TALLINNA TEHNIKAÜLIKOOL Raadio- ja sidetehnika instituut Kood: IRT80LT WCDMA RAADIOVÕRGU PLANEERIMINE LÄHTUVALT OLEMASOLEVAST GSM VÕRGUST WCDMA RADIO NETWORK PLANNING BASED ON EXISTING GSM SITE REUSE Jevgeni Okuško Töö on tehtud telekommunikatsiooni õppetooli juures Juhendaja: Avo Ots Kaitsmine toimub Infotehnoloogia teaduskonna kaitsmiskomisjonis Autor taotleb tehnikateaduste magistri nimetust Esitatud: 30.11.2006 Kaitsmine: 11.12.2006 Tallinn 2006

2

REFERAAT Tänapäeval on klientide ootused ja drastiliselt kasvanud nõudmised erinevate mobiiliside teenuste järele sundinud mobiilside tööstust pöörama oma pilgud teiselt mobiilside generatsioonilt kolmandale. Olenemata faktist, et teise generatsiooni mobiilside tehnoloogia ikka veel areneb ja turule tuuakse uusi teenuseid on suur osa mobiilside operaatoreid alustanud kolmanda generatsiooni võrkude rajamisega. Euroopa Telekommunikatsiooni Standardite Instituut (ETSI) valis kolmanda generatsiooni mobiilside süsteemi raadioliidese standardiks WCDMA Laiaribaline koodidega eraldatud mitmekordne juurdepääs. WCDMA on mõeldud ja arendatud pakkumaks suurematel andmedastuskiirustel põhinevaid multimeedia teenuseid, kui see on võimalik teise generatsiooni süsteemides. Koos muutustega võrgu infarstruktuuris toob WCDMA ka uue lähenemise raadiovõrgu planeerimisse, lisades sinna uusi väljakutseid. Kui teise generatsiooni raadiovõrkude planeerimine on peamiselt tehtud katvuse printsiipi jälgides, siis kolmanda generatsiooni võrkude planeerimise juures on liskaks katvusele oluline ka interferentsi ja mahu analüüs. Teisisõnu on kolmanda generatsiooni raadiovõrkude planeerimisel vaja samaaegselt arvesse võtta palju enam faktoreid . Seega on tugijaamde konfiguratiooni optimeerimine alates tugijaama asukohast ja lõpetades antenni tüübiga, -suuna ja –allakallutusega väga oluline täitmaks teenuse ja mahu nõudeid. Käesolev magistritöö on esitatud 68 leheküljel, sisaldab 33 joonist ja 17 tabelit ja on kirjutatud inglise keeles. Märksõnad: WCDMA, GSM, raadiovõrkude planeerimine, mahtuvuse dimensioneerimine, katvuse dimensioneerimine, raadiovõrgu planeerimise tarkvara simulatsioonid.

3

PREFACE Nowadays customer expectations and drastically growing demand of different mobile services push the whole mobile communication industry to focus on radio access technology evolution from the second generation towards the third generation. Despite the fact that 2G mobile networks still evolve and bring new services into the market, great number of operators started to deploy 3G networks. European Telecommunications Standards Institute (ETSI) selected Wideband Code Division Multiple Access (WCDMA) as a multiple access technique for the radio interface in the 3rd generation mobile telephone communication systems. WCDMA has been specified and developed to enable advanced multimedia services using significantly higher bit rates than the current 2nd generation systems. Together with providing changes in the network infrastructure, WCDMA brings a new approach in the radio network planning process, promising a number of challenges on the way to 3G. If in the case of the 2nd generation, radio planning is based on coverage optimization, then there is more interference and capacity analysis than just coverage area estimation in 3rd generation planning. In other words, 3G-network planning is based on the fact that a lot of issues should be considered simultaneously. Thus, the site configurations’ optimization, starting from site locations and finishing with antenna type, directions and tilts, takes on special significance to meet capacity and service requirements. Current thesis is presented on 68 pages, containing also 33 illustrations and 17 tables and is written in English language. Keywords: WCDMA, GSM, radio network planning, capacity dimensioning, coverage dimensioning, radio planning tool simulations.

4

TABLE OF CONTENTS

REFERAAT ..................................................................................................................................................... 2

PREFACE ........................................................................................................................................................ 3

LIST OF FIGURES......................................................................................................................................... 6

LIST OF TABLES........................................................................................................................................... 7

USED ABBREVIATIONS .............................................................................................................................. 8

INTRODUCTION ......................................................................................................................................... 10

1 WCDMA OVERVIEW ......................................................................................................................... 11 1.1 WCDMA AIR INTERFACE ................................................................................................................. 11 1.2 WCDMA RAN ARCHITECTURE ......................................................................................................... 12

2 RADIO NETWORK PLANNING........................................................................................................ 14 2.1 PLANNING PROCESS .......................................................................................................................... 14 2.2 RADIO PROPAGATION MODELING ...................................................................................................... 15

2.2.1.1 Fast and slow fading ............................................................................................................................15 2.2.1.2 Properties of wideband radio channel ..................................................................................................16 2.2.1.3 Okumura-Hata model...........................................................................................................................17 2.2.1.4 The COST 231 Walfisch-Ikegami model.............................................................................................19

2.3 NETWORK DIMENSIONING ................................................................................................................. 22 2.3.1 Traffic estimation ..................................................................................................................... 23 2.3.2 Definitions................................................................................................................................ 23

2.3.2.1 Radio access bearers ............................................................................................................................23 2.3.2.2 Activity factor and DTX gain...............................................................................................................25 2.3.2.3 Channel models....................................................................................................................................26

2.3.3 Radio link budget ..................................................................................................................... 27 2.3.3.1 Margins ................................................................................................................................................27 2.3.3.2 Uplink link budget ...............................................................................................................................30 2.3.3.3 Downlink link budget...........................................................................................................................33

2.3.4 Capacity calculations............................................................................................................... 36 2.3.4.1 Uplink capacity ....................................................................................................................................36 2.3.4.2 Downlink capacity ...............................................................................................................................37 2.3.4.3 Soft capacity.........................................................................................................................................39

3 DETAILED PLANNING ...................................................................................................................... 40 3.1 ANTENNA CONFIGURATION ............................................................................................................... 40

3.1.1 General .................................................................................................................................... 40 3.1.2 Antenna height ......................................................................................................................... 40 3.1.3 Antenna beamwidth selection and sectorization ...................................................................... 41 3.1.4 Antenna downtilt ...................................................................................................................... 42

3.1.4.1 Mechanical downtilt.............................................................................................................................42 3.1.4.2 Electrical downtilt ................................................................................................................................43

3.1.5 Soft and softer handover .......................................................................................................... 44 3.1.5.1 Softer handover factor..........................................................................................................................44 3.1.5.2 Pilot pollution.......................................................................................................................................45

3.1.6 Antenna directions ................................................................................................................... 45 3.1.6.1 Coverage overlap between adjacent sectors .........................................................................................45

3.2 CAPACITY AND COVERAGE PLANNING .............................................................................................. 46 3.2.1 Planning tool............................................................................................................................ 46

3.2.1.1 Monte Carlo analysis of TEMS Cell Planner Universal.......................................................................48 3.2.1.2 Load estimation....................................................................................................................................49

4 STUDY CASE ........................................................................................................................................ 51 4.1 SIMULATION ENVIRONMENT ............................................................................................................. 51

4.1.1 General simulation parameters ............................................................................................... 53 4.1.2 Traffic density information....................................................................................................... 53

5

4.2 SIMULATION RESULTS ....................................................................................................................... 54 4.2.1 First scenario ........................................................................................................................... 54

4.2.1.1 CPICH coverage ..................................................................................................................................54 4.2.1.2 Soft handover probability.....................................................................................................................55 4.2.1.3 Influence of spacing between adjacent sectors.....................................................................................57 4.2.1.4 Statistics report.....................................................................................................................................58

4.2.2 Second scenario ....................................................................................................................... 59 4.2.2.1 CPICH coverage ..................................................................................................................................60 4.2.2.2 Soft handover probability.....................................................................................................................61 4.2.2.3 Soft handover probability.....................................................................................................................62

5 KOKKUVÕTE....................................................................................................................................... 64

6 CONCLUSION ...................................................................................................................................... 65

7 REFERENCES....................................................................................................................................... 66

A. LOG-NORMAL FADING MARGINS ............................................................................................ 68 A.1 SIMULATED LOG-NORMAL FADING MARGINS FOR 3-SECTOR SITES, MULTI-CELL ENVIRONMENT....... 68

6

LIST OF FIGURES FIGURE 1.1 WCDMA FREQUENCY BAND ALLOCATION [12]............................................................................. 11 FIGURE 1.2 UMTS DEPLOYMENT [12]. ............................................................................................................. 12 FIGURE 1.3 WCDMA RAN ARCHITECTURE. .................................................................................................... 13 FIGURE 2.1 SIGNAL STRENGTH VARIATIONS [12].............................................................................................. 16 FIGURE 2.2 FADING WIDTH VS. THE PRODUCT OF DELAY SPREAD AND SYSTEM BANDWIDTH............................ 16 FIGURE 2.3 OKUMURA SET OF CURVES. ............................................................................................................ 17 FIGURE 2.4 SITE AREA DEFINITION. .................................................................................................................. 19 FIGURE 2.5 WALFISCH-IKEGAMI MODEL PARAMETERS..................................................................................... 20 FIGURE 2.6 DEFINITION OF STREET ORIENTATION ANGLEϕ............................................................................... 21 FIGURE 2.8 RADIO ACCESS BEARER (RAB) DEFINITION.................................................................................... 23 FIGURE 2.9 LINK BUDGET. ................................................................................................................................ 27 FIGURE 2.10 THE CUMULATIVE NORMAL DISTRIBUTION FUNCTION [12]. ......................................................... 28 FIGURE 2.11 COVERAGE AREA ACCORDING TO JAKE’S FORMULA [12]. ............................................................ 29 FIGURE 2.12 NOISE RISE. .................................................................................................................................. 37 FIGURE 2.13 SOFT CAPACITY IN WCDMA [16]................................................................................................ 39 FIGURE 3.1 FIRST FRESNEL ZONE. .................................................................................................................... 41 FIGURE 3.2 PRACTICAL ANTENNA RADIATION PATTERNS. (A)33° HORIZONTAL ANTENNA BEAMWIDTH,(B) 65°

HORIZONTAL ANTENNA BEAMWIDTH [26]................................................................................................. 41 FIGURE 3.3 EFFECT OF WIDENING OF THE HORIZONTAL RADIATION PATTERN IN CASE OF INCREASING

MECHANICAL DOWNTILT VALUE [29]........................................................................................................ 43 FIGURE 3.4 HORIZONTAL RADIATION PATTERN IN CASE OF USING ELECTRICAL ANTENNA TILT [17]. ............... 44 FIGURE 3.5 COVERAGE OVERLAP BETWEEN ADJACENT SECTORS...................................................................... 46 FIGURE 3.6 PLANNING TOOL SIMULATIONS APPROACH..................................................................................... 47 FIGURE 3.7 TCPU SIMULATIONS’ STEPS [35].................................................................................................... 48 FIGURE 4.1 FIRST SCENARIO NETWORK PLAN. .................................................................................................. 51 FIGURE 4.2 SECOND SCENARIO NETWORK PLAN. .............................................................................................. 52 FIGURE 4.3 CPICH COVERAGE PLOT (1ST SCENARIO)........................................................................................ 54 FIGURE 4.4 REAL VS. AVERAGE ANTENNA HEIGHT OF THE SITES. ..................................................................... 55 FIGURE 4.5 IRREGULAR ANTENNA DIRECTIONS. ............................................................................................... 56 FIGURE 4.6 HANDOVER MAP (1ST SCENARIO). ................................................................................................... 56 FIGURE 4.7 CORRELATION BETWEEN ADJACENT SECTOR SPACING AND SHO PROBABILITY. ............................ 58 FIGURE 4.8 DOWNLINK LOADING (1ST SCENARIO). ............................................................................................ 59 FIGURE 4.9 CPICH COVERAGE PLOT (2ND SCENARIO). ...................................................................................... 60 FIGURE 4.10 HANDOVER MAP (2ND SCENARIO).................................................................................................. 61 FIGURE A.1 LOG-NORMAL FADING MARGINS FOR 3-SECTOR SITES ................................................................... 68

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LIST OF TABLES TABLE 1.1 WCDMA TECHNICAL CHARACTERISTICS........................................................................................ 11 TABLE 2.1 UMTS QOS CLASSES ...................................................................................................................... 24 TABLE 2.2 RADIO ACCESS BEARERS. ................................................................................................................ 25 TABLE 2.3 DTX GAIN [12]................................................................................................................................ 26 TABLE 2.4 MAPPING OF CHANNEL MODEL TO UE SPEED [12]. .......................................................................... 26 TABLE 2.5 UPLINK LOG-NORMAL FADING MARGINS FOR 3-SECTOR SITES (HANDOVER GAIN INCLUDED).......... 29 TABLE 2.6 UPLINK LINK BUDGET...................................................................................................................... 32 TABLE 2.7 DOWNLINK LINK BUDGET................................................................................................................ 35 TABLE 4.1 SIMULATION PARAMETERS. ............................................................................................................ 53 TABLE 4.2 TRAFFIC DATA INPUT PER SERVICE. ................................................................................................. 53 TABLE 4.3 LOAD LEVEL OF SERVICES PER CELL................................................................................................ 53 TABLE 4.4 WORST SOFT HANDOVER PROBABILITY CELLS................................................................................. 57 TABLE 4.5 STATISTICAL RESULTS FOR SYSTEM PARAMETERS (1ST SCENARIO). ................................................. 58 TABLE 4.6 COMPARISON OF COVERAGE AREAS OF 1ST AND 2ND SCENARIOS....................................................... 60 TABLE 4.7 COMPARISON OF HANDOVER PROBABILITIES OF 1ST AND 2ND SCENARIOS. ........................................ 62 TABLE 4.8 STATISTICAL RESULTS FOR SYSTEM PARAMETERS (2ND SCENARIO).................................................. 62 TABLE 4.9 AMOUNT OF SERVED USERS (1ST VS. 2ND SCENARIOS). ...................................................................... 63

8

USED ABBREVIATIONS 2G - The 2nd Generation of Mobile Networks 3G - The 3rd Generation of Mobile Networks 3GPP - The 3rd Generation Partnership Project AGL - Antenna Height above Ground Level AMR - Adaptive Multi Rate AS - Active Set ASC - Antenna System Controller BCCH - Broadcast Control Channel BPSK - Binary Phase Shift Keying BS - Base Station CCH - Control Channels CDMA - Code Division Multiple Access CN - Core Network COST - Cooperative Scientific Research CPICH - Common Pilot Control Channel CPL - Car Penetration Loss CS - Circuit Switched DCCH - Dedicated Control Channel DL - Downlink DS-CDMA - Direct-Sequence Code Division Multiple Access DTCH - Dedicated Traffic Channel DTX - Discontinuous Transmission ETSI - European Telecommunication Standards Institute FACH - Forward Access Channel FDD - Frequency Division Duplex GSM - Global System for Mobile communications HO - Handover HSDPA - High Speed Downlink Packet Access HSUPA - High Speed Uplink Packet Access HT - Hilly Terrain KPI - Key Performance Indicator LOS - Line-Of-Sight MS - Mobile Station NLOS - Non-Line-Of-Sight PDF - Probability Density Function QoS - Quality of Service QPSK - Quadrature Phase Shift Keying PS - Packet Switched P-SCH - Primary Synchronization Channel RA - Rural Area RAB - Radio Access Bearer RB - Radio Bearer RBS - Radio Base Station RET - Remote Electrical Tilt RNC - Radio Network Controller RF - Radio Frequency S-SCH - Secondary Synchronization Channel SHO - Soft Handover SRB - Signaling Radio Bearer

9

TDMA - Time Division Multiple Access TEMS - Test Mobile Station TCPU - TEMS Cellplanner Universal TDD - Time Division Duplex TMA - Tower Mounted Amplifiers TU - Typical Urban UE - User Equipment UL - Uplink UMTS - Universal Mobile Telecommunications System UTRAN - UMTS Terrestrial Radio Access Network WCDMA - Wideband CDMA, Code Division Multiple Access

10

INTRODUCTION Nowadays co-siting of 3G sites with the existing 2G sites help to significantly reduce costs and speed up WCDMA deployment. However, very often co-siting can introduce a number of issues that need to be considered. Apparent cost savings can come back as an ineffective network plan with wasted radio resources and money as a consequence. This could be a result of blindly copying an existing 2G network for the WCDMA network planning, which is strongly discouraged due to differences in the planning approaches for the two different technologies. Current paper covers the radio network planning of a new 3G network based on an existing GSM network’s radio plan. The main differences between radio planning approaches in GSM and WCDMA in order to avoid dramatic network performance deterioration by following inappropriate “old-fashioned” radio planning principles are considered. A general overview of the WCDMA technology characteristics and features as well as the WCDMA radio access network (RAN) architecture are provided in Chapter 1. Chapter 2, firstly, highlights the main principles of the WCDMA radio planning process, split into a few major sub-processes described further in more detail. Secondly, the main principles of radio propagation modeling with descriptions of the most common models used in urban environments have been presented. Finally, WCDMA radio link budget calculations together with capacity dimensioning methodology are addressed in this chapter. As mentioned above, GSM radio planning principles can no longer be valid for WCDMA radio planning to certain extent. If in case of low traffic areas, WCDMA radio planning is quite similar with GSM radio planning, then in high traffic scenarios this similarity disappears. The reason is that, there is no clear split between coverage, capacity and interference planning in WCDMA radio planning. Chapter 3 highlights the most important aspects of detailed planning. The output is worked out methodology of radio network design based on initial minimization of the harmful effects of excessive coverage overlap and soft handover probability by means of antenna re-directions, changes of angles between adjacent sectors and electrical tilt optimization. In addition, the main functionality of Monte-Carlo analysis of TEMS Cellplanner Universal (TCPU) planning tool, used for case study simulations, has been described in Chapter 3. Two different radio planning scenarios, performed by TCPU tool, are being investigated in Chapter 4. In the first scenario, the 3G network based “purely” on the existing GSM network’s radio is investigated. In the second scenario, a modified plan, according to the planning methodology worked out in Chapter 3, is presented. Coverage and traffic statistics of both networks as well as simulation results plots, showing network performance, interference and pilot pollution, are presented and analyzed. The influence of proper site configuration choice on network performance is studied. Chapters 5 and 6 conclude the thesis along with providing some assumptions and recommendations.

11

1 WCDMA OVERVIEW 1.1 WCDMA AIR INTERFACE WCDMA (Wideband Code Division Multiple Access) is a wideband Direct-Sequence Code Division Multiple Access radio interface technology. It has been selected as a radio transmission technology for UMTS (Universal Mobile Telecommunications System), which is the European third generation mobile Communications system developed by ETSI (European Telecommunications Standards Institute). WCDMA has become the most popular global 3G air interface mode within the last few years. It has been actively implemented by existing GSM operators across the world.

Figure 1.1 WCDMA frequency band allocation [12].

The main technical characteristics of WCDMA are shown in the table below:

Table 1.1 WCDMA technical characteristics. Multiple Access Scheme DS-CDMA Duplex Scheme FDD/TDD Carrier spacing 5 MHz Chip rate 3.84 Mcps Frame length 10 or 20 ms (optional) Multirate Variable speading and multicode Data modulation QPSK (downlink)

BPSK (uplink) Spreading factors 4-512 Power control Open and fast closed loop Handover Soft and interfrequency handover

The main WCDMA features and advantages can be presented as follows: • Same frequency time domain for all users • Users separated by orthogonal codes • Frequency Division Duplex (FDD) and Time Division Duplex (TDD) modes • Chip rate of 3.84 Mbps within a 5 MHz frequency band • Multi circuit and packet-switched high bit-rate services • Simultaneous operation of mixed services

frequency 5 MHz (WCDMA)

time

code

12

• Highly variable user data rates based on the rate matching procedure (HSDPA and HSUPA)

• Asynchronous base stations • Coherent detection on downlink and uplink • Inter-system handover with GSM • Soft/softer inter-frequency handover 1.2 WCDMA RAN ARCHITECTURE The main goal of UMTS is to deliver new high data rate services to the user in the mobile domain. This new technology requires a wide frequency band of between 5 MHz and 15 MHz (compared with a 200 kHz carrier for GSM), which has an impact on both radio and core network architecture (see Figure 1.2).

Figure 1.2 UMTS deployment [12]. A WCDMA network can be overlaid onto an existing GSM network, and in so doing this can help to achieve significant savings on operator infrastructure investment. This paper is focused on the WCDMA radio network planning issues. The WCDMA radio access network (RAN) architecture is shown in Figure 1.3. WCDMA RAN consists of one or more radio network subsystems (RNS), which in turn consists of 2 main network node types:

• The radio network controller (RNC) exercises radio network control functions on radio base stations (RBSs) and user equipment (UE). It comprises a number of end-user services such as: mobile telephony, packet data (including HSDPA), short message service (SMS), ciphering and mobile positioning. It also provides end-user functions: radio access bearer (RAB) (see Section 2.3.2.1), mobility (cell reselection, handover, macro diversity and location update), radio resource management, connection control and capacity management.

• The radio base station (RBS) provides radio resources for the RAN, i.e. it handles the user data traffic and control communication with the RNC and the UE.

GSM operator

UMTS operator Other UMTS operator

f 4.4 MHz 5.0 MHz 5.0 MHz 3 MHz

2.7 + 4.4 + 5.0 + 2.5 = 14.6 MHz

Macro layer Micro layer

13

Communication between UTRAN nodes goes through a number of external interfaces:

• Iu: Interface between an RNC and the Circuit Switched / Packet Switched Core Networks. The interface is used for traffic related signaling.

• Iub: Interface between an RNC and an RBS used for traffic related signaling. • Uu: Interface between an RNC and a UE. • Mub/Mur: Management interface provided by the RBS/RNC. It is used for

element management and network management. • Iur: This interface is between two different RNCs. The interface is used for user

data and control related signaling

Figure 1.3 WCDMA RAN architecture. Operation and Maintenance functionality is handled through the embedded management in RNC and RBS as well as software solutions [12]:

• Radio Access Network Operation Support (RANOS): operates the WCDMA RAN including coordinated handling of tasks on multiple network elements.

• Tools for Radio Access Management (TRAM): tool-set for planning, design, test and performance monitoring.

14

2 RADIO NETWORK PLANNING Radio network planning is a very time consuming and labor-intensive procedure. The quality of network planning has a direct impact on an operator’s future income. WCDMA technology in particular has set new requirements for radio planning and has created the need for a new planning approach. The reason for that are fundamental differences between 2G and 3G technologies. A WCDMA-based system is a multiservice environment with variable rates for its users using the same frequency simultaneously. The number of active users and type of services used has a direct influence on the coverage of the cell, which means that coverage and capacity planning can’t be separated into phases and should be considered at the same time. This well-known phenomenon is called “cell breathing” and shows strong dependency of coverage and capacity on each other. Despite the differences in the planning approaches of the two technologies, utilization of existing GSM sites by operators is very important in speeding up 3G network deployment. If an operator has an already existing GSM network then use of existing infrastructure can sufficiently minimize WCDMA network deployment expenses. Besides co-siting (using already existing GSM sites’ locations), similar to existing GSM network cell plan (as similar as possible in WCDMA and GSM, i.e. antenna positions, heights, directions and tilts) will most likely be used in a large extent. However, blind copy of existing GSM1800 network plan, for instance, should be avoided. 2.1 PLANNING PROCESS The overall goal of the radio network planning is to maximize the coverage and capacity while meeting key performance indicators (KPIs) and quality of service (QoS) requirements. In general, a radio network planning consists of three major phases: • Dimensioning

- area definition - link budgets and coverage analysis - traffic and capacity estimation - estimation of number of base stations required

• Detailed planning

- site configurations (site locations, heights, azimuths, tilts etc.) - traffic estimations - code and frequency planning - coverage thresholds and capacity requirements - parameters settings

• Optimisation and monitoring

- network tuning (parameters settings adjustment) - coverage and capacity verification - traffic measurements

It can be easily noticed that the traffic level has to be continuously taken into account at all the radio planning stages. The distribution of the traffic between different services must be determined for each base station coverage area as precisely as possible. Ideally, exact

15

location of the users has to be known, which is obviously almost impossible to obtain in reality. However, the more accurate users’ distribution forecast the better radio network design can be done. Radio base station locations should be placed on the traffic hot spots in order to obtain the best link budget for the mobile users served by a particular RBS. It might significantly reduce power consumption in the network, which decreases interference level and increases capacity. Existing GSM network statistics can be good support in rough traffic estimations in 3G radio planning. As a rule, in the initial dimensioning phase, a fixed predicted during busy hour load defined for all the base stations in the planned area. However, in the detailed planning phase, traffic distribution might be used in order to allocate the traffic to the particular cells. Thus, in some cases the load between the cells can vary dramatically. Coverage targets also should be carefully checked during detailed planning phase. It must be kept in mind that the traffic distribution is assumed to be homogeneous in the particular areas during dimensioning phases. Also, propagation is assumed to be similar for all the cells. However, the fact that traffic density of the particular areas might be quite different must be considered. Moreover, coverage predictions can be very different across the planned network due to propagation environment and traffic distribution. Before we can proceed with the network dimensioning process consideration, the main principles of radio propagation modeling together with well-known models’ basics, used for dimensioning and predicting in urban environment, should be understood.

2.2 RADIO PROPAGATION MODELING 2.2.1.1 Fast and slow fading Fading is quite typical for urban environments when there is no line-of-sight path between the transmitter and the receiver. Shadowing from obstacles in the propagation path will cause log-normal fading. Due to multiple reflections, radio waves travel along different paths of varying lengths, causing effect of fast fading. High building density causes severe diffraction loss. In addition, the path loss, i.e. the decrease of the global mean value of the signal strength, is one more component that will affect the received signal strength. Further (in sections 2.2.1.3 and 2.2.1.4) the two most common models for path loss estimations in terms of urban environments have been considered. Thus, in general, the mobile radio channel can be characterized by three major signal components:

• Fast fading, e.g. Rayleigh distributed • Slow fading or log-normal fading • Path loss

16

Figure 2.1 Signal strength variations [12]. 2.2.1.2 Properties of wideband radio channel The main advantage of a wideband radio channel is that the fast fading decreases with the increase of the system bandwidth. An empirical relationship how the fading width varies with the system bandwidth and the delay spread is shown in Figure 2.2 [6].

(Delay spread) × (system bandwidth)

Fadi

ng w

idth

[dB

]

Figure 2.2 Fading width vs. the product of delay spread and system bandwidth. The fading width is directly proportional to the average difference between the values of the peaks and the dips in dB. It is defined as the difference between 99 % and 1 % levels of the cumulative distribution function of the measured signal strength values. The delay spread shows the spread of the propagation paths in the time domain. If the delay spread is assumed to be constant (a typical value for urban environment is 0.5 μs), the fading width will decrease with the increase of the bandwidth. Thus, according to

17

Figure 2.2, for GSM systems with a bandwidth of 200 kHz, the fading width would be 22 dB, while it would decrease to 9 dB for WCDMA systems with a bandwidth of 5 MHz. 2.2.1.3 Okumura-Hata model Usually, the propagation loss is calculated by means of different propagation models. The most common is the Okumura-Hata propagation model, which is based on the Okumura method and considers several parameters such as effective antenna height, terrain type, terrain height, frequency, and so on. The Okumura method is semi-empirical and based on extensive measurements performed in the Tokyo area [9]. The results are expressed in the sets of curves, showing field strength as a function of distance for different frequencies and antenna heights. See example of Okumura set of curves in Figure 2.3.

Figure 2.3 Okumura set of curves. The formulas for analytical calculations have been derived from Okumura curves by Hata. Path loss, maxpL , can be found as:

18

RhhahfL bmbp log)log55.69.44()(log82.13 26.16log69.55max ⋅−+−−+= (2.1)

where f - the signal frequency,

bh - the effective antenna height of the base station, )( mha - the correction factor,

mh - the mobile terminal height, R - the cell range. The cell range, R, is the distance corresponding to the maximum allowed path loss, Lpmax. The correction factor, a(hm), for urban areas (small and medium size cities) can be found as follows [15]:

8.0log56.1)7.0log1.1()( +−⋅−= fhfha mm (2.2) For the large cities, a(hm) is:

( ) ( )[ ]( )[ ]⎩

⎨⎧

≥−≤−

=MHz40097.475.11log2.3MHz20010.154.1log29.8

2

2

fhfhha

m

mm (2.3)

It must be noted that a(hm) is fixed to 0 dB in case of hm = 1.5m, which is the most common height for cellular radio system calculations. Equation 2.1 can be slightly modified:

RhhAL bbp log)log55.69.44(log82.13max −+−= (2.4) where A - semi-empirical constant (155.1 for urban area, used in calculations, Table 2.6 and Table 2.7)

bh - the antenna height of the base station (35m in calculations, Table 2.6 and Table 2.7). According to equation (2.4), the cell range can be found as:

α10=R (2.5) where

( )b

mbpmax

hhahAL

log55.69.44log82.13

−++−

=α (2.6)

Thus, the coverage area of the cell can be defined as:

19

2389_ RareaSite = (2.7)

Figure 2.4 Site area definition. The model is well suited for the following conditions: • 150 ≤ f ≤ 1500 MHz • 1 ≤ R ≤ 20 km • 30 ≤ hb ≤ 200 m • 1 ≤ hm ≤ 10 m

Different variants of the Okumura-Hata model are implemented in the various radio planning tools. 2.2.1.4 The COST 231 Walfisch-Ikegami model The COST 231 Walfisch-Ikegami model is a combination of the models from J. Walfisch and F. Ikegami. It was further developed in terms of the COST 231 project. COST 231, “Evolution of land mobile radio (including personal) communications”, is a subgroup of a European Union forum for cooperative scientific research. COST 231 has been later continued by COST 259. The model considers the buildings between the transmitter and the receiver in the vertical plane. Since the propagation over the rooftops (multiple diffractions) is the most dominant part in urban environments, the accuracy of the model is quite high. This model is well suited for the following conditions: • 800 ≤ f ≤ 2000 MHz • 0.02 ≤ d ≤ 5 km • 4 ≤ hb ≤ 50 m • 1 ≤ hm ≤ 3 m • Flat ground • Uniform building heights and building separations. The parameters used in Walfisch-Ikegami model calculations are depicted on Figure 2.5 [10].

20

hb

H

ΔH

d

hm

α

b

w

Figure 2.5 Walfisch-Ikegami model parameters.

In case of free line-of-sight between the base station and the mobile terminal antennas in a street canyon path loss can be calculated as:

mRfRLLOS 20,log20log266.42 ≥++= (2.8) In case of non-LOS:

msdrtsFSnLOS LLLL −−= (2.9) where

FSL - the free space loss,

rtsL - the rooftop-to-street diffraction and scatter loss,

msdL - the multi-screen loss. The rooftop-to-street loss can be found as:

orimrts LhHfwL +−++−−= )log(20log10log109.16 (2.10) where w - the width of the street (see Figure 2.5), H - the height of the buildings (see Figure 2.5),

mh - the height of the mobile terminal (see Figure 2.5). Expression oriL is defined as:

( )( )⎪

⎩

⎪⎨

⎧

≤≤−−≤≤−+≤≤+−

=o

o

o

905555114.00.4553535075.05.2350354.010

ϕϕϕϕϕϕ

oriL (2.11)

where φ - the angle in degrees between incidences coming from base station and road (see Figure 2.6) [10].

21

Figure 2.6 Definition of street orientation angleϕ. In the case, when the base antenna height exceeds the surrounding rooftops, Lmsd can be defined as:

( )

bff

RHhL bmsd

log9log1925

7.04

log181log1854

−⎥⎦

⎤⎢⎣

⎡⎟⎠⎞

⎜⎝⎛ −+−+

++−+−= (2.12)

where b - the separation distance between blocks (see Figure 2.5). There are terms added for short distances (R < 0.5 km) and for base antennas lower than rooftops. However it has been shown that the accuracy of the prediction is best for the case hb >> H [12]. Thus, the path loss formula for urban environments with cell size less than 1km can now be expressed as,

)17log(18log38 −−+= bhRKL (2.13)

where

K = ⎩⎨⎧

MHz 2050for 155.3MHz 1900for 1.154

(2.14)

It has to be noted that equation (2.13) is only valid for base station antenna heights above 18 m.

α10=R (2.15) where

38)17log(18 −+−

= bpmax hKLα (2.16)

Different variants of the Walfisch-Ikegami model are implemented in the various radio planning tools.

22

2.3 NETWORK DIMENSIONING Purpose of network dimensioning is to estimate amount of node elements needed in order to cover planned area. Thus, this step includes calculation of radio link budgets, capacity and coverage in both uplink and downlink. Normally, traffic estimation and growth forecasts have to be based on market analysis. A common process of network dimensioning is depicted in Figure 2.7. It can be seen that the dimensioning is successfully finished as soon as the balance between calculations in uplink and downlink is reached. Obviously, at the initial stages, when network load is not high, the highest priority is to fulfill set coverage thresholds. Therefore, capacity has not been considered as an issue in further calculations.

Figure 2.7 A common process for network dimensioning [12].

23

2.3.1 Traffic estimation The traffic estimation for speech in the network can be done based on live GSM network statistics. Although, even for speech the amount of traffic is strongly linked to how aggressively 3G handsets are pushed into the market. UMTS specific services such as video service, high speed packet services are very hard to predict, and will be to a certain extent affected by the pricing model for video calls, for instance. Likewise, for packet the usage will be strongly linked to the pricing model in conjunction with the pricing of other (mobile) broadband services available. All in all, based on the combination of 2G voice and the number of 3G handsets planned to be sold (with contracts or on pre-paid) the voice traffic, and to a certain extent the packet traffic can be estimated. Despite on obvious difficulties with the UMTS services traffic estimation, it is very important at least roughly to predict potential growth of the traffic capacity in the near future. 2.3.2 Definitions 2.3.2.1 Radio access bearers The transport through the radio network in UTRAN is provided by a Radio Access Bearer (RAB) service. A RAB is a logical connection between the Core Network (CN) and the User Equipment (UE). It consists of a Radio Bearer (RB) connection between the UE and RNC, and an Iu bearer connection between RNC and core network, and is used to provide a connection for a UMTS service via UTRAN (Figure 2.8).

Core networkRNCRBSUEUu Iub Iu

Radio bearer

Radio access bearer (RAB)

Iu Bearer

Figure 2.8 Radio access bearer (RAB) definition. The radio bearers can be mapped onto both dedicated channels as the Dedicated Traffic Channels (DTCH) and common channels as the Random Access Channel (RACH)/Forward Access Channel (FACH). The RABs are divided into different traffic classes, which are optimized for different application types with different QoS requirements. Table 2.1 presents types of traffic classes with their characteristics and example applications [1]:

24

Table 2.1 UMTS QoS classes

Traffic class RAB configuration Example

application

Conversational Preserved time variation between information units in data stream (low delay) Voice

Streaming Preserved time variation between information units in data stream Streaming audio

Interactive Request response pattern (preserved payload content) Web browsing

Background Destination is not expecting the data within a certain time (preserved payload content)

Background download of

emails More details about the RAB attributes and QoS concepts can be found in [1]. Table 2.2 shows configuration information of some WCDMA system radio access bearers (RABs) [12]. The total bit rates in both UL and DL is defined as the sum of the service rates and signaling rates, i.e. the total bit rate in the case of the speech service 12.2 kbps (service) and 3.4 kbps (signaling) is 15.6 kbps. The higher bit rate connections have lower Eb/No requirements. The robustness against interference provides a processing gain, PG, defined as:

)log(10inf o

chip

RR

PG = (2.17)

where

chipR - the chiprate (3.84 Mcps),

oRinf - the data rate. The higher the data rate, the lower the processing gain value. The reason is that a fixed chip rate of 3.84 Mcps is used in WCDMA systems. Hence the coverage area will be smaller for high data rate connections.

25

Table 2.2 Radio access bearers.

Traffic class RAB configuration

SRB for BCCH

SRB for PCCH

SRBs for BCCH, CCCH and DCCH (FACH)

SRBs for CCCH and DCCH (RACH)

Signaling radio bearers

13.6/13.6 kbps SRB for DCCH

AMR 12.2 kbps RAB

28.8 kbps CS RAB Conversational

64 kbps CS RAB

64/64 kbps PS RAB

64/128 kbps PS RAB Interactive

64/384 kbps PS RAB

57.6 kbps CS RAB Streaming 8/54 kbps PS RAB + Interactive [64/64 or 64/128 or 64/384] kbps PS

RAB

AMR 12.2 kbps RAB + + Interactive [64/64 or 64/128 or 64/384] kbps PS RAB

AMR 12.2 kbps RAB + + Interactive [64/64 or 64/128 or 64/384] kbps PS RAB + + Interactive [64/64 or 64/128 or 64/384] kbps PS RAB

Mixed

Interactive [64/64 or 64/128 or 64/384] kbps RAB + + Interactive [64/64 or 64/128 or 64/384] kbps RAB

2.3.2.2 Activity factor and DTX gain A radio link between the UE and the RBS consists of a Dedicated Traffic Channel (DTCH) and a channel used for radio resource control signaling sent on the Dedicated Control Channel (DCCH). When one of the channels (DTCH or DCCH) is not transmitting, less interference is generated on the air interface and more capacity can be expected. The capacity gain depends on the activity factor of the DCCH(s) and DTCH(s).

26

Table 2.3 DTX gain [12].

DTX gain RB configuration

UL DL

Speech/AMR 12.2 kbps RB1 + 3.4 kbps SRB2 69% 102%

AMR 7.95 kbps RB1+ 3.4 kbps SRB2 69% 102%

AMR 5.95 kbps RB1+ 3.4 kbps SRB2 69% 102%

AMR 4.75 kbps RB1+ 3.4 kbps SRB2 69% 102%

28.8 kbps CS RB3 + 3.4 kbps SRB 7% 5%

64 kbps CS RAB3 + 3.4 kbps SRBs on DPDCH/DPCH2 7% 5%

8 kbps PS RB3 + 3.4 kbps SRB2 5% 5%

16 kbps PS RB3 + 3.4 kbps SRB2 5% 5%

32 kbps PS RB3+ 3.4 kbps SRB2 5% 5%

64 kbps PS RB3 + 3.4 kbps SRB2 5% 5%

128 kbps PS RB3 + 3.4 kbps SRB2 – 2%

384 kbps PS RB3 + 3.4 kbps SRB2 – 1%

57.6 kbps CS RAB3 + 3.4 kbps SRBs for DCCH2 6% 6%

Streaming 16 kbps PS RB3 + 8 kbps PS RB3 + 3.4 kbps SRB2 6% –

Streaming 64 kbps PS RB3 + 8 kbps PS RB3 + 3.4 kbps SRB2 – 6% 1 50% activity factor 2 10% activity factor 3 100% activity factor during packet transmission

2.3.2.3 Channel models Bit energy over noise, Eb/No, is an important parameter in WCDMA coverage and capacity planning as a part of quality requirements for the WCDMA bearers. It depends on the radio environment and the speed of the mobile terminal. The 3GPP specifications standardize channel models [5] in order to reflect the broadband channel properties of a WCDMA system and simplify radio environment modeling in network planning tools. Table 2.4 shows an overview of some 3GPP-specified channel models applicable for WCDMA network planning.

Table 2.4 Mapping of channel model to UE speed [12].

Channel model UE speed Typical Urban (TU-3, TU-50) 3 km/h, 50 km/h Rural Area (RA-3, RA-50, RA-120) 3 km/h, 50 km/h, 120km/h Hilly terrain (HT-120) 120km/h

27

2.3.3 Radio link budget The link budget is used to calculate the maximum allowed path loss and the maximum cell range. After that the cell coverage area can be calculated.

Figure 2.9 Link budget. The link budget includes a number of margins [16], [12], which are needed in order to compensate various uncertainties and losses during radio network design. 2.3.3.1 Margins Interference margin The interference margin is the increased noise level caused by greater load in a cell. It shows dependency between coverage and capacity dimensioning - the larger the cell load, the smaller the cell coverage area. Fast fading (log-normal) margin The signal strength value calculated by means of wave propagation algorithms can be considered as a mean value of the signal strength in a small area, which is determined by the accuracy and resolution of the model. The deviation of the local mean has nearly a normal distribution in dB in comparison with the predicted mean. That is the reason why variation is called log-normal fading. As a rule, radio propagation models used for pathloss predictions in WCDMA planning tools do not capture the log-normal fading. As a result, the coverage probability reaches only about 50%, whereas most operators have requirements of 95-99,99%. In order to improve percentage of probability of signal strength above the prediction value, a log-normal fading margin, argmLNF , is added to the link budget calculation during the radio design process.

argmLNF can be expressed by means of Jakes’ formula [12]:

Feeder lossfL

RBS power RBSP

Noise rise ULI

UE sensitivity sensUE

RBS sensitivity sensRBS

Antenna gain antG Pathloss

maxpL

UE power UEP

28

γ−+−= ))]/log(10)(([ 00arg dRdLPLNF pathtm (2.18) where

tP - the transmitted power,

)( 0dLpath - the average reference path loss,

0d - the distance at which path loss is referred to (in meters), R - the radius from transmitted antenna, γ - the desired received signal threshold. The relation between argmLNF and the perimeter coverage, )(γP , which denotes the probability of having a received signal strength value above a certain threshold on the cell border, can be expressed as [33]:

⎟⎟⎠

⎞⎜⎜⎝

⎛Φ=⎟⎟

⎠

⎞⎜⎜⎝

⎛+=

σσγ argarg

221

21)( mm LNFLNF

erfP (2.19)

where

)(tΦ - the normal distribution function with its variable t, σ - the standard deviation. If )(γP is known then LNFmarg can be found as [12]:

σ⋅= tLNFm arg (2.20) The variable t can be found in a normal distribution function table.

Figure 2.10 The cumulative normal distribution function [12]. According to Figure 2.10, if the perimeter coverage equals 75 %, t will be 0.67. In case of standard deviation value of 8 dB, LNFmarg equals 5.4 dB, according to equation (2.20).

29

Thus, if a guaranteed availability of 75 % is required at the cell border and 90 % within the cell area, then an extra margin of 5.4 dB has to be added to the signal threshold. Correlation between distance dependence exponent n (1/Rn) and standard deviation σ according to Jakes’ formula is depicted on Figure 2.11.

0,82

0,84

0,86

0,88

0,9

0,92

0,94

0,96

0,98

1

0 0,5 1 1,5 2 2,5 3 3,

Border coverage

70 %

72 %

74 %

76 %

94 %92 %90 %

86 %84 %

78 %

80 %

82 %

88 %

σ/n [dB]

Area

cov

erag

e [%

]

96 %98 %

Figure 2.11 Coverage area according to Jake’s formula [12]. Jakes’ formula doesn’t take the effect of many servers into account. The presence of many servers at the cell border causes handover, which results in the presence of a handover gain and lower required log-normal fading margin as a consequence. Thus, handover gain, GHO, must be taken into consideration during LNFmarg calculations for multi-cell system:

HOm GtLNF −⋅= σarg (2.21) The fading margin values for the most common area coverage probabilities are presented in Table 2.5 [12]. More values presented graphically in Appendix A. Table 2.5 Uplink log-normal fading margins for 3-sector sites (handover gain included).

Area coverage [%] Environment σLNF

[dB] 75 85 90 95 98

Rural, suburban 6 –4.1 –1.7 0.0 2.3 4.6

Urban 8 –3.9 –0.9 1.1 4.1 7.2

Dense urban; suburban indoor 10 –3.8 –0.1 2.3 5.9 9.6

Urban indoor 12 –3.8 0.6 3.4 7.5 12.1

Dense urban indoor 14 –3.8 1.1 4.3 9.0 14.3

30

Power control margin Approaching the cell border UE causes the path loss increase. The power control loop of the system compensates it by increasing the UE power until the loop saturates and transmits with maximum power. At this point power control is not operational anymore, which leads to reduced uplink system sensitivity. Power control margin, PCmarg, takes this effect into consideration. Margin values for different radio environments (channel models and UE speeds) can be found in [12]. Body loss The human body has negative impact on the UE performance. The reason is that it absorbs energy causing reduction of antenna efficiency. The body loss margin recommended by ETSI is 3 dB for 1900 MHz [14]. For data services users normally don’t keep the mobile terminal positioned by the ear, so body loss is not applied for them and is set equal to 0 dB. Car penetration loss If the UE is placed in the car without external antenna, an extra 6 dB margin has to be added in order to compensate for the penetration loss [19]. Building penetration loss Building penetration loss is expressed as the difference between the average signal strength immediately outside the building and the average signal strength over the ground floor of the building. A typical value for urban and dense urban areas in link budget calculations is 18 dB [8]. However, building penetration loss can vary significantly, depending on specific environments. Feeder loss Normally the feeder loss parameter includes all the losses between the top of the RBS and the antenna, i.e. includes possible jumper, duplexer, diplexer, etc. losses. In the case of ASC/TMA presence, feeder loss parameter includes all the losses between the top of the RBS and the ASC/TMA in the DL. In the UL the ASC compensates for feeder losses. In addition, ASC insertion loss has to be added to the calculations. 2.3.3.2 Uplink link budget Calculations start from the uplink (reverse link) direction, because typically uplink interference is the limiting factor in WCDMA systems. The uplink budget can be calculated as follows [12]:

jfantBPLCPLBLmULmsensUEp LLGLLLLNFIPCRBSPL −−+−−−−−−−= argargmax (2.22)

where

maxpL - maximum path loss due to radio wave propagation,

UEP - the maximum UE output power,

sensRBS - the RBS sensitivity. Depends on the RAB and channel model,

argmPC - the power control margin,

ULI - the noise rise or uplink interference margin, section,

31

argmLNF - the log-normal fading margin,

BLL - the body loss,

CPLL - the car penetration loss,

BPLL - the building penetration loss,

antG - the sum of RBS antenna gain and UE antenna gain,

fL - the feeder loss

jL - the jumper loss. The RBS sensitivity can be expressed as [12]:

fboftsens LNERNNRBS ++++= 0inflog10 (2.23)

where

tN - the thermal noise power density (-174 dBm/Hz),

fN - the noise figure (typical value 2.3dB),

oRinf - the information bit rate [bps],

0NEb - the bit energy divided by noise spectral density,

fL - the feeder loss. The rough estimation of macro cell range as well as coverage area, without taking into account terrain specifics, in Table 2.6 and Table 2.7 is obtained by means of the Okumura-Hata propagation formulas 2.4-2.7, Section 2.2.1.3. The input values for the calculations have been taken from Sections 2.3.3.1 and 4.1 as well as from [12] and [35]. The number of sites, siteN , required in order to fulfill presented in the link budget tables requirements is found as:

areaSiteareaTotalN site _

_= (2.24)

where

areaTotal _ - the total planned area (13.63 km2 in calculations, Section 4.1). A reference uplink link budget for different service types used in the planning tool simulations is shown in Table 2.6.

32

Table 2.6 Uplink link budget.

Service type Parameter

Units Voice CS64 PS128

Probability of coverage % 95 95 95

RBS Receiver Sensitivity, sensRBS dBm -121 -117.5 -114

Subscriber Maximum Transmit Power, UEP dBm 21.0 21.0 24.0

Power control margin, argmPC dB 0.7 0.7 0.7

UL Max Loading, ULη % 30 30 30

Noise rise or the uplink interference margin, ULI dB 1.5 1.5 1.5

Lognormal fading margin (outdoor) 1, argmLNF dB 4.1 4.1 4.1

Lognormal fading margin (indoor) 1, argmLNF dB 7.5 7.5 7.5

Building Penetration Loss, BPLL dB 18 18 18

Body Loss, BLL dB 3 0 0

RBS Antenna Gain, antG dBi 18.0 18.0 18.0

Feeder and Jumper losses, fL + jL dB 3 3 3

Maximum Path Loss (Outdoor), maxpL dB 147.7 147.2 146.7

Maximum Path Loss (Indoor), maxpL dB 126.3 125.8 125.3

Cell range (Indoor), R km 0.610 0.590 0.571

Area (Indoor) km2 0.73 0.68 0.64

Number of sites 19 20 21

According to formula (2.32) uplink noise rise from the table is calculated as:

dBIUL 5.13.0-1

1log10 =⎟⎠⎞

⎜⎝⎛= (2.25)

As already noted, the Okumura-Hata formula can be normally used only for rough estimations at initial stages. For more precise results, a network planning tool must be used. Since the formula is valid for 1 ≤ R ≤ 20 km then (see sections 2.2.1.3 and 2.2.1.4), it can give unreliable results for small cells, e.g. in dense urban environment. In such cases, formula based on the Walfisch-Ikegami model should be used, see Section 2.2.1.4. NB! The calculation results in both uplink and downlink link budget tables (Table 2.6 and Table 2.7) have been considered as input for planning tool simulations presented in Chapter 4. In order to keep consistency, the Okumura-Hata model has used in both the link budget calculations and the planning tool simulations. However, it must be kept in mind

33

what presented margins should be considered as example values and can be not applicable for real networks dimensioning. In conclusion, it must be noted that packet service has the lowest maximum allowable pathloss, which makes it the limiting service in the uplink direction. 2.3.3.3 Downlink link budget Downlink link budget calculations are similar to uplink link budget calculations. However, downlink dimensioning is a more complex procedure for a few reasons. The most important reason is that all the UE’s share the same transmitter, i.e. use the same power source. In addition, interference levels are strongly dependant on user distribution and traffic load. As a consequence, downlink dimensioning is determined by the average total output power and the average CCH/DCH power. The downlink link budget can be expressed by means of following formula [12]:

jantBPLCPLBLmDLmsensTXp LGLLLLNFIPCUEPL −+−−−−−−−= argargmax (2.26)

where

maxpL - maximum path loss due to radio wave propagation,

TXP - the maximum transmitter output power at the reference point,

sensUE - the user equipment sensitivity,

argmPC - the power control margin,

DLI - the noise rise or downlink interference margin, section 2.3.4.2,

argmLNF - the log-normal fading margin,

BLL - the body loss,

CPLL - the car penetration loss,

BPLL - the building penetration loss,

antG - the sum of RBS antenna gain and UE antenna gain,

jL - the jumper loss. The UE sensitivity can be expressed as [12]:

0inflog10 NERNNUE boftsens +++= (2.27)

where

tN - the thermal noise power density (-174 dBm/Hz),

fN - the noise figure (typical value 7 dB),

oRinf - the information bit rate [cps],

0NEb - the bit energy divided by noise spectral density.

34

Total output power reftotP , at the reference point (at the antenna) can be calculated as the sum of the powers allocated to each individual UE, the power allocated to synchronization and common control channels. Normally about 25% of total power allocated for control channels refCCHP , , leaving 50% for dedicated channels to traffic and about 25% as headroom for mobility needs. Assuming that activity factors for synchronization channels (P-SCH and S-SCH) are considerably low, the average value of the total output power at the system reference point can be expressed as [12]:

DL

sarefCCHreftot

LHPP

η−⋅+

=1,

, (2.28)

where

DLη - the downlink system loading,

refCCHP , - the average level of the power allocated to the all common control channels at the system reference point (at the antenna),

H - the factor related to the path loss distribution of the UEs

saL - the signal attenuation at the system reference point to the UE at the

cell border. The signal attenuation at the system reference point to the UE at the cell border:

jaBPLBLmmpsa LGLLLNFPCLL +−++++= argargmax (2.29)

Downlink noise rise for UE located at the cell border can be found as [12]:

DL

sarefCCHDL

HLPKI

η−+

⋅+=1

1 , (2.30)

where

chipft

cc

RNNFK +

=α (2.31)

where

cα - the non-orthogonality factor at the cell border,

cF - the average ratio between received inter-cell and intra-cell interference at the cell border,

chipR - the system chip rate.

The downlink noise rise DLI defines margin for the noise floor at the UE in the loaded WCDMA system, which is obviously higher than in an unloaded system. As can be seen from formulas (2.29-2.31), downlink noise rise depends on the transmitter output power and the location of the users in the cell.

35

A reference downlink link budget for different service types used in the planning tool simulations is shown in Table 2.7. The input values for the calculations have been taken from Sections 2.3.3.1 and 4.1 as well as from [12] and [35].

Table 2.7 Downlink link budget.

Service type Parameter

Units Voice CS64 PS128

Probability of coverage % 95 95 95

UE Receiver Sensitivity, sensUE dBm -119 -112.5 -111

Subscriber Maximum Transmit Power, UEP dBm 28.0 31.2 32.0

Power control margin, argmPC dB 0.7 0.7 0.7

DL Max Loading, DLη % 60 60 60

Noise rise or the downlink interference margin, DLI dB 7 7 7

Lognormal fading margin (outdoor), argmLNF dB 3.4 3.4 3.4

Lognormal fading margin (indoor), argmLNF dB 7 7 7

Building Penetration Loss, BPLL dB 18 18 18

Body Loss, BLL dB 3 0 0

RBS Antenna Gain, antG dBi 18.0 18.0 18.0

Feeder and Jumper losses, fL + jL dB 3 3 3

Maximum Path Loss (Outdoor), maxpL dB 147.9 147.6 146.9

Maximum Path Loss (Indoor), maxpL dB 126.3 126.0 125.3

Cell size (Indoor), R km 0.610 0.590 0.571

Area (urban) km2 0.73 0.70 0.64

Number of sites 19 20 21

As can be seen from Table 2.6 and Table 2.7, the balance between UL and DL has been reached. According to the dimensioning results, 21 sites required in order to fulfill requirements for the service with the lowest maximum path loss (PS128). However, it must be taken into account that the rough estimations obtained during the dimensioning phase can be considered only as starting point for further detailed planning by means of the radio planning tool.

36

2.3.4 Capacity calculations This section introduces well-known load equations for calculating load of WCDMA cell in both downlink and uplink directions. 2.3.4.1 Uplink capacity

First, the definition of bit energy per noise ratio, ⎟⎟⎠

⎞⎜⎜⎝

⎛

0NEb , has to be established:

⎟⎟⎠

⎞⎜⎜⎝

⎛

++−=⎟⎟

⎠

⎞⎜⎜⎝

⎛

Notherjown

j

j

chip

j

b

Pipip

RR

NE

0

(2.32)

where

chipR - the system chip rate,

jR - the bit rate of j th user,

jp - the received power from j th user,

owni - the interference power received from the own cell,

otheri - the interference power received from the other cell,

NP - the thermal noise power. The capacity per cell depends on the amount of interference per cell; hence it can be defined by means of throughput-based load factor ULη [16]:

( )i

RNE

R

N

j

jjj

b

chipUL +⋅

⎟⎟⎠

⎞⎜⎜⎝

⎛+

= ∑=

11

11

0

υ

η (2.33)

where N - the number of active users in the cell,

jυ - the activity factor of the service for j th user, i - the ratio of other cell and the own cell interferences (other-to-own-cell interference). The given formula shows a limit for the uplink load, which is contributed by fractional load of each particular active user. Obviously, in case of fixed target uplink load factor, lower other-to-own-cell interference helps to increase the number of served users, i.e. capacity. A radio network planning parameter, interference margin also known as noise rise, can be found using the uplink load factor.

)1log(10 ULULI η−⋅−= (2.34)

37

0

2

4

6

8

10

12

14

1 2 3 4 5 6 7 8 9 10

Load

Noi

se ri

s

Figure 2.12 Noise rise.

The interference margin used in the link budget must be equal to the maximum planned noise rise. It must be noted that the recommended maximum uplink load is around 60-70% [12]. A higher system load can lead to uncontrollable noise rise effect. Obviously, 100% load would cause infinite noise rise, which can be considered as infinite interference. 2.3.4.2 Downlink capacity Notwithstanding that the downlink principles differ from uplink ones, the downlink load factor DLη can be defined based on a similar approach used for the uplink load factor definition, although the parameters are slightly different [16]:

( )[ ]jjN

j

j

j

b

jDL i

RWNE

++⋅⎟⎟⎠

⎞⎜⎜⎝

⎛

⋅= ∑ =αυη 1

1

0 (2.35)

where new parameters are:

ji - other-to-own-cell interference of j th user,

jα - the orthogonality factor of the channel of j th user. Orthogonality factor depends on radio channel conditions and mobile user’s speed. It equals 1 in an ideal radio environment (without fading). However, in reality the code orthogonality of the user is partially destroyed by multipath propogation. Typically, the orthogonality is between 0.4 and 0.9 in multipath channels. It should be noted that since

38

other-to-own-cell interference in the downlink is unique for each user, depending on the user’s location, it is practical to use average values in capacity dimensioning. The interference margin can be found by means of the downlink load factor.

)1log(10 DLDLI η−−= (2.36) It should be noted that when 1→DLη , noise rise ∞→ , i.e. system approaches its pole capacity. Clearly, the downlink coverage is more dependent on load then the uplink coverage. The reason is that transmitted power is constant and shared between all mobile users in the cell, while in the uplink each terminal has its own power amplifier. Therefore, downlink coverage decrease is directly related to the number of mobile users in the cell.

At the same time, in order to fulfill a user’s ⎟⎟⎠

⎞⎜⎜⎝

⎛

0NEb requirement in the downlink, the

following criteria has to be satisfied [26]:

∑≠=

++−⋅⋅=⎟⎟

⎠

⎞⎜⎜⎝

⎛N

mnnN

jn

n

jm

mj

jm

j

j

b

PLP

LPL

pRW

NE

,1 ,,

,0 )1(

1

α (2.37)

where

jp - the average transmitted power for j th user,

jmL , - the path loss from the serving base station sector m to the j th user,

jnL , - the path loss from the other base station sector n to the j th user,

mP - the total transmit power from the serving base station sectors m,

nP - the total transmit power from the other base station sectors n. Since WCDMA downlink capacity is interference limited, transmitted power control accuracy becomes very crucial (see equations (2.35), (2.37)). The power control is based on carrier-to-interference ratio (C/I) and can be defined as [26]:

∑∑==

== N

nn

N

n n

D

R

D

RIC

11

1

1

γ

γ

γ

γ (2.38)

where R - the distance between serving base station and mobile,

nD - distance between nth interfering base station and mobile, γ - the exponent of the attenuation of the radio wave. In GSM a certain (C/I)-ratio has to be achieved for a proper quality of speech. It is mainly determined by the frequency reuse factor of the network. In WCDMA all cells are using

39

the same frequencies. As a consequence, base stations-interferers can locate within the same distance as the serving base stations [26]. 2.3.4.3 Soft capacity According to [4] Erlang capacity can be obtained from the Erlang B model only for hardware limited systems, also known as hard blocked systems. However, there is no single fixed value for the maximum capacity in the case of interference limited systems such as WCDMA, because interference and capacity can be shared between adjacent cells. Thus, the Erlang B model is not valid any longer because of too pessimistic results. Such a phenomenon is known as soft capacity. The idea is that the less interference is coming from neighboring cells, the more capacity is available in the middle cell (see Figure 2.13). And if neighbor cell’s loading is considerably low, it means that extra capacity is available in this cell, which can be borrowed by other adjacent cells. Thus, interference sharing provides soft capacity.

Figure 2.13 Soft capacity in WCDMA [16]. As a rule, in the dimensioning phase, equally loaded cells are assumed, but using radio planning tool (and in reality) different load in each cell.

40

3 DETAILED PLANNING In WCDMA systems, mobile users select a cell to camp on by estimating the quality of the common pilot control channel (CPICH) from each base station in the network [2]. Therefore, cell size depends on power level of CPICH, radio environment conditions of the network and loading. On the one hand, the higher CPICH transmit power means larger cell coverage and more mobile terminals camping on the cell, whereas on the other hand, it means larger soft handover areas and less power for traffic channels. In addition, it is very important that traffic distribution is fairly even in the network in order to utilize radio resources efficiently. Careful selection of possible site locations with acceptable antenna heights, azimuths and tilts is catered for in the detailed planning phase. 3.1 ANTENNA CONFIGURATION 3.1.1 General The coverage and capacity in a network are influenced by the antenna characteristics and configuration: azimuth, beam width, side lobe level, number of sectors per site, number of antennas per sector, height above ground and tilt. A Tower Mounted Amplifier (TMA) can improve the uplink radio performance and ensure a balanced link budget. The requirements on azimuth and beam-width are set depending on traffic load and on the number of sectors for the site. It is very difficult to define the optimum antenna site configuration for each environment and each traffic load profile. The perfect antenna configuration for a sector is strictly related to the specific position of the site, to the target coverage and to the location of possible obstacles. 3.1.2 Antenna height As a general rule, the cell size is determined by capacity considerations in an urban environment. Thus, there is no need to maximize coverage by high antenna masts. In order to avoid unnecessary interference, the antenna should be placed to limit the coverage area to the desired target. Therefore, the antenna should be mounted as low as possible, reducing coverage further by tilting, if necessary. In rural environments and for road coverage, coverage may have to be maximized by erecting high poles or masts. There may not be any nearby or close obstacles that are higher than the transmitter antenna. In theoretical terms, the first Fresnel zone should be free of obstacles in the vertical direction and the sector covered by the antenna should be free of obstacles in the horizontal direction [12].

41

Figure 3.1 First Fresnel zone. This leads to a rule to mount the antenna height at least 5 meters above the closest obstacle. 3.1.3 Antenna beamwidth selection and sectorization The main network planning goal is to achieve an overall sufficient coverage, which can be achieved by means of higher antenna gain in the first place. At the same time, power transmission in unwanted directions has to be minimized. Interference level in both downlink and uplink directions can be controlled using a proper antenna configuration as antenna horizontal beamwidth [21], [18], [28]. Figure 3.2 shows examples of horizontally 33° and 65° antenna beamwidths, respectively.

Figure 3.2 Practical antenna radiation patterns. (a)33° horizontal antenna beamwidth,(b)

65° horizontal antenna beamwidth [26]. The effect of antenna beamwidth and sectorization on capacity and coverage is explored in [22] and [21]. As research shows it is very difficult to control cell overlapping in case of high sectorization (for instance, 6 sectors sites). The amount of users increase is not proportional to the number of sectors. The number of soft handover (SHO) connections increases simultaneously with interference leakage from neighbor sectors. The described process can become uncontrollable in terms of urban environments.

42

3.1.4 Antenna downtilt In dense urban environments, the antennas are frequently installed at a height greater or equal to the average rooftop level. Clearly, a higher antenna position causes larger coverage overlapping areas increasing soft handover probability. In such cases it might be necessary to tilt the antenna in order to reach the coverage target and reduce interference. The effect of antenna downtilt has been widely studied [17], [29]. It is a well known fact that a wise approach in antenna tilting allows one to increase overall system capacity in WCDMA. There are two different kinds of tilt: • Electrical tilt, and • Mechanical tilt.

3.1.4.1 Mechanical downtilt Mechanical downtilt is achieved by directing the antenna towards the ground. It depends on two main factors: geometrical factor, GEOθ , and antenna vertical beamwidth factor,

BWVER,θ . The geometrical factor takes into account heights of the base station, bh , and mobile station, mh , and the size of the dominance area or cell size, R. So, the optimum mechanical downtilt angle, mν , can be found as a function of the geometrical factor and vertical beamwidth factor [29]:

( )BWVERGEOm f ,,θθν = (3.1) The geometrical factor can be calculated using the relation of the height difference between the base station antenna and mobile station antenna, and sector dominance size [29]:

⎟⎠⎞

⎜⎝⎛ −

=R

hh mbGEO arctanθ (3.2)

Mechanical antenna downtilt has been observed and found as an effective solution for reducing inter-cell interference by confining the signal to its dominance area [23]. Typical capacity gain varies from 15% to 20% [13], [25], [7], [29], but strongly dependant on network and antenna configurations [27]. However, it must be noticed that the angle between base station mechanical downtilt and the effective downtilt angle is the same in the horizontal plane only in the main lobe direction. With higher downtilt angles, the radiation pattern effectively shrinks in the main lobe direction, but widens in the side lobe directions, which clearly means increase in the overlapping between adjacent sectors, hence increasing the softer handover probability. In addition, potentially harmful effect of back lobe uptilt has to be taken into account. All in all, high attention has to be paid to extremely high mechanical downtilt values in order to avoid a negative effect on the network performance.

43

Figure 3.3 Effect of widening of the horizontal radiation pattern in case of increasing mechanical downtilt value [29].

3.1.4.2 Electrical downtilt Electrical tilt means an in-built phase-shift of all antenna elements that lowers the vertical beam in all horizontal directions. Antennas, supporting the Remote Electrical Tilt (RET), allow modifying the electrical down tilt via remote control system, simplifying the network optimization process. The need for a common interface for base station equipment to support RET has been also highlighted by the 3GPP specification body, which is currently specifying the RET concept for the Release 6 [3]. As for mechanical downtilt, it depends on 2 factors: geometrical factor GEOθ and antenna vertical beamwidth factor BWVER,θ [17]:

( )BWVERGEOe f ,,θθν = (3.3)

Obviously, vertical beamwidth factor, BS antenna height and site spacing are as important as in the case of mechanical tilt for network capacity performance. Since all directions are tilted evenly, the efficiency of electrical downtilt in the struggle against inter-cell interference is very high. In general, EDT is able to provide slightly better results than mechanical downtilt in terms of system capacity improvements and mitigation of pilot pollution [30]. However, it should be kept in mind that excessive tilt values can drastically deteriorate coverage in the main lobe direction causing a significant drop in network coverage performance.

44

Figure 3.4 Horizontal radiation pattern in case of using electrical antenna tilt [17]. 3.1.5 Soft and softer handover Soft and softer handovers (SHO) are an essential part of WCDMA network functionality. While in soft handover a mobile terminal can be served by a few cells from different radio base stations at the same time. In the case of softer handover a terminal can be connected simultaneously to a few cells from the same base station. The set of cells to which a mobile terminal is simultaneously connected is called an active set (AS). The typical size of an AS is 3. In certain situations, soft and softer handovers give additional gain to the link due to macro diversity. Gain size is proportional to the differences in path losses between participating in handover cells. Smaller difference helps to achieve greater gain. The effect of soft handover in the WCDMA uplink direction for different level differences and radio channels has been analyzed in [32]. The output of research is SHO gain can be up to 4.5dB in the case of slow moving terminals and lower than 1dB in case of high (4-6 dB) level difference depending on mobile speed. In softer handover the gain could be up to 1dB higher. According to SHO simulation result in the downlink in [20], the maximum gain of about 3dB can be observed. However, since 2-3 simultaneous transmission links are needed, the gain can also be negative. This proves the importance of having optimal cells in the AS. Besides, it can’t be noticed that there is always tradeoff in SHO, the gain is achieved by means of extra power transmitted (mobile connected to a few base stations instead of one) in the network, which introduces additional interference to the network, and causes excess overhead on system resources. Therefore, the amount of mobile terminals in soft/softer handover must be kept to a reasonable number. 3.1.5.1 Softer handover factor As it has been already noted in sections 3.1.2-3.1.5, possible overlap between adjacent sectors of one site and other neighboring sites should be taken into account during antenna configuration selection. Generally, the overall coverage overlap of cells, or the soft handover area, is required to be kept below 30-40%, because excessive soft handover probabilities might decrease downlink capacity [16]. The reason is that each SHO connection increases interference in the network. When the generated interference level exceeds the diversity gain, the soft handover does not provide any gain for system performance anymore. Besides, every connection reserves additional system resources (in

45

RBS and RNC) in both downlink and uplink and transmission capacity in Iub link. At the same time it must be noted that low handover probability values might inhibit the system ability to support UE mobility. Thus, the task of radio planning and optimization is to keep the soft handover probability values below desired values. 3.1.5.2 Pilot pollution Pilot pollution is observed in areas in which there are more CPICH signals received at the mobile station’s RAKE receiver than it is capable of processing, or none of the received CPICH signals is dominant enough [24]. “Too many” means that the number of MS CPICH signals received exceeds the active set size (see chapter 3.1.5). Every additional pilot polluter increases the interference level in the cell, reduces the received energy per chip over the power density )( 0NEc from the serving cell, causing degradation in the quality of the active connection. In order to avoid pilot pollution, the number of unnecessary CPICH signals in dominant area should be kept as low as possible. In general, pilot pollution can be reduced by means of CPICH power tuning [34]; antenna configuration adjustments, i.e. antenna direction changing, downtilting. Implementation of multi-carrier solutions [11] or repeaters [31] can be also considered. 3.1.6 Antenna directions The requirements on antenna directions are set depending on traffic load and sectorization of the site (number of sectors on site). If in a nominal cell plan the sectors of a site are normally evenly spaced, i.e. in case of 3-sector site, the angle between the main directions of the antennas is 120°, then in reality it is not always possible to configure the site with equally spaced sectors. In general, the choice of the direction is dependant on the particular radio environment and areas with potential traffic concentration. Nevertheless, it is very often recommended not to point an antenna directly towards a hill or a big obstacle like buildings and avoid small angle difference between adjacent sectors in order to avoid high interference levels in the cell. 3.1.6.1 Coverage overlap between adjacent sectors As has already been highlighted in sections 3.1.2-3.1.5, the antenna configuration has a great impact on network performance. Suitable antenna height position, beamwidth, sectorization, downtilt can aid to avoid high overlapping between cells and quality degradation in the network, as a consequence. However, in reality, one of the most widespread scenarios of coverage overlap arises, when antennas with quite wide horizontal antenna beamwidth (as a rule, 65°) are in use and the azimuths of two sectors are too close to each other. In such a case, it is almost impossible to avoid huge coverage overlap, which leads to excessive soft handover probabilities, pilot pollution and ping-pong effect.

46

Figure 3.5 Coverage overlap between adjacent sectors.

In order to minimize the coverage overlap between adjacent cells, it could be recommended to keep the separation between the adjacent sectors less than a certain angle, dependant on the horizontal antenna beamwidth. If delta in azimuth between adjacent cells is less than 100°, switching to antenna with 44° horizontal beamwidth should be considered [12]. 3.2 CAPACITY AND COVERAGE PLANNING Intuitively, capacity and coverage planning cannot be separated into 2 different processes because of their strong inter-correlation, especially in high traffic areas. Capacity and coverage planning activities dependency is expressed in cell size variation in WCDMA networks, also known as the “cell breathing” phenomenon. When a mobile user is located near the cell edge, its transmitting power will increase according to the load and interference level in the cell, and soon reaches the maximum allowed power per connection. The other users closer to the BS location will “overshoot” a user at the cell edge, preventing him from connection establishment and, thus, decreasing cell size. In other words, cell size will vary depending on the number of the active users in the cell and their location, services and data rates they are using. Then the objective of coverage planning is to ensure availability of the chosen services in the entire planning area. The maximum capacity in the network depends on the coverage area and network element’s configuration (radio hardware configuration, site and antenna configuration). Radio network planning cannot be properly done without using sophisticated planning tools. 3.2.1 Planning tool Since WCDMA systems are interference limited systems, the interference and capacity estimation play important role during coverage prediction process. Each user influences other users, causing everyone’s transmit power to change continuously until they stabilize, i.e. users cannot be separated during analysis and must be considered as a single whole. To compare, in the second generation systems detailed planning concentrated mostly on coverage planning. As a consequence, mobile users speed, radio channel profile, type of services play a much more important role in 3G system planning than in 2G.

47

One more major difference between the 2nd and 3rd systems planning is the importance of the traffic layer allocation. In addition, QoS targets for all the particular services have to be met during the simulation process. In order to handle complicated behavior of mobile users in 3G, WCDMA iterative analysis based on Monte Carlo simulations can be used for detailed coverage and capacity planning. Figure 3.6 shows the common radio planning approach by means of WCDMA planning tool simulations in case of existing GSM network as an input for 3G network.

Figure 3.6 Planning tool simulations approach. After initial dimensioning is done, coverage thresholds set and traffic/capacity figures estimated, the number of the most appropriate existing GSM sites has to be chosen as an input for 3G co-sites and WCDMA planning tool simulations in order to meet target requirements (coverage and capacity). During the simulation process necessary configuration and parameters adjustments are to a certain extent being made. The reason is that very often 2G/3G co-site share the same multiband antenna, so antenna configuration change (azimuth re-direction, mechanical tilt) can affect an optimized live GSM network, which could be unacceptable in many cases. As a result of continuous simulation activities, part of the chosen existing candidate sites can be eliminated from the plan as unacceptable for the 3G network or replaced with new candidates from existing GSM network sites or replaced with totally new sites. The process continues until the set targets are met.

Coverage/QoS/Capacity/ requirements

Re-use of an existing 2G sites as an input for 3G network

WCDMA planning tool simulations

Requirements fulfilled?

Remove/add sites, re-configure existing ones

END

Yes

No

48

3.2.1.1 Monte Carlo analysis of TEMS Cell Planner Universal The Monte Carlo simulator of TEMS CellPlanner Universal (TCPU) is designed to reflect as closely as possible the UTRAN behavior in terms of setting up, managing and releasing user connections [35].

Figure 3.7 TCPU simulations’ steps [35]. In short, the process of Monte Carlo simulations, shown on the Figure 3.7 contains following steps:

• Depending on the traffic demand defined for each WCDMA bearer, users are generated at random locations according to Poisson distribution.

• Connection attempt for specific MS and WCDMA bearer is made according to the

list of cells ranged in order by the selected ranking algorithm.

• The achieved C/I for each user is calculated based on the uplink and downlink power settings and the interference level known from the previous iteration.

49

• Over several iterations the transmitted power of the cells and the users is updated in order to match as closely as possible the achieved C/I to the target C/I, which is calculated from the user-defined uplink and downlink Eb/Io values and spreading factors used of particular WCDMA bearer.

• Users, exceeded user-defined thresholds, such as: maximum number of DL or UL

ASE, maximum UL interference (noise rise), maximum DL power limit, maximum number of users on particular spreading factors etc. are being disconnected.

• Once a possible overload situation is resolved for all the cells, the system must

verify if a stable state in the network has been achieved, i.e. the power changes are minimal between the iterations.

The result of Monte Carlo simulations is expressed in a number of plots and statistic reports reflecting the planned network status. The process of simulations is described in [35] in more detail. 3.2.1.2 Load estimation Before starting the WCDMA analysis, the expected load estimation with respect to the given traffic demand has to be done. The total traffic demand per service can be defined as follows: CS services

cell

subsubcell N

NdemandTrafficdemandTraffic ⋅=

__ (3.4)

where

celldemandTraffic _ - the traffic demand per cell in E/cell,

subdemandTraffic _ - the traffic demand per subscriber in mE/sub,

subN - the total amount of subscribers,

cellN - the total amount of cells. PS services

sub

subarea Nhours

bytebitsdemandTrafficdemandtrafficTotal⋅⋅

=)/3600(

/8___ (3.5)

where

areademandtrafficTotal __ - the total traffic demand in planned area in kbps,

subdemandTraffic _ - the traffic demand per subscriber in kB/hour/sub.

50

cell

areakbpscell N

demandtrafficTotaldemandTraffic ___ , = (3.6)

where

kbpscelldemandTraffic ,_ - the traffic demand per cell in kbps/cell.

throughputServicedemandTraffic

demandTraffic kbpscellcell _

__ ,= (3.7)

where

throughputService _ - the service throughput in kbps. It must be noticed that since in the Monte Carlo simulation of the TCPU, each user is assumed to be using the network continuously, one Erlang is supposed to represent one user.

51

4 STUDY CASE 4.1 SIMULATION ENVIRONMENT Study case comprises two different scenarios. A planned network based on existing GSM sites locations and antenna configurations of one of operators in Guanzhou province has been observed in the first scenario. In other words, 3G sites’ antenna configurations (height, antenna directions and tilts) of the WCDMA network fully coincide with existing GSM sites’ antenna configurations. The idea of such an approach is quite common – to use existing GSM network’s radio plan entirely as an input for future 3G network, which, however, could very often be inappropriate in case of 3G network planning. The network consists of a 20 3-sector base stations with 750m site-to-site distance in average and covers a total area of 13.63 km2 (Figure 4.1). The antenna installation height is on average 34.5m AGL. According to the coverage calculations presented in Section 2.3.3.2 and 2.3.3.3, the chosen amount of sites should allow us to fulfill 95% probability of coverage requirements for the speech and CS64 services.

Figure 4.1 First scenario network plan. In the second scenario a more advanced and extensive radio network planning approach has been considered. Antenna configurations of sites have been adopted for the existing environment and WCDMA specifics have been taken into account. Moreover, 3 sites have been discarded and only one new site has been added from/to the initial plan based on the GSM sites. Thus, the modified radio plan with 18 3-sector sites covering the same area as the first scenario, but still fulfilling requirements is presented (Figure 4.2).

52

Figure 4.2 Second scenario network plan. Monte Carlo simulations from the TEMS Cellplanner Universal (TCPU) planning tool have been used in both cases in order to perform WCDMA analysis [35]. The digital map of 20m x 20m resolution including main terrain types and elevation data has been used for predictions. In spite of the fact that it is recommended to use Walfisch-Ikegami model in case of cell size less than 1km (Section 2.2.1.4), propagation results have been computed by means of Ericsson 9999 propagation model [12] based on Okumura-Hata propagation principles (Section 2.2.1.3). The reason for that is that the model was tuned particularly for this medium urban environment based on prior radio measurements and gave relatively precise results in comparison with the other models.

53

4.1.1 General simulation parameters General simulation parameters can be found in Table 4.1.

Table 4.1 Simulation parameters.

Parameter Value Maximum Tx power 44.7 dBm

CPICH Tx power 28 dBm BS noise figure 5 dB

UE maximum Tx power (speech/data) 21/24 dBm UE minimum Tx power -50 dBm Minimum 0NEb margin -16 dBm

Speech service bit rate 12.2 kbps Video service bit rate 64 kbps

Packet service DL/UL bit rate 128/64 kbps Channel profile ITU Vehicular A

Mobile station speed 3 km/h SHO window 3 dB

Downlink orthogonality 0.67 Maximum active set size 3

BS antenna 65°, 18 dBi Feeder cable losses 3 dB

Number of trials/iterations 20/50 4.1.2 Traffic density information Random homogenous distribution of users has been used in predictions. Total amount of users in planned area was 130 000. A service mix of voice users (12.2 kbps), video service users (circuit switched 64 kbps) and packet data users (128 kbps) has been assumed. Following traffic load as per service type has been used.

Table 4.2 Traffic data input per service.

Service type Load per user Speech 30 mE Video 2 mE

Packet (128 kbps) 100 KB/hour/sub As a result of calculations in (Equations (3.4)-(3.7)), following load for each service per cell has been used during simulations.

Table 4.3 Load level of services per cell.

Parameter Load (E/cell) Speech service 14.77 Video service 0.98

Packet service (128 kbps) 1.53

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As can be seen from the Table 4.3, the average cell load is far below recommended values (see Section 2.3.4.1). Overall cell load per cell (all services included) in the simulations seats around 30% of loading. 4.2 SIMULATION RESULTS 4.2.1 First scenario 4.2.1.1 CPICH coverage The first result that has to be checked is CPICH coverage.

Figure 4.3 CPICH coverage plot (1st scenario). The plot displays the downlink CPICH coverage quality in terms of Ec/Io, considering chip energy from the best serving cell and total DL interference received by a mobile terminal in a specific position in the network. Values are calculated as a margin of the minimum CPICH quality threshold set for WCDMA analysis with the parameter Min.DL Ec/Io for CPICH (dB) [35]. The threshold value is the minimum CPICH value required for UE to detect and decode the pilot channel of the best serving cell. The plot shows the margin remaining until the minimum threshold value is reached. A positive margin means that a specific position in the network provides CPICH coverage with sufficient quality. A negative margin means that quality requirements for CPICH are not fulfilled in the position [35]. In our case, areas with negative or slightly above threshold positive values can be observed close to the edge of investigated area. The major reason is that sectors of sites located at

55

the border are over down tilted in order to avoid coverage overlap with sites out of the marked area. Since the possible effect of coverage overlap with sites located out of the investigated area is not part of our scope, insufficient CPICH coverage areas can be partially eliminated by means of reasonable uptilting of antennas of sectors pointing towards the edge of the observed area. 4.2.1.2 Soft handover probability Obviously, sites with higher antenna positions (see Figure 4.4) can create larger coverage overlapping areas as well, if antenna tilt values are not sufficiently optimized. Therefore, even more attention must be paid to the sites with high (higher then average) antenna heights.

0

5

10

15

20

25

30

35

40

45

50

Site

-001

Site

-002

Site

-003

Site

-004

Site

-005

Site

-006

Site

-007

Site

-008

Site

-009

Site

-010

Site

-011

Site

-012

Site

-013

Site

-014

Site

-015

Site

-016

Site

-017

Site

-018

Site

-019

Site

-020

Site name

Figure 4.4 Real vs. average antenna height of the sites. In addition, it can be easily noticed that sectors of many sites are directed towards each other. Also, the angle between adjacent sectors of many sites is below recommended values (see Section 3.1.6.1), (Figure 4.5), which logically results in large coverage overlapping areas, and hence increased soft handover probability (Figure 4.6).

56

Figure 4.5 Irregular antenna directions. Thus, one of the most important harmful outputs of non-optimized antenna configurations is expressed in high soft handover probability areas.

Figure 4.6 Handover map (1st scenario). Intuitively, the less site-to-site distance, the higher impact of tilt values on soft handover probability and network performance as a consequence. With lower downtilt angles, this correlation can be emphasized more. Relative dependency of height, downtilt values, spacing between adjacent sectors and soft handover probability for the worst performing cells are shown in Table 4.4.

57

Table 4.4 Worst soft handover probability cells.

SectorID Antenna height, m

MDT, angles

EDT, angles

Angle spacing, degrees

HO probability,

% Site-001A 30 1 4 85 39.04 Site-003A 35 2 4 105 37.22 Site-003B 35 1 4 95 32.15 Site-003C 35 3 4 95 50.72 Site-006C 35 1 4 100 30.48 Site-008C 37 3 4 130 34.89 Site-010B 34 3 5 100 30.97 Site-010C 34 3 5 100 31.97 Site-012C 40 6 6 110 32.31 Site-013A 33 0 3 130 47.18 Site-013B 33 0 3 110 48.79 Site-014C 34 2 4 120 35.80 Site-016A 45 3 4 70 40.04 Site-016C 45 2 4 70 38.49 Site-017B 27.6 0 2 120 33.85 Site-020B 32 4 6 120 36.96

Although, each component in the table plays its own role, it must be noticed that the effect of irregular antenna directions and angle spacing between adjacent sectors as well as antenna position height play the most significant role in high soft handover probability achievement. It is difficult to overestimate the importance of proper antenna directions and spacing between sectors, because further adjustments in operational network are very complicated and can lead to uncontrollable results, drastically deteriorating network performance. That is why proper radio network planning has to be done prior to network roll-out. Required actions for minimizing negative influence of this effect have been taken in the 2nd scenario. 4.2.1.3 Influence of spacing between adjacent sectors Influence of spacing between adjacent sectors on SHO probability percentage based on worst performers’ results from Table 4.4 can be seen on the Figure 4.7. Notwithstanding that negative effect of small angle spacing between adjacent sectors is obvious, it is difficult to estimate precisely the share of particular “bad spacing” case in obtaining of excessive handover probability levels in terms of real environment. Individual approaches towards all the particular cells have to be taken in order to minimize harmful effect of excessive handover probability on network performance. However, the general recommendation about spacing between adjacent sectors for 65° antennas has to be followed as much as possible in the first place.

58

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

0 20 40 60 80 100 120 140Spacing between sectors

Figure 4.7 Correlation between adjacent sector spacing and SHO probability. 4.2.1.4 Statistics report WCDMA statistics report can be used to analyze statistics on number of user attempts, users served, users blocked and power consumption. Overall WCDMA statistics report per service can be found in Table 4.5

Table 4.5 Statistical results for system parameters (1st scenario).

Service #attempts %served #Insuff.CPICH #Insuff.DL #Blocked High Interf

Video 56.35 85.45 0.25 7.4 0.2 Speech 885.2 99.34 3.35 2.4 0.05Packet 128 85.5 72.40 0.05 9.7 2.4 Summary 1027.05 96.34 3.65 19.5 2.65

The statistics can be used to verify the reason why users were blocked, which is very helpful for troubleshooting. As a result, possible ways of improving network design can be found. Since speech service priority is the highest, and then the blocked speech users can be used as the first indicator of problems in the network. Coverage holes on Figure 4.3 results in number of blocked users for users of different services due to insufficient CPICH coverage. According to the statistics results, there are no serious problems with high interference level in the network because of considerably small average DL and UL load used in predictions (around 30%).

59

Insufficient DL indicates lack of downlink transmission power for some cells. The reason is that excessive amount of active links have been performed in some particular cells (Figure 4.8).

Figure 4.8 Downlink loading (1st scenario). More detailed studies of this type of statistics per cell might give us even more valuable feedback. In general, analysis results of 1st scenario network plan give us a valuable feedback for 2nd scenario radio planning. 4.2.2 Second scenario The purpose of 2nd scenario has been to improve network performance in comparison with 1st scenario results with same or less amount of sites. Reasonable antenna azimuths re-direction, electrical tilt optimization has been as working tool in order to achieve set targets. As a result of consecutive antenna configuration adjustments and planning tool simulations, optimized radio plan have been worked out. Amount of used base stations has been decreased from 20 sites in original plan to 18 sites (3 sites discarded: Site-006, Site-014, Site-016 and one new added: Site-021). Since shared multi-band antenna usage can be a practical solution from an installation point of view and cost-effective from a financial point of view in the initial stage of network roll-out, the original antenna configurations of the existing GSM network have been kept on as many sites as possible.

60

4.2.2.1 CPICH coverage It can be seen that CPICH coverage has been slightly improved in comparison with first scenario CPICH coverage in the border areas. As a consequence, best server area for services has been improved as well (see Table 4.6).

Figure 4.9 CPICH coverage plot (2nd scenario).

Table 4.6 Comparison of coverage areas of 1st and 2nd scenarios.

Coverage area , % Coverage area , % Service type (1st scenario) (2nd scenario)

Speech 96.91 97.37 Video 90.58 95.11

Packet 128 82.1 91.76 The most significant coverage area improvement has been achieved for video and packet services. It is also important that CPICH coverage improvement did not lead to additional excessive soft handover probability.

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4.2.2.2 Soft handover probability

Figure 4.10 Handover map (2nd scenario). There are only couple areas with considerably high soft handover probabilities can be found on the Figure 4.10, which is very important from saving of system resources point of view. It must be admitted that soft handover probability has significantly decreased after a few inappropriate sites removal from the original plan, some antennas re-direction and electrical tilt optimization. 21.49% SHO probability in average in 2nd scenario plan instead of 23.99% in original plan has been obtained. SHO probability values for worst performance cells “before” and “after” can be found in Table 4.7. There are no “after” results presented for sites Site-006, Site-014 and Site-016 because mentioned sites have been removed from the plan during 2nd scenario radio planning process. Cells with higher than 30% SHO probability could be further investigated.

62

Table 4.7 Comparison of handover probabilities of 1st and 2nd scenarios.

SectorID HO probability

(before) HO probability

(after) Site-001A 39.04% 30.71% Site-003A 37.22% 36.00% Site-003B 32.15% 29.01% Site-003C 50.72% 30.84% Site-006C 30.48% Site-008C 34.89% 28.57% Site-010B 30.97% 31.67% Site-010C 31.97% 25.99% Site-012C 32.31% 11.28% Site-013A 47.18% 26.62% Site-013B 48.79% 33.39% Site-014C 35.80% Site-016A 40.04% Site-016C 38.49% Site-017B 33.85% 24.95% Site-020B 36.96% 16.49%

4.2.2.3 Soft handover probability It can be seen that overall statistical results improvement in 2nd scenario in comparison with 1st scenario.

Table 4.8 Statistical results for system parameters (2nd scenario).

Service #attempts %served #Insuff.CPICH #Insuff.DL #Blocked High Interf

Video 54.05 95.65217 0.15 2.15 0.0 Speech 838 99.7494 1.55 0.55 0.0 Packet 128 84.2 87.70784 0.05 4.65 0.7 Summary 976.25 98.48399 1.75 7.35 0.7

% of served users increased for all services, most significantly for video and packet data users as well as amount of blocked users due to insufficient CPICH coverage, DL transmit power and high interference decreased. However, it must be noticed that the total amount of served users and the amount of served speech users is slightly decreased (about 3% and 5% relatively) (see Table 4.8). However, drop in amount of served speech users compensated by increase in amount of served video and packet users, which means more wise distribution of users in multi-service environment. In general, in case of same amount of served users, higher DL power consumption should take place, which should cause higher DL loading and slight interference increase. But it is going to be crucial only in high loading situations, when available resources approach the limit. It must be noticed that there are certain steps that could be taken in order to prevent lack of resources.

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Table 4.9 Amount of served users (1st vs. 2nd scenarios).

Service

Served users (1st scenario)

20 sites

Served users (2nd scenario)

18 sites Video 48.15 51.7 Speech 879.4 835.9Packet 128 61.9 73.85 Summary 989.45 961.45

Thus, by means of advanced radio planning and decreasing the number of sites by 10%, CPICH and service coverage areas are improved, there is a decrease in excessive handover probability, and a decrease in the amount of blocked users has been achieved.

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5 KOKKUVÕTE Kokkuvõtteks võime öelda:

• Töö käigus vaadeldi WCDMA raadiovõrgu planeerimise protsessi üldiselt ja selle erinevusi GSM raadiovõrgu planeerimise protsessist.

• Anti ülevaade kärje üles- ja allalüli mahtvuse dimensioneerimise meetodist.

Arvutuste kujul esitati kärje mahtuvust piiravad tegurid. • Välja on töötatud ülekatvuse vähendamisel ja pehme kõne üleandmise tõenäosuse

vähendamisel, mis põhineb antennide suundade muutmisel, kärgede vaheliste suundade muutmisel ja antennide allakallutustel, põhinev raadiovõrgu planeerimise metoodika.

• Kirjeldatud on Monte-Carlo analüüsil põhineva WCDMA raadiovõrgu

planeerimise vahendi peamisi omadusi.

• Praktilise töö käigus on uuritud ja tulemused esitatud kahe erineva TCPU-l põhineva WCDMA raadiovõrgu planeerimise stsenaariumi kohta.

• Esimesel juhul vaadeldi olemasoleval GSM 1800 antenni konfiguratsioonil

põhinevat WCDMA raadiovõrgu planeerimist. Selle meetodi puudusi on analüüsitud ja esile toodud kasutades TCPU statistilisi võimalusi ja graafikuid.

• Teisel juhul kasutati edasi arendatud WCDMA raadiovõrgu planeerimise

metoodikat. Selle tulemusena vähenes tugijaamade arv 20-lt 18-le. Rakendati kõik vajalikud antennide suuna ja allakallutuse muutused. Selle tulemusena saavutati tuntav CPICH parenemine, teenuse katvusala suurenemine ja väiksem pehme kõne üleandmise tõenäosus. Selle tulemusena saavutati statistiliselt paremad tulemused koos väiksema arvu blokeeritud kasutajatega. Ära märgiti ka mõningane kõne kasutajate arvu vähenemine mis tuleneb väiksemast tugijaamade arvust. See on kompenseeritud arukama multi-kasutajate jaotusega (suurenenud teenindatud video- ja andmeside klientide arv).

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6 CONCLUSION In conclusion, following points can be summarized:

• General process of WCDMA radio planning and its difference from traditional GSM planning approach has been studied in the thesis.

• Cell capacity dimensioning methodology in both downlink and uplink directions of

WCDMA network has been overviewed. Limiting factors in cell capacity have been presented by means of calculations.

• Methodology of radio network design based on initial minimization of harmful

effect of excessive coverage overlap and soft handover probability by means of antenna re-directions, changes of angles between adjacent sectors and electrical tilt optimization has been worked out.

• Main functionalities of WCDMA radio planning tool based on Monte-Carlo

analysis has been described.

• 2 different scenarios of radio planning based on WCDMA tool simulations (TCPU) have been investigated in the case study chapter and results presented.

• Radio planning of WCDMA network based on existing GSM1800 antenna

configurations have been observed in the first scenario. Disadvantages of such approach have been analyzed and highlighted by means of TCPU tool statistics and plots.

• Advanced WCDMA radio network planning approach based on worked out

methodology has been considered in the second scenario. Thus, total amount of sites have been decreased from 20 sites in the 1st scenario to 18 sites. Required antenna re-directions and electrical tilt changes have been implemented. Obvious improvements in CPICH, service coverage areas and lower soft handover probabilities have been achieved. As a consequence, better statistical results with fewer amounts of blocked users have been obtained. Slight decrease in speech and total amount of users as a consequence of smaller number of base stations available has been noticed. However, it has been compensated by more wise multi-users distribution (increased amount of served video and packet users).

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7 REFERENCES [1] Technical Specification TS 23.107, QoS Concept and Architecture, 1999. [2] 3GPP Technical Specification 25.304, UE Procedures in Idle Mode and Procedures for Cell Reselection in Connected Mode, 1999. [3] 3GPP Technical Specification 25.463. UTRAN Iu antenna interface: Remote Electrical Tilting (RET) antennas application part (RETAP) signaling, 1999. [4] 3GPP Technical Specification 25.922, Radio Resource Management Strategies, 1999. [5] 3GPP Technical Specification 25.943, Deployment aspects, 1999. [6] A. Alayon Glasunov, H. Asplund, J.-E. Berg, An investigation of measured and simulated wideband channels with application to 1.25 MHz and 5 MHz CDMA systems, Conference Proceeding, VTC 1998. [7] S. C. Bundy, “Antenna downtilt effects on CDMA cell-site capacity”, in Proc. IEEE Radio and Wireless Conference, pp. 99-102, 1999. [8] COST 231 TD (90) 116 Rev 1, Building penetration losses, 1991. [9] COST 231 TD (90) 119, rev. 2, Urban transmission loss models for mobile radio in the 900- and 1800-MHz bands, 1991. [10] J. Doble, Introduction to Radio Propagation for Fixed and Mobile Communications, Artech House, Boston-London, 1996. [11] M. M. El-Said, A. Kumar, A. S. Elmaghraby, Pilot pollution interference reduction using multi-carrier interferometry, in Proc. 8th IEEE Int. Symp. Computers and Communications, pp. 919-924, 2003. [12] Ericsson technical documentation. [13] I. Forkel, A. Kemper, R. Pabst, R. Hermans, The effect of electrical and mechanical down-tilting in UMTS networks, in Proc. 3rd Intern.Conf. 3G Mob. Com. Technol., pp. 86-90, 2002. [14] GSM 03.30 (Phase 2+), Radio Network Planning Aspects, ETSI, version 8.3.0, 1999. [15] M. Hata, Empirical formula for propagation loss in land mobile radio service, IEEE Trans. on Vehicular and Technology VT-29, pp. 317-325, 1980. [16] H. Holma, A. Toskala, WCDMA for UMTS:Radio Access for Third Generation Mobile Communication, Chichester: John Wiley & Sons Ltd, 2000. [17] T. Isotalo, J. Niemelä, and J. Lempiäinen. Electrical antenna downtilt in UMTS network, in Proc. 5th European Wireless Conference, Barcelona, pp. 265–271, 2004. [18] B. C. V. Johansson, S.Stefansson, Optimizing antenna parameters for sectorized W-CDMA networks, in Proc. IEEE 52th Veh.Technol.Conf., vol.4, pp. 1524-1531, 2000. [19] I. Kostanic, C. Hall, J. McCarthy, Measurements of the Vehicle Penetration Characteristics at 800 MHz, in Proc. IEEE Vehicular Technology Conference, 1998. [20] J. Laiho, A. Wacker, T. Novosad, Radio Network Planning and Optimisation for UMTS, Chichester: John Wiley & Sons Ltd, 2002. [21] J. Laiho-Steffens, A. Wacker, P. Aikio, The impact of the radio network planning and site configuration on the WCDMA network capacity and Quality of Service, in Proc. IEEE Vehicular Technology Conference, pp. 1006-1010, 2000. [22] J. Laiho-Steffens, Achim Wacker, Kari Sipilä and Kari Heiska, The Impact of the Base Station Sectorisation on WCDMA Radio Network Performance, in Proc. IEEE Vehicular Technology Conference, pp. 2611-2615, 1999. [23] D. J. Y. Lee, C. Xu, Mechanical antenna downtilt and its impact on system design, in Proc. IEEE 42nd Vehicular Technology Conference, vol.2, pp. 447-451, 1997. [24] J. Lempiäinen, M. Manninnen (ed.), UMTS Radio Network Planning, Optimization and QoS Management, Dordrecht: Kluwer Academic Publishers, 2003.

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[25] M. J. Nawrocki, T. W. Wiekowski, Optimal site and antenna location for UMTS – output results of 3G network simulation software, in Proc. 14th Intern.Conf. on Microwaves, Radar, and Wireless Com., vol.3, pp. 890-893, 2002. [26] J. Niemelä, J. Borkowski, Topology planning considerations for capacity and location techniques in WCDMA radio networks. [27] J. Niemelä, T. Isotalo, J. Lempiäinen, Optimum antenna downtilt angles for macrocellular WCDMA network, EURASIP Journal on Wireless Communications and Networking, 2005. [28] J. Niemelä, J. Lempiäinen, Impact of the base station antenna beamwidth on capacity in WCDMA cellular networks, in Proc. IEEE 57th Veh.Technol.Conf., vol.1, pp. 80-84, 2003. [29] J. Niemelä and J. Lempiäinen. Impact of mechanical antenna downtilt on performance of WCDMA cellular network, in Proc. 59th Vehicular Technology Conference, Milan, vol. 1, pp. 2091-2095, 2004. [30] J. Niemelä, J. Lempiäinen, Migration of pilot pollution through base station antenna configuration in WCDMA, in Proc. IEEE 60th Semiannual Vehicular Technology Conference, vol.6, Los Angeles, pp. 4270-4274, 2004. [31] F. Sapienza, S. Kim, Dominant pilot recovery in IS-95 CDMA systems using repeaters, IEICE Trans. Communications, vol.82, no. 1, January 1999. [32] K. Sipilä, M. Jäsberg, J. Laiho-Steffens, A. Wacker, Soft Handover Gains in Fast Power Controlled WCDMA Uplink, in Proc.IEEE VTS Proceedings of Vehicular Technology Conference 1999 spring, Houston, Texas, pp. 1594-1598, May 1999. [33] D. Sõropjatov, In-building radio network planning, Masters thesis, Tallinn, p. 51, 2005. [34] Y. Sun, F. Gunnarsson, K. Hiltunen, CPICH Power Settings in Irregular WCDMA Macro Cellular Networks. [35] TEMS Cellplanner Universal WCDMA Reference Guidelines.

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A. LOG-NORMAL FADING MARGINS A.1 SIMULATED LOG-NORMAL FADING MARGINS FOR 3-SECTOR SITES, MULTI-CELL ENVIRONMENT This appendix contains graphs showing the uplink log-normal fading margin, LNFmarg, required for achieving a certain area coverage probability. The soft handover graphs include soft handover gain. It is recommended to use the graphs valid for 3 dB soft handover enter threshold.

Figure A.1 Log-normal fading margins for 3-sector sites