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3 Radio planning with Atoll.The purpose of this paper is to provide the plan and design a UMTS mobilecommunications network to give coverage to the town of Seville.We used the software tool Atoll radio planning and simulation, developed by thecompany Forsk. With the help of this tool will determine the design parameters ofthe network and relevant simulations will be performed to verify that theobjectives have been achieved quality.3.1 About Atoll.Today is no longer regarded the implementation manual or any programming ofall necessary calculations for radio planning as described in Chapter 2 of thisdocument.In a professional environment they are always planning tools, exceptin very simplified.ATOLL is a radio planning environment based on windows, easy to use, supportswireless carriers throughout the lifetime of the network. From initial design to theoptimization phase and during the various extensions .More than an engineering tool, ATOLL is a technical information system open,scalable and flexible that it can be easily integrated into othertelecommunications systems, increasing productivity and reducing developmenttime.ATOLL allows a wide variety of deployment scenarios. From a single server, upconfigurations 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 UMTSmodule (allowing projects CDMA / CDMA 2000) specifically for the analysis andnetwork planning W-CDMA/UMTS, the Measures module allows you to importand manage specific measures CW or test data mobile routes, Module AutomaticFrequency Planning for the optimization of frequency plans GSM / TDMA andMicrowave Planning module. This module allows users to plan and analyzemicrowave links.The advantages for our purposes is obtained from this application are basedmainly 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 oninformation extracted from these maps and databases that the engineergenerates information on the network. Maps, databases andthe 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 userpopulation of the city of Seville  , .We create a UMTS-type project (File | New) by selecting the template UMTSHSDPA. 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 (maptype 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 sufficientbecause the target area topography is fairly uniform and regular.The map is a map of heights and contains altimetry and topographic relief of thework area.The information contained in this map is used for the calculation ofcoverage 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 acolor 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 mapwe 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 bymoving the mouse for almost all visible simultaneously. We will arrange toappreciate all the time clutter maps, orthophoto and vectors. The result of thisoverlap 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, andeach one will assign a number of UMTS services with certain parameters thatindicate the user traffic generated by each service.We are only going to includein the model of services: voice, MMS, Internet access and video conferencing. Itwas 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 conferenceR99 Bearer LCD12 UDD64 UDD384 LCD64Service Type Circuit mode Packet mode Packet Circuit mode ModeSoft handoff allowed Yes No No YesPriority 2 0 0 1Factor activity in the UL 0,4 0,75 0,75 1Factor activity in the DL 0,4 0,75 0,75 1Average date rate in the UL 12.2 kbps 64 kbps 64 kbps 64 kbpsAverage date rate on the DL 12.2 kbps 64 kbps 384 kbps 64 kbpsLost by the body 3 dB 0 dB 0 dB 0 dBTable 1: Characteristics of UMTS services.
These services can be obtained from different types of terminals. We willconsider two different types of terminals: mobile phone and PDA. The terminalcharacteristics are those that have default Atoll, and are listed in Table 2.Terminal Minimum power Maximum Noise Active set sizeType (dBm) power (dBm) Figure (dB)Telephone -50 21 8 3PDA -50 25. 7 1Table 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 UMTSnetworks to which access has been , . · 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 150MMS Telephone Mobile 0 - 200 6.000Access TelephoneThe Internet Mobile 0,005 125 - -Video TelephoneConference MobileTable 3: Traffic generated by the user Adolescents. · Young (20-30 years). Service Terminal Calls per Call duration Volume of data Data volume in Type hour (Sec) in the UL DL (Kbytes) (Kbytes)Voice Mobile 0,25 275 - - PhoneMMS Mobile 0 - 200 200 Phone
Internet Mobile 0 - 300 7.000Access PhoneVideo Mobile 0,005 150 - -Conference PhoneTable 4: Traffic generated by young users. · Middle-aged (30-50 years).Service Terminal Calls per Call duration Volume of data Data volume in Type hour (sec) in the UL DL (Kbytes) (Kbytes)Voice Mobile 0,2 200 - - PhoneMMS Mobile 0,005 - 100% 100% PhoneInternet Mobile 0 - 200 6.000Access PhoneVideo Mobile 0,025 100% - -Conference PhoneTable 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 - - PhoneMMS Mobile 0,001 - 100% 100% PhoneInternet Mobile 0,0025 - 200 6.000Access PhoneVideo Mobile 0,00125 60 - -Conference PhoneTable 6: Traffic generated by the user age. · Elderly (+65 years).Service Terminal Calls per Call duration Volume of data Data volume in Type hour (sec) in the UL DL (Kbytes) (Kbytes)
Voice Mobile 0,05 60 - - PhoneMMS Mobile 0,0005 - 100% 100% PhoneInternet Mobile 0,00125 - 100% 3.000Access PhoneVideo Mobile 0,00005 30 - -Conference PhoneTable 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)Voice Mobile 0,5 350 - - PhoneMMS Mobile 0 - 200 200 PhoneInternet Mobile 0,25 - 500 10.000Access PhoneVideo Mobile 0 200 - -Conference PhoneVoice PDA 0,5 350 - -MMS PDA 0 - 200 200Internet PDA 0,25 - 500 10.000AccessVideo PDA 0 200 - -ConferenceTable 8: Traffic generated by the user person business.The next step for modeling the traffic generated by the city is to define a seriesof "environments" type, each of which will assign a population density of usersassociated with their mobility.Later on the map available generate an environment map, which is only noted onthe 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 areconsidered typical values of UMTS in cities.Average speed mobility rate Eo / Io Threshold (Km / h) (dB) HG-SCCH Ec / Nt (dB)
Pedestrian 3 -14 -950 Km / h 50 -14 -990 Km / h 90 -14 -9Table 9: Types of mobilityAnd finally we define the environments. Each environment is characterized by aseries of pairs "user profile" mobility "and a population density associated witheach of them. Environments are defined as set out in Table 10. The densitieswere chosen by reference to demographic studies which have been accessed ,.Type of environment Population density (hab/Km2) Density of subscribers(ab/Km2)Open 400 100Urban 20000 4000Dense urban 30000 6000Residential 5000 1000Industrial 10000 2000Great Buildings 40000 8000Table 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 notachieved, but ensures that the network does not saturate easily.Then we estimated the density associated with each environment for each usergroup, again taking as reference demographic studies of the National Institute ofStatistics .The results are shown in Table 11.Type Teenage Young Medium older other BusinessenvironmentOpen 8 21 39 21 9 2Urban 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 50Buildings 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 withthe 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/hTeen 2 3 3Young 7 7 7Median age 13 13 13older 7 7 7other 3 3 3Business 0 1 1Table 12: Types of users and mobility associated with the open environmentTable 13 shows what we have estimated for an urban environment:User type/Mobility Pedestrian 50Km/h 90km/hTeen 375 25 25Young 700 50 50Medium 1000 100 100Older 700 50 50Other 40 40 620Business 50 13 12Table 13: Types of users and mobility associated with the urban environment.For a dense urban environment has been a percentage of subscribers in muchlower vehicle, being mainly the old town area, which is intended to restrictvehicle access in the near future.Densities associated with the binomial type ofuser-mobility are shown in Table 14:User Type /Mobility Pedestrian 50Km/h 90km/hTeen 780 10 10Young 1170 15 15Median 1760 20 20Older 1170 15 15Other 880 10 10Business 95 3 2Table 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 associateddensities are given in Table 15:user type /Mobility Pedestrian 50 Km / h 90 km / hTeen 140 5 5Young 180 10 10Middle 250 13 12Older 180 10 10Other 140 5 5Business 20 3 2Table 15: Types of people associated with residential mobility.All these parameters can be completed in the UMTS parameters folder in thedata tab of the browser window.You can delete and add entries for folders:Environments, User Profiles, Terminals, Mobility Types, Services and within eachentry 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 wewill define a number of areas and each of them we assign one type ofenvironment (environment map or raster).The map of environments we will generate a similarity of map of land uses whichhave the city of Seville.The land use map or clutter classes each zone shows adifferent color.To create a traffic map Atoll Geo select the tab of the browser window, create anew road map, scenario-based or raster, and we mark on the map kind ofenvironment that belongs to each zone. The result is shown in Figure 15
Open Residential Urban Dense urban High buildings Industrial estates ParksFigure 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 designedfor applications in mobile communications in any environment (COST231 is onlyfor urban environments) and on the other hand, the Okumura-Hata method isonly for frequencies below 1500 MHz Cost-Hata (or Hata, COST231) is a variationof the Hata formula for systems operating at 1,800 MHz and 2,000 MHz , as isthe case at hand.Propagation Models folder in the Modules tab of the browser window assign adifferent formula for each type of clutter map area.The allocation formula is that of Table 16:Zone Type Cost-Hata formulaField (OPEN) Rural (open area)Water (INLAND_WATER) Rural (open area)Residential (RESIDENTIAL) medium-sized city and suburbanUrban average (MEAN_URBAN) Metropolitan CenterUrban sprawl (DENSE_URBAN) Metropolitan CenterBuildings (BUILDINGS) Metropolitan CenterPueblo (VILLAGE) medium-sized city and suburbanIndustrial (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 suburbanTable 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) = (1.1logf - 0.7) H r - (1.56 logf - 0.8)Total = Lu - a (H r) · Rural (almost open):Lu logf = 46.3 + 33.9 - 13.82 logHb + (44.9 to 6.55 logHb) logd to (H r) = (1.1logf - 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):Lu logf = 46.3 + 33.9 - 13.82 logHb + (44.9 to 6.55 logHb) logd to (H r) = (1.1logf - 0.7) H r - (1.56 logf - 0.8)Total = Lu - a (H r) - 4.78 log 2 logf f + 18.33 - 40.94Finally, define Predictions folder as the default method of propagation Cost-Hatawith a resolution according to the resolution of the maps (25 m) and a terminalheight of 1.5 m. This value for the height of the terminal is a typical value usedfor such studies and that implies that all active users are at ground level, ie in theworst case (further away from the base station) .3.4 Network equipment.We will introduce information about the technical characteristics of the computerin your network. These specifications pertain to the equipment described inChapter 4. We will try to model with these teams Atoll as realistic as possible sothat 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 paragraph22.214.171.124 of Chapter 4.Atoll contains a database with some antennas defined by default. We will createa 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 browserwindow.The characteristics of the antenna set are shown in Table 17. Thepatterns of horizontal and vertical filing of the antenna are shown in Figures 16and 17 respectively.Name UD01P_D18BBManufacturer KathreinGain 18 dBiPower Tilt 4ºBeamwidth 63 ºmaximum frequency 2,170 MHzMinimum frequency 1920 MHzTable 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 horizontalplane (3 dB drop at 63 º) the attenuation is 10 dB at 120 º and the attenuationof 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 (seeFigure 17).3.4.2 Base Station.The base station model chosen is the IN-60 from Nortel, whose maincharacteristics will be found in Chapter 4.The characteristics of the base station is included in Atoll in the correspondingdeployment template. In the radio toolbar, select manage staff, make a copy ofan old template and fill it with the specifications of our base station. The selectedparameters are those of Table 18:Number of sectors 3Antenna model UD01P_D18BB 2 Frequency Band ,170 MHzHeight 30 m
base station Noise figure 5 dBPilot Channel Power 33 dBmSCH Power 21 dBmPower other CCH 30 dBmAS Threshold 5 dBMaximum power 43 dBmMaximum load on the DL (peak) 75%The maximum load on the UL 50%Maximum date rate per user at 1,000 KbpsDLMaximum date rate per user at 1,000 KbpsULMaximum number of CEs in the DL channel 256Maximum number of CEs in the UL 256Table 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 thesites 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 telephonenetworks are usually designed for a 2% chance of rejection. We have set aquality goal of 5% for MMS because it has a lower priority than those of theservices 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 themost penalized other services, it is likely therefore to be the most likely to berejected by the network and we may be difficult to obtain high levels ofavailability .We will begin the deployment of sites using the available templates. As most ofthe target area is urban type, we will use the urban insole to begin thedeployment and conduct the first simulations and assessments.The template urban uses hexagonal cells, with 550 m cell radius and a singlecarrier.We deployment of Node Bs throughout the target area, the result is shown inFigure 18:
Figure 18: Deployment design and hexagonal cell radius 550 m.With an array of these features can cover the citys urban core with 36 locations.We will perform a first simulation to gauge whether the cell size and number ofcarriers is adequate or not.Atoll UMTS simulations are based on a Monte Carlo simulator .Since the userdistributions of traffic map Atoll generates a population of users on the map andfor each of these users the simulator executes a power control algorithm for theuplink and downlink.The objective of the algorithm is to minimize interferenceand maximize network capacity.This will restrict the connection to the networkusers who use low-priority services and generate a lot of interference.Thisprocess creates a snapshot of the UMTS network, the result is a distribution ofusers 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 thantheir own cells, but not other phones, and all base station receives interferencefrom their cell phones and other cells, but not the other base stations.
We have already said that UMTS capacity depends on the total receivedinterference. Atoll simulates the power control mechanism using an iterativealgorithm in each iteration, all the population of mobile users generated try to beconnected, one by one, to the network. If certain users penalize others toomobile, they are rejected, with the decision of rejection correlated with servicepriority.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 networkcongestion: · 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 thesynchronization channel, another to control channels and the rest is sharedamong the traffic channels. Unlike the pilot channel and synchronization andcontrol channels, the number of traffic channels and their powers depend on thedata traffic, and is one of the parameters in the simulations is determinedthrough the control algorithm power. The minimum and maximum power oftraffic channels for each service are detailed in Table Services for UMTSParameters.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 groupof several simulations and study the results statistically. By running 10simulations with all restrictions and value the results of the simulation average.The results obtained (on average) are shown in Tables 20-22 (in parenthesesindicates the standard deviation):Traffic requested: Users Active Active Active Inactive on the DL in the UL DL+ UL
Total 3.684,8(68.6) 1.483,8 846 461.4 893.6Voice 2.480,6(57.85) 595.3 593.6 398.1 893.6MMS 136.8(8.28) 67.6 69.2 0 0Internet access 1.005,6 (18.17) 820.9 183.2 1.5 0Video Conference 61.8(9.04) 0 0 61.8 0Table 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 inthe UL (Pmob> Pmob max) 1.2It exceeds the standard maximum power available for trafficChannels in DL (PTCH> PTCH max) 134.9The carrier-interference in the pilot channel (DL) is belowthreshold (Ec / Io <Ec / Io min) 1086Saturation loading in the 635.6 DLRefusal of admission 10.2Table 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+ULServicesTotal 1816(49.3%)(44.4) 459.2 448.4 300.6Voice 1689.5(68.1%)(50.55) 398.1 413.9 268.8
MMS 17.1(12.5%)(4.93) 7.5 9.6 0Internet access 78.7(7.8%)(8.94) 53.6 24.9 0.2Video Conference 31.6(51.1%)(6.76) 0 0 31.6Table 22: Breakdown of courses by the service connectionsWe can also study these models in a more graphic. Figure 19 shows the positionof all the terminals at the time of the simulation are trying to access a serviceand the state found. In this case we see those red and black line that are beingrejected or delayed. Connection RejectionFigure 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 thatindeed most penalized services are the lowest priority (MMS and Internet access)and more specifically the penalty is Internet access, which is what generatesmore interference. As the service requires the highest date rate, is the mosttraffic demand and therefore more traffic channels required and the cell thatneeds more power (generating interference in other phones).
Looking at Table 18, we see that the second cause of rejection is the saturationon the DL. That is, we do not have sufficient traffic channels to meet demand. Inprinciple, the easiest way to increase the number of traffic channels is addingnew carriers.And adding more transmitters also helps that there is more power to distributeamong the traffic channels and may help to improve the quality of the signal,which would also be attacking the main cause of rejection (the carrierinterference 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 meetthe quality objectives. If amply fulfilled, we can reduce the number of carriers inthe cells, to allow for future network expansions. Are met by a small margin, itwould 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 areshown in Tables 23-25.Traffic requested: Users Active Active Active Inactive In the DL in the DL DL+ ULTotal 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 0Internet (14.86)Video 60.5 0 0 60.5 0Conference (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) 1.4It exceeds the standard maximum power available for traffic channelsin DL (PTCH> PTCH max) 106.2The carrier-interference in the pilot channel (DL)is below the threshold (Ec / Io <Ec / Io min) 161.1Saturation load on the DL 487.9Refusal of admission 0.1Table 24: Breakdown of rejected connections as the cause of rejection.
Broken down by services:Users online online online online In the DL in the DL DL+ ULServicesTotal 2943.4(79.5%)(53.1) 905.7 735.7 440.6Voice 2393.3(97%)(58.71) 574.7 575.5 381.7MMS 75.3(57.5%)(9.49) 36.4 38.9 0Internet Access 416.1 (40%)(9.61) 294.6 121.3 0.2Video Conference 58.7(97%)(7.79) 0 0 58.7Table 25: Breakdown of courses by the service connections.In this case we can represent the map of Seville on the results of thesesimulations (Figure 20). Connection RejectionFigure 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 simulationssimultaneously. 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 possibleto cover UMTS to Seville with the cell size.Lets try using the following template available for deployment of UMTS Atoll inareas with high population density. The template dense urban target area dividedinto cells of 350 m radius, the result of covering the urban area of Seville withcells 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 carriersper cell. If we find that the cell size is sufficient we can begin to reduce thenumber of carriers at less charged cells, to give him room for network growthand 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 + ULTotal 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 0The Internet (18,82)Video 61,7 0 0 61,7 0Conference (5,06)Table 26: Demand for a given traffic.Simulation results (18 iterations on average per simulation):Number rejected users 263.3 (7.2%)Exceeding the maximum powerterminal in the UL (Pmob> Pmob max) 0It exceeds the standard maximum poweravailable for traffic channels in the DL (PTCH> PTCH max) 30The carrier-interferencepilot channel (DL) is below the threshold (Ec / Io <Ec / Io min) 3.1Saturation load on the DL 230.2Refusal of admission 0Table 27: Breakdown of rejected connections as the cause of rejection.Brokendown by services:Users online online online online On the DL in the DL DL+ULServicesTotal 3406.6(92.8%)(46.39) 1.239,5 816.5 461.7Voice 2474.9(99.9%)(41.05) 603 583.6 399.4MMS 120.2(89.2%)(10.14) 59.4 60.8 0Internet Access 750.1(75.2%)(15.31) 577.1 172.1 0.9Video Conference 61.4(99.5%)(5.12) 0 0 61.4Table 28: Breakdown of courses by the service connections.In this case we can represent the map of Seville on the results of thesesimulations (Table 23):
Connection RejectionFigure 22: State of the terminal cells of 350 m radius and 3 carriers.The results are still not achieving the quality objectives, so lets try to reduce alittle the size of the cell.Predefined templates Atoll UMTS cell sizes do not allow minors. This is explainedweve made a pretty optimistic traffic modeling (from the point of view of theoperator) to cover our backs and make sure that the network later on stayingsmall.We will define a template image of the dense urban, but with a cell size of 200 m3 carriers. After making the deployment on the map the result is shown in Figure22:
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 + ULTotal 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 0The Internet (29,69)Video 54,67 0 0 54,67 0Conference (4,78)
Table 29: Demand for a given traffic.Simulation results (17.33 average per simulation iterations):Number of users rejected 97 (2.6%)Exceeding the maximum powerterminal in the UL (P mob> P mob max) 0It exceeds the standard maximum available powerfor traffic channels in the DL (P tch> tch P max) 13.33The carrier-interference in the pilot channel (DL)is below the threshold (E c / I o <E c / I or min) 0Saturation load on the DL 83.67Denial of admission 0Table 30: Breakdown of rejected connections as the cause of rejection.Broken down by services:Users online online online online In the DL in the DL DL+ ULServicesTotal 3587(97.4%)(43.18) 1.398,67 823 470.67Voice 2495.67(100%)(16.65) 602.33 583.67 415MMS 122.33(97.6%)(13.72) 61 61.33 0Internet access 914.33(90.7%)(15.37) 735.33 178 1Video Conference 54.67(100%)(4.78) 0 0 54.67Table 31: Breakdown of courses by the service connections.In this case we can represent the map of Seville on the results of thesesimulations. The state of the network shown in Figure 24:
Connection RejectionFigure 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 someroom to try to minimize the cost of the network (number of sites) and reduce thenumber of carriers in some transmitters to provide a network for further marginexpansion.To obtain these results are needed 250 locations.However, many of them are onthe edges of the target area and only use 50% of the surface of some of theircells. It is expected that these sites are not providing service to many users andthe traffic of these users can be taken up by neighboring cells without the degreeof saturation increased significantly.Similarly, there are areas of the map with a density of users / traffic muchsmaller, so small cells do not need to support this traffic.200 m cells are essentialin urban, dense urban buildings and in fact, in previous simulations most of therejected users come from these areas.We rely on that to assume that if we remove the border sites to cover smalltarget area and eliminate some sites open and industrial areas, the probability of
rejection need not be accepted.We dimensioned the network to the rejection inurban areas is acceptable, but in doing so we have oversized the network inother areas.After you delete and add sites several times and repeat the simulations as oftenas 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 areaand those in which only one cell was missed we reoriented the antenna to givecoverage within the area of interest.We have also eliminated some sites of the environments with lower trafficdensity (open area and industrial area). In residential and industrial areas thatare surrounded by dense areas and have maintained those sites that serve asreinforcement to support the traffic of the surrounding areas.We have also reoriented the antenna sites within the village that gave coverageto low traffic areas (such as parks, open type), to strengthen coverage of thesurrounding areas more densely populated.The final configuration results areshown in Tables 32-34: Assets Assets Assets in Inactive Users in DL in UL DL + ULTotal 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 0The Internet 12.1Video 57,5 0 0 57,5 0Conference (8,08)Table 32: Demand for a given traffic.Simulation results (16.75 average per simulation iterations):Number of users rejected 98 (2.7%)Exceeding the maximum powerterminal in the UL (P mob> P mob max) 0It exceeds the standard maximum available power for channelsTraffic on the DL (P tch> tch P max) 13.25The carrier-interference in the pilot channel (DL)is below the threshold (E c / I o <E c / I or min) 0Saturation load on the DL 84.75Refusal of admission 0Table 33: Breakdown of rejected connections as the cause of rejection.Broken down by services:Users online online online online In the DL in the DL DL+ULServicesTotal 3587(97.4%)(43.18) 1.398,67 823 470.67Voice 2463.25(100%)(34.37) 577.75 601 386.5MMS 120.25(98.2%)(11.37) 63 57.25 0Internet access 908.25(90.5%)(4.66) 729 177 2.25Video Conference 57.5(100%)(8.08) 0 0 57.5Table 34: Breakdown of courses by the service connections.Reducing the number of sites by approximately 25% have achieved similar oreven better for some services (MMS). This shows that some of the projected sitesadded nothing to the network and that something as simple as redirecting someantennas to areas of high traffic density can increase the network capacity.This is also confirmed in Figure 26, showing where the terminals are locatedrejected the previous simulations. We see that areas with higher density of sitesare still the highest density of terminals has rejected, while the industrial areajust west of the river has a dozen rejections with only 7 base stations.
Connection RejectionFigure 26: Location of the connections rejected.3.6 Establishment of neighborhoods.Atoll is possible to establish automatically neighborhoods by imposing somerestrictions on certain cells that may be part of a neighborhood. Once establishedneighborhood relations, Atoll easy viewing of neighboring cells on the map, whichallows easy management.The algorithm for automatic assignment of neighboring cells is based on thefollowing 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 Automaticacallocation option, which is in Neighbours option within the cells of the folderoption transmitters of the data tab of the browser window.We will impose the following restrictions on the establishment of neighborhoodalgorithm:Distance between neighboring sites: 1,200 m: in urban areas the distancebetween adjacent sites is around 600 m.But sites that cover open or industrialareas are more isolated, more than about 1,000 of the closest locations. Thisrestriction aims at limiting the number of residents in such locations.Setting amaximum distance of 1,200 meters to ensure that these are neighboring sitesonly closer.Maximum number of neighbors: 20: This restriction is intended for sites in themost populated areas.Each cell is surrounded by a maximum of 6 other cells.Ifeach physical cell Atoll are 3-cell (cell = torque transmitter / carrier) we will have6 x 3 = 18 + 2 (the others carry the same physical cell) = 20. With thisrestriction we make sure that even if more than 20 pairs of transmitter / carrierthat are less than 1,200 meters these are not considered neighbors.Atoll generates a huge table with all the neighbors of each cell. As suchinformation becomes unmanageable will be included in Table 36, which showsonly few cells have a given number of neighbors to see which is approximatelythe average number of neighbors per cellNumber of neighbors Number of cells13 6January 2005 910 269 138 547 137
6 10325 2054 913 172 3Table 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 toassign different codes to a given cell and all cells belonging to its list ofneighbors. The assignment can be done manually for each cell, or automaticallyon all cells or a group of cells. Depending on the allocation strategy may beimposed various restrictions on code groups and domains, defining exceptionalcouples, distances and neighborhoods. At all times you can check the consistencyof the current code assignment on the network under study.In UMTS there are 512 scrambling codes that are distributed in 64 clusters of 8codes. The clusters are numbered from 0 to 63, and codes from 0 to 511.Thecode assignment can be done either manually or automatically. In the secondcase, Atoll provides a mapping tool based on an algorithm that takes into accountthe definition of groups and code domains, as well as additional restrictionsbased on the list of neighboring cells, second neighboring cells, criteria andminimum distance pairs exceptional.First lets create a code for domain Atoll. In the browser window, we willTransmitters | 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 themaximum number of neighbors that we introduced in the calculation algorithmneighborhoods is 20 going to try initially to run the algorithm with 20 codes tosee what it gives. In addition, we have seen that 20 is the number of cells in thespace adjacent to another cell in the area of highest density of sites, so it seemsa reasonable value to start. Table 36 lists the 20 codes are initially elected, in 4groups of 5.Groups Minimum Maximum StepGroup 1 0 4 1Group 2 32 36 1Group 3+ 64 68 1Group 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, inTransmitters | Cells | Primary Scrambling Codes | Automatic allocation.Theassociated dialog box, you can select the parameters that the algorithm takesinto 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 usedifferent code to the neighbors of neighbors to 20 codes was too weak. It doesnot seem advisable to abuse of the codes that way in such a large network.Activate only as constraintsNeighbours and Additional Existing Ec / Io conditions.On the other hand, we have seen that there is distance between neighboringsites if up to 1,200 m. Since it is very critical that we have in our network signalswith power levels of the same order of magnitude using the same code in thesame cell, we will be very restrictive in this regard and set a manifestly greaterreuse distance: 2,000 m.The first execution of the algorithm given error, it was impossible to enforcethese restrictions by using only 20 codes.So groups of 5 were added to thedomain 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 StepGroup 1 0 4 1Group 2 32 36 1Group 3+ 64 68 1
Group 4 96 100% 1Group 5 128 132 1Group 6 160 164 1Group 7 192 196 1Group 8 224 228 1Group 9 256 260 1Group 10 288 292 1Group 11 320 324 1Table 37: Codes of randomization used.With the results of the algorithm, Atoll generates statistics that show the numberof times the algorithm has assigned a specific code (Figure 27) and the numberof 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 atotal 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 theaforementioned value, indeed of the 11 sets of codes we see that there are 6 inall 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 domainconsisting of 11 groups of 5 codes, each group therefore a distinct cluster. Wethen used 11 clusters, each with 3 free codes. Could therefore be added to thenetwork 33 new codes without the need for a new cluster3.8 Study coverageIn this section we will perform a series of studies on the deployed networkcoverage. The aim of these studies is to document graphically the network andverify that the design is adequate.Coverage studies provide us with information on the status of the network at alllocations of the target area. The different types of site surveys that can beperformed 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 theterminal (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 thatthe 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 mobileterminal we have 15 dB of gross margin for fading, so in principle, the signallevel should not be a problem for our network.Study transmitter coverage.This study will cover a different color mark the footprint of each transmitter inthis case we used 10 colors and have been alternating for treating adjacenttransmitters that do not match the same color. The result of the study are shownin Figure 31.Figure 31: Study transmitter coverage.We see the sites in the village, the coverage area roughly coincides with thecorresponding cell, while more isolated sites provide coverage to some areassignificantly higher.Study overlap.This study shows the number of base stations that each point on the map abovethe 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 ofpredictions that we will henceforth always refer to a simulation or set ofsimulations is performed for a terminal, service and mobility determined.We will conduct two studies on the level of interference, one for the majoritycase, telephone and voice terminal and one for the most critical case: terminaltelephone and Internet access.These studies are done to the population generated by the simulation average of10 made for the final configuration of the above.The study for the voice serviceand 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 thesignal level of the site survey in Figure 30.Anyway it should not worry, becauseas explained in Chapter 2, UMTS systems are resistant to interference and due tothe CDMA technology is easy to discriminate between the receptor interferenceand the desired signal. As discussed in the study of signal-interference in thepilot 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 inFigures 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 levelsare even higher. This is because Internet access service requires a higherbandwidth and therefore needs more power transmission in the downlink. Theresults 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 therelationship between E C / I O of the received signals.As in the previous case wehave chosen the population generated by the simulation average of 10simulations.Just as before, we will conduct a study to the most common (and your voice) andfor 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 terminalTable 9 is set threshold E C / I O for all mobilities in -14 dB. We see that virtuallythe entire target area will have values above -15 dB, so in principle confirms theresults of the simulations and we should not just rejection by poor signal qualityfor 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 telephoneterminal.The results are very similar to the voice service, which is logical since thetransmission power in the pilot channel is the same and the interference is thesame for all services.The findings are equivalent to the previous case, we havean Ec / Io above -15 dB throughout the target area, so it is likely that there justrejections 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 thedownlink, taking into account the limited traffic capacity based or active bases.This study is very interesting because it is the mobile that checks are rejectedbecause of network congestion.We know that the power intended for trafficchannels depends on the amount of traffic that has to be handed-over, and if atsome point we have to transmit more power than the maximum, then there istraffic that has to be rejected, for which a running Atoll power control algorithm
that determines how much power goes to each connection and powerconnections are not (are rejected).This study places a test terminal at each location of the target area and see ifyou 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 phoneservice.We see that we can get service at all locations of the target area. This isconsistent with the results of simulations and for the voice service had norejections.We must remember that this does not mean never going to have rejections forthis service. This means that in 10 (which are the times you have repeated thesimulation) we have made snapshots of the network with traffic demand withinthe normal range, there were no rejections.
In exceptional situations, where demand for passenger traffic to grow, such asdisasters, Fair, Easter, New Year ... it certainly will be significant even rejectionrates for voice service.The results of the study for the terminal telephone and Internet access areshown in Figure 38.Figure 38: Study of the service area on the DL for the Internet access servicetelephone terminal.We see that most of the target area can get service, but especially in denseurban areas, there are some locations where our connection attempts would berejected.This confirms the results of the simulations, they gave us half a rejectionrate of 9.5% for this service.Of course, the majority of these rejections wouldoccur 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 limitedpower of the mobile terminal.
The results of the study for the terminal telephone and voice are as shown inFigure 39.Figure 39: Study of the service area in the UL for voice service telephoneterminalIn other mobile communications systems such as GSM or TETRA uplink is usuallymore limiting than the downward, as the need to take small, manageableterminals forces us to take power in the upstream transmission very low and notget compensated designing high sensitivity receivers in base stations.However, our UMTS network behaves the opposite. As seen in Figures 39 and 40get service in the increase in all locations of the target area, which agrees withthe results of the simulations, which gave us 0 rejections excess load on theascendant. This is logical because the Internet access service has a veryasymmetric 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 theother.
Figure 40: Study area in the UL service for Internet access service telephoneterminalStudy 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, sothe results of this study are virtually identical to the study of the service area inthe 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 yourterminalHandover study.This prediction studies the active set of a test mobile located at each point on themap, and renders it according to selected criteria.Let us briefly explain theconcept of the active set in UMTS.In the UMTS system uses a handover mechanism for transferring calledcontinuity, SHO (Soft / Softer Handover).Thanks to universal frequency reuse ispossible to connect the call to the candidate to the handover station beforedisconnecting it from the source station, keeping both links simultaneously forsome time. A call can be supported by the three sectors of a base station and /orby two or more stations. Each of the bases involved keeps in touch with thephone until the attenuation to one of them is excessive, when you leave the linkon that basis. In the uplink, during the handover period continuously, the signaltransmitted by the mobile is detected by the base stations involved, make aselection or combination of demodulated signals. In general, for base stationslocated 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, thephysical proximity to combine the signals (soft hand-off) before demodulation.The set of bases with a mobile is known as the Joint Contact Active (ActiveSet).The maximum number of stations that can be part of the active set of amobile (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 onthe concept of threshold for handover (AS THRESHOLD), defined for each cell inthe table Transmitters | Cells | Open Table.The transmitters that constitute theactive 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 serviceJust as occurred in studies of Ec / Io, these studies are identical for both servicesand 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 of10 simulations of the final configuration.
Figure 44: Study of active Internet services terminal access to yourStudy of interference in the pilot channel.At each pixel indicating whether the number of bases that are received Ec / Ioenough is "excessive" in the sense that exceeds the maximum number of activebases allowed by the choice of mobile terminal.It is appropriate that each location on the network has the maximum number ofactive bases, as this benefits the soft handover, but if we have more bases thanallowed only thing is to get more signal level waste, which translates intointerference.Any signal that arrives at a terminal that is not one of its bases isactive interference.Interference studies conducted in the pilot channel are shown in Figures 45 and46
Figure 45: Study of interference in the pilot channel for the service of Voice ofthe telephone terminal.We hardly have seasons interfering in most locations. This affects very low levelsof 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 servicetelephone terminal.In this case the number of interfering base stations is much higher, which resultsin a rejection rate higher than for voice service (which we have seen in thesimulations).This is because Internet access service is not configured to support softhandover, and therefore any base station exceeds the threshold Ec / Io insteadof 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 objectiveswhen the forecast of subscribers has reached its peak (20% of the inhabitants ofthe city).It is expected that the number of subscribers later years to reach thosenumbers, or you may not even reach these amounts.Have also discussed the difficulties involved for a CDMA system the handoverbetween different frequencies, and that requires working in compressed mode,so they agree to limit as far as possible the areas that must be produced usingvarious carriers.Not seem necessary or desirable then the use of three carriers per cell since thelaunch of the network. The logical thing is to make an initial deployment with asingle carrier per cell into expanding capacity to measure the number ofsubscribers need them.In this section we make a study of how it degrades the quality of network serviceas the number of subscribers increases and substantial improvements are madeas extensions of the building.Atoll can easily simulate such scenarios due to the scaling factor. When thesimulation is allowed to use a parameter called Global Scaling Factor, whichscales the traffic demand by multiplying by the scaling factor.A factor of 0.4means 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 ofthe implementation of the network. As mentioned above, initially carried out thedeployment with a single carrier per sector.1 year after deployment (1 carrier per cell, 10% of subscribers):Online ServicesTotal 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 atfull capacity. This allows us to significantly reduce the initial investment forsetting up the network and guarantees a better initial performance of thenetwork (at work with only one carrier per sector). Avoid oversizing and also getthe network itself to finance its expansion of capacity, since the network isoperational and therefore billing from day one. Besides the capacity expansion ofthe network are zero-risk investment, because traffic is rejected and the moneywe lose the ability to increase income means increasing systematically.2 years after deployment (1 carrier / cell, 20% of subscribers):Services OnlineTotal 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)Video Conference 13.9 (100%) (2.07)Table 39: Connections accepted by the network (20% of users and 1 carrier).Quality objectives continue to be met comfortably 2 years after completion of thedeployment. In addition to reducing the investment required for implementationof the network, another advantage of not displaying all the carriers from theinitial moment is that you avoid the wear suffered all these carriers to beoperational, thus prolonging the life of the network andMinimizing the number of failures in the network (unless carriers, lower failurerate). This also saves on maintenance and improvement in the quality of networkservice.3 years after deployment (1 carrier / cell, 30% of subscribers):Services OnlineTotal 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)Table 40: Connections accepted by the network (30% of users and 1 carrier).We see that in this case the quality objectives are met by a small margin. It isclear that during the 3 rd year of operation of the network will have to start to bethe first expansion of capacity, adding a carrier in the most loaded (which willprobably 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 allcells).We will simplify and as we have done until now we demand that qualityobjectives are met in all cells, but only at the entire network (most operators donot or globally).We will not make the expansion of capacity in a progressivemanner, which would be optimal. Lets go on pretending until the qualityobjectives are no longer met, at which will double the network capacity byadding a carrier to all sectors.4 years after deployment (1 carrier / cell, 40% of subscribers):Services OnlineTotal 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)Table 41: Connections accepted by the network (40% of users and 1 carrier).As expected, after 4 years of operation of the network of low priority serviceshave fallen below the quality objectives.It is therefore the time of the firstexpansion of network capacity. Adding one carrier per sector the results of thesimulations are:4 years after deployment (2 carriers / cell, 40% of subscribers):Services OnlineTotal 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 fewmore years before needing a new extension.5 years after deployment (2 carriers / cell, 50% of subscribers):Services OnlineTotal 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)Video Conference 29.88 (100%) (3.95)Table 43: Connections accepted by the network (50% of users and 2 carriers).Quality objectives continue to be met satisfactorily. However, it is normal at 5years 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 spendabout 10 years and that 5 is normal to migrate to an intermediate technology. Infact, 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) .With this new technology, it is possible that the capacity expansion planningwhen otherwise it would be appropriate to consider that if the capacity expansionthat migration brings is enough to meet increased traffic demand or need tocontinue to deploy carriers. Anyway, HSDPA escapes the objectives of thisproject, so it is going to plan the expansion of capacity without regard tomigration.6 years after deployment (2 carriers / cell, 60% of users):Services OnlineTotal 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)Video Conference 37.5 (100%) (4.57)Table 44: Connections accepted by the network (60% of users and 2 carriers).Already beginning to be seen again as the increase in the number of subscribersis gradually degrading the quality of service.However, following the sameapproach as before, not to simulate 3 carriers to fall below the quality objectives.7 years after deployment (2 carriers / cell, 70% of users):Services OnlineTotal 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)Video Conference 42.8 (100%) (5.74)Table 45: Connections accepted by the network (70% of users and 2 carriers).We see that for some, but have fallen back below the quality objectives. It istherefore the time of the last upgrade of the capacity of our network.7 years after deployment (3 carriers / cell, 70% of capacity):Services OnlineTotal 2523.8 (98.6%) (65.56)Voice 1728 (100%) (30.05)MMS 96.6 (98.4%) (10.97)Internet Access 654 (95.3%) (33.24)Video Conference 45.2 (100%) (5.42)Table 46: Connections accepted by the network (70% of users and 3 carriers).As we expected, with 70% of the number of subscribers and the network to itsmaximum capacity exceeded the targets.Little else is there to comment, Tables 39, 40 and 41 show the simulation resultsfor 80%, 90% and 100% of the number of subscribers expected.8 years after deployment (3 carriers / cell, 80% of users):
Services OnlineTotal 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)Video Conference 49.4 (100%) (10.25)Table 47: Connections accepted by the network (80% of users and 3 carriers).9 years after deployment (3 carriers / cell, 90% of users)Services OnlineTotal 3201.5 (97.9%) (52.41)Voice 2187 (100%) (36.4)MMS 119.75 (97.6%) (9.6)Internet Access 847 (92.8%) (30.85)Video Conference 47.75 (100%) (6.87)Table 48: Connections accepted by the network (90% of users and 3 carriers).10 years after deployment (3 carriers / cell, 100% of users):Services OnlineTotal 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)Video Conference 57.5 (100%) (8.08)Table 49: Connections accepted by the network (100% of users and 3 carriers).This raises the question of what to do after 10 years when the number ofsubscribers 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 whenthese networks were planned just as GPRS (2.5 G) served as a bridge betweenGSM (2G) and UMTS (3G) technologies appear to provide increased capacity of
UMTS, HSDPA and HSPA already in operation, 5 years after the launch of UMTSin Seville and there is talk that it is possible the emergence of the first 4Gnetwork in the United States later this year .The evolution of technology is virtually unpredictable and as I said before is notthought advisable to design networks that will be in operation for many yearsmay become obsolete before starting to recover its investment. 4 G may begin toappear at any time between 2008 and 2012. This means that a UMTS network inSeville may have a lifespan of well over 10 years, and if it turns out, are alwaysbridges to support technologies that increase in traffic demand.