terminal

Study of effective service area.

This study provides the area intersection of the two.

As we have seen, the downlink is much more restrictive than the upwardly, so
the results of this study are virtually identical to the study of the service area in
the downlink.

The results for the telephone and voice terminal are shown in Figures 41 and 42:

Figure 41: Study of effective service area to service your voice terminal

Figure 42: Study of effective service area to service Internet access to your
terminal

Handover study.

This prediction studies the active set of a test mobile located at each point on the
map, and renders it according to selected criteria.Let us briefly explain the
concept of the active set in UMTS.

In the UMTS system uses a handover mechanism for transferring called
continuity, SHO (Soft / Softer Handover).Thanks to universal frequency reuse is
possible to connect the call to the candidate to the handover station before
disconnecting it from the source station, keeping both links simultaneously for
some time. A call can be supported by the three sectors of a base station and /
or

by two or more stations. Each of the bases involved keeps in touch with the
phone until the attenuation to one of them is excessive, when you leave the link
on that basis. In the uplink, during the handover period continuously, the signal
transmitted by the mobile is detected by the base stations involved, make a
selection or combination of demodulated signals. In general, for base stations
located at different sites, it is easier to select the signal of higher quality (soft

hand-off).For base stations located on the same site, as in sectorized cells, the
physical proximity to combine the signals (soft hand-off) before demodulation.

The set of bases with a mobile is known as the Joint Contact Active (Active
Set).The maximum number of stations that can be part of the active set of a
mobile (Active Set Size) depends on the type of terminal.

The criteria used for a station is part of the active set of a terminal is based on
the concept of threshold for handover (AS THRESHOLD), defined for each cell in
the table Transmitters | Cells | Open Table.The transmitters that constitute the
active set of a tower should meet the following conditions:

· "They must use the same frequency

· "The quality of the pilot (Ec / Io) of the best season to exceed a
threshold defined for terminal mobility (in this case -14 dB).

· "The pilots of the other bases in the active set must have a Ec / Io
that does not fall below the threshold of handover on the best season.

· "They must be nearby stations of the best base if you selected AS
Neighbours restricted to the characteristics of the equipment.

The results of this study are shown in Figures 43 and 44:

Figure 43: Study of the asset to the Voice of the terminal telephone service

Just as occurred in studies of Ec / Io, these studies are identical for both services
and the level of the pilot channel signal and interference are the same for both.

As before, studies have been done to the population generated by the average of
10 simulations of the final configuration.

Figure 44: Study of active Internet service's terminal access to your

Study of interference in the pilot channel.

At each pixel indicating whether the number of bases that are received Ec / Io
enough is "excessive" in the sense that exceeds the maximum number of active
bases allowed by the choice of mobile terminal.

It is appropriate that each location on the network has the maximum number of
active bases, as this benefits the soft handover, but if we have more bases than
allowed only thing is to get more signal level waste, which translates into
interference.Any signal that arrives at a terminal that is not one of its bases is
active interference.

Interference studies conducted in the pilot channel are shown in Figures 45 and
46

Figure 45: Study of interference in the pilot channel for the service of Voice of
the telephone terminal.

We hardly have seasons interfering in most locations. This affects very low levels
of denial of connections to the network (as we have seen in the simulations,
where we have not had any rejection for voice service).

Figure 46: Study of interference in the pilot channel for Internet access service
telephone terminal.

In this case the number of interfering base stations is much higher, which results
in a rejection rate higher than for voice service (which we have seen in the
simulations).

This is because Internet access service is not configured to support soft
handover, and therefore any base station exceeds the threshold Ec / Io instead
of being part of the active set, it becomes an interfering base station.

3.9 Network evolution.
As mentioned above, the network has been designed to meet quality objectives
when the forecast of subscribers has reached its peak (20% of the inhabitants of
the city).It is expected that the number of subscribers later years to reach those
numbers, or you may not even reach these amounts.

Have also discussed the difficulties involved for a CDMA system the handover
between different frequencies, and that requires working in compressed mode,
so they agree to limit as far as possible the areas that must be produced using
various carriers.

Not seem necessary or desirable then the use of three carriers per cell since the
launch of the network. The logical thing is to make an initial deployment with a
single carrier per cell into expanding capacity to measure the number of
subscribers need them.

In this section we make a study of how it degrades the quality of network service
as the number of subscribers increases and substantial improvements are made
as extensions of the building.

Atoll can easily simulate such scenarios due to the scaling factor. When the
simulation is allowed to use a parameter called Global Scaling Factor, which
scales the traffic demand by multiplying by the scaling factor.A factor of 0.4
means that the simulations were performed considering 40% of actual traffic.

Let us assume that the number of subscribers increases linearly at a rate of 10%
maximum per year to reach the maximum number of subscribers to 10 years of
the implementation of the network. As mentioned above, initially carried out the
deployment with a single carrier per sector.

1 year after deployment (1 carrier per cell, 10% of subscribers):

Online Services

Total 345.7 (99.4%) (16.03)
Voice 234.4 (100%) (17.01)

MMS 12.9 (98.5%) (1.81)
Internet Access 93.3 (98.1%) (7.27)
Video Conference 5.1 (100%) (1.64)

Table 38: Connections accepted by the network (10% of users and 1 carrier).

We found that indeed, there is no need to start the deployment with the racks at
full capacity. This allows us to significantly reduce the initial investment for
setting up the network and guarantees a better initial performance of the
network (at work with only one carrier per sector). Avoid oversizing and also get
the network itself to finance its expansion of capacity, since the network is
operational and therefore billing from day one. Besides the capacity expansion of
the network are zero-risk investment, because traffic is rejected and the money
we lose the ability to increase income means increasing systematically.

2 years after deployment (1 carrier / cell, 20% of subscribers):

Services Online
Total 720.7 (98.6%) (23:43)
Voice 490.3 (100%) (17.81)
MMS 25.5 (99.6%) (6.76)
Internet Access 191 (94.9%) (18.07)


Quality objectives continue to be met comfortably 2 years after completion of the
deployment. In addition to reducing the investment required for implementation
of the network, another advantage of not displaying all the carriers from the
initial moment is that you avoid the wear suffered all these carriers to be
operational, thus prolonging the life of the network and

Minimizing the number of failures in the network (unless carriers, lower failure
rate). This also saves on maintenance and improvement in the quality of network
service.


Services Online
Total 1079.5 (97.3%) (9.22)
Voice 745.7 (100%) (17.94)

MMS 41.7 (98.6%) (5.73)
Internet Access 272.9 (90.3%) (9.22)
Video Conference 19.2 (99.5%) (4.21)


We see that in this case the quality objectives are met by a small margin. It is
clear that during the 3 rd year of operation of the network will have to start to be
the first expansion of capacity, adding a carrier in the most loaded (which will
probably make time to be risen from 10% to reject the service Internet access,
as these data provide for the entire network and would ideally be met for all
cells).

We will simplify and as we have done until now we demand that quality
objectives are met in all cells, but only at the entire network (most operators do
not or globally).We will not make the expansion of capacity in a progressive
manner, which would be optimal. Let's go on pretending until the quality
objectives are no longer met, at which will double the network capacity by
adding a carrier to all sectors.


Services Online
Total 1408.9 (95.8%) (42.97)

Voice 990.2 (100%) (39.32)
MMS 49.8 (94.3%) (7.24)
Internet Access 343.8 (85.5%) (15.09)
Video Conferencing 25.1 (100%) (3.08)


As expected, after 4 years of operation of the network of low priority services
have fallen below the quality objectives.It is therefore the time of the first
expansion of network capacity. Adding one carrier per sector the results of the
simulations are:

4 years after deployment (2 carriers / cell, 40% of subscribers):

Services Online
Total 1426.1 (98.8%) (20.44)

Voice 983.8 (100%) (37.02)

MMS 47.3 (99.4%) (6.42)
Internet Access 370.1 (95.8%) (20.44)
Video Conference 24.9 (99.6%) (5.79)

Table 42: Connections accepted by the network (40% of users and 2 carriers).

The capacity expansion has had the expected and the network could grow a few
more years before needing a new extension.

5 years after deployment (2 carriers / cell, 50% of subscribers):

Services Online
Total 1817.38 (98.4%) (37.06)
Voice 1259.5 (100%) (28.24)
MMS 63.63 (99%) (5.1)
Internet Access 464.38 (94.3%) (22.04)


Quality objectives continue to be met satisfactorily. However, it is normal at 5
years is thought to migrate to new technology (in this case would be HSDPA).

It is accepted that between the deployment of each generation of mobile spend
about 10 years and that 5 is normal to migrate to an intermediate technology. In
fact, we know that the first UMTS network in Seville began operation on June 1,
2002 and five years later, in 2007 and we cover HSDPA (3.5G) [10].

With this new technology, it is possible that the capacity expansion planning
when otherwise it would be appropriate to consider that if the capacity expansion
that migration brings is enough to meet increased traffic demand or need to
continue to deploy carriers. Anyway, HSDPA escapes the objectives of this
project, so it is going to plan the expansion of capacity without regard to
migration.

6 years after deployment (2 carriers / cell, 60% of users):

Services Online
Total 2158.67 (97.7%) (45.55)
Voice 1472.17 (100%) (50.69)
MMS 84.67 (97.3%) (7.72)

Internet Access 564.33 (92%) (19.8)


Already beginning to be seen again as the increase in the number of subscribers
is gradually degrading the quality of service.However, following the same
approach as before, not to simulate 3 carriers to fall below the quality objectives.


Services Online
Total 2498.6 (96.9%) (40.58)
Voice 1755.6 (100%) (45.26)
MMS 86 (96.6%) (7.27)
Internet Access 614.2 (88.9%) (10.53)


We see that for some, but have fallen back below the quality objectives. It is
therefore the time of the last upgrade of the capacity of our network.

7 years after deployment (3 carriers / cell, 70% of capacity):

Services Online
Total 2523.8 (98.6%) (65.56)
Voice 1728 (100%) (30.05)
MMS 96.6 (98.4%) (10.97)


As we expected, with 70% of the number of subscribers and the network to its
maximum capacity exceeded the targets.

Little else is there to comment, Tables 39, 40 and 41 show the simulation results
for 80%, 90% and 100% of the number of subscribers expected.


Services Online
Total 2886.8 (98.3%) (54.88)
Voice 1972.2 (100%) (32.52)
MMS 103.6 (98.9%) (12.88)
Internet Access 761.6 (93.9%) (30.86)


9 years after deployment (3 carriers / cell, 90% of users)

Services Online
Total 3201.5 (97.9%) (52.41)
Voice 2187 (100%) (36.4)
MMS 119.75 (97.6%) (9.6)



Services Online
Total 3587 (97.4%) (43.18)

Voice 2463.25 (100%) (34.37)
MMS 120.25 (98.2%) (11.37)
Internet Access 908.25 (90.5%) (4.66)


This raises the question of what to do after 10 years when the number of
subscribers continues to grow and the quality of network service getting worse,
"increase the number of sites?

The answer is clearly no. Even the most visionary could guess back in 2000 when
these networks were planned just as GPRS (2.5 G) served as a bridge between
GSM (2G) and UMTS (3G) technologies appear to provide increased capacity of

UMTS, HSDPA and HSPA already in operation, 5 years after the launch of UMTS
in Seville and there is talk that it is possible the emergence of the first 4G
network in the United States later this year [10].
The evolution of technology is virtually unpredictable and as I said before is not
thought advisable to design networks that will be in operation for many years
may become obsolete before starting to recover its investment. 4 G may begin to
appear at any time between 2008 and 2012. This means that a UMTS network in
Seville may have a lifespan of well over 10 years, and if it turns out, are always
bridges to support technologies that increase in traffic demand.

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