wcdma radio network capacity planning

7/30/2019 WCDMA Radio Network Capacity Planning

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WCDMA Radio Network Capacity Planning

Huawei Technologies Co., Ltd.

All rights reserved


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WCDMA Radio Network Capacity Planning Confidentiality level: Customer

Mexico Training Center Confidential information of Huawei. Page 2/50


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Revision Record

Date Version Change description Author

1-07-2007 1A Victor Toledo


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Table of Contents

1 Traffic Model........................................................................................................ 9

Service overview............................................................................................ 9

QoS type ..................................................................................................... 11

Traffic Model................................................................................................ 12

CS Traffic Model......................................................................................... 13

PS Traffic Model .......................................................................................... 14

2 Uplink Capacity Analysis ................................................................................ 20

Uplink Interference Analysis- Uplink Interference Composition.................... 24

Uplink Interference Analysis- Uplink Load Factor ........................................ 23

3 Downlink Capacity Analysis ............................................................................ 26

Downlink Interference Analysis.................................................................... 29

4 Multi-service capacity estimation procedure ................................................. 30

Network capacity restriction factors ............................................................. 30

Downlink Channel code resources .............................................................. 32

Channel Element ........................................................................................ 34

Iub Interface Capacity ................................................................................. 36

Typical capacity design methods-Erlang B formula ..................................... 37

Typical capacity design methods- Equivalent Erlangs ................................. 41

Typical capacity design methods- Campbells theorem............................... 42

5 Network estimation procedure ........................................................................ 45

6 Capacity enhancement technologies.............................................................. 46

Transmission Diversity................................................................................. 46

Sectorization ................................................................................................ 48


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Objectives

Upon completion of this module, you will be able to:

Grasp the parameters of 3G traffic model

Understand the factors that restrict the WCDMA network capacity

Understand the methods and procedures of estimating multi-service

capacity

Understand the key technologies for enhancing network capacity


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Foreword

WCDMA is a self-interference system

WCDMA system capacity is closely related to coverage

WCDMA network capacity has the soft capacity feature

The capacity planning of the WCDMA network is performed under certain

traffic models


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1 Traffic Model

Service Overview

The WCDMA system supports multiple services

Variable-rate services (e.g. AMR voice)

Combined services (e.g. CS & PS)

High-speed data packet services (384k service)

Asymmetrical services (e.g. stream service )

Large-capacity and flexible service bearing

The WCDMA system provides the users with flexible and diversified services, whichis an important characteristic of WCDMA. In different propagation environment, the

WCDMA system requires reaching different target transmission rate values, e.g., in high-

speed motion, the rate is up to 144 kbps; in case of walking, the rate is up to 384 kbps,

and the rate in indoor environments is up to 2 Mbps. The WCDMA system supports the

variable-rate service, hybrid service, high-speed data packet service (multimedia);

supports uplink/downlink rate-asymmetrical services (Internet access); considers the

future service development requirements, and provides sufficient capacity and data

bearing capability of flexible rate matching methods. The QoS of the WCDMA service is

described by data rate, bit error rate (BER), transmission delay, and delay jitters.

Different services and service composition proportions affect the WCDMA performance

significantly. Therefore, the WCDMA network planning analysis should be based on the

prerequisite of a certain traffic model estimate.


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QoS Type

Table I.- Services and quality of service.

For the session-type service, requirement on end-to-end delay is strict. For example,

for the voice service, the delay is required to be smaller than 150ms, and must not

exceed 400ms; otherwise, it will be difficult to understand the voice. The session-type

services are typically carried by the CS domain. For the session-type services, the

system can perform no queue processing for the calls. In this case, we can use the

Erlang B formula or the extended Erlang B formula to calculate.

Compared with the session-type service, the stream-type service imposes low

requirement on the end-to-end delay. Generally, the stream-type service tolerates the

call waiting to a greater extent, and can provide the call queue mechanism. In this case,

we can use the Erlang C formula to calculate the blocking probability of this type of users

(defined as the probability of the call waiting for a specified time).

Interaction-type service refers to the service through which the user requests data

from the server. The service is described with the terminal users request response

pattern. Therefore, round-trip delay is the most important index of this service type. The

interaction-type services are typically carried on the CS domain. The background-service

tolerates delay to the greatest extent, and can tolerate the delay of a magnitude of an

hour. Due to such great delay tolerance, the system can save such requests in the busy

hour, and respond when the channel becomes idle; meanwhile, for such services, once a

request with higher QoS comes in, the processing can be stopped at any time. The


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system decides startup and termination at any time, the above formulasErlang B

formula and Erlang C formula are not applicable. Generally, according to the difference

between the maximum number of channels and the busy-hour average occupied

channels, we can calculate the traffic of the background-type service. The users of

traffic-type services also tolerate the call waiting to some extent. The system provides aqueue mechanism, and uses the Erlang C formula to calculate the blocking rate.

Objectives of Setting Up Traffic Model

In order to determine the system configuration, we need to determine the

capacity of the air interface first.

In the data service, different transmission model will generate different

system capacities.

We need to set up an expected data transmission model of the customer

so that we can plan the network properly.

In order to set up a right model, the operator should provide some statistic

data as reference.

The system has many key performance indicators, e.g., coverage, spectrum

efficiency, which are closely related to the type of service carried by the system.

Therefore, in order to predict the performance of the WCDMA system in carrying a

certain type of service, we must know the service features. Service features are

represented by the traffic model.


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Traffic Model

Traffic model is a means of researching the capacity features of each

service type and the QoS expected by the users who are using the service fromperspective of data transmission.

In the data application, the user behaviour research mainly forecasts the

service types available from the 3G, the number of users of each service type,

frequency of using the service, and the distribution of users in different regions.

Contents of a traffic model

The contents of a traffic model consist of service patterns and user behaviours.

Service pattern refers to the service features, and user behaviour refers to the conduct of

people in using the service. In the actual application, service pattern is closely related to,

and sometimes is no strictly different from, the traffic measurement model.

Figure 1.- The contents of the traffic model.

By determining the service pattern and the user behaviour parameters, we

determine the traffic models of various services in the network. By calculating the hybrid

services of multiple traffic models, we determine the network system configuration.


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Typical Service Features Description

Typical service features include the following feature parameters:

User type (indoor ,outdoor, vehicle)Users average moving speed

Service Type

Uplink and downlink service rates

Spreading factor

Time delay requirements of the service

QoS requirements of the service

For each service, since the channel structure and demodulation method are different,

the required uplink rate is different from the required downlink rate even for the same

service type and the same data rate. For a typical service, we first need to identify

whether it is uplink or downlink rate. A typical service can be described by the following

parameters:

(1) User type (indoor users, users inside a vehicle, outdoor users)

(2) Users average moving speed (km/h)

(3) Voice, real-time data, non real time data

(4) Uplink and downlink service rates (kbps)

(5) Spread factor (SF)

(6) Signal delay requirement of the service (ms) The above parameters

ultimately determine the QoS requirements of the service.


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CS traffic model

Voice service is a typical CS services. Voice data arrival conforms to the

Poisson distribution. Its time interval conforms to the exponent distribution. Key parameters of the model:

Penetration rate

BHCA Mean busy-hour call attempts

Mean call duration (s)

Activation factor

Mean rate of service (kbps)

(Erl)For CS service, mean busy-hour traffic (Erlang) per user = BHCA * mean call

duration /3600 (Erl)

(kbps)Mean busy-hour throughput per user = BHCA * mean call duration * activation

factor * mean rate of service (kbps)

In the actual application, service pattern is closely related to, and sometimes is no

strictly different from, the traffic measurement model.

CS Traffic Model Parameters

Mean busy-hour traffic (Erlang) per user = BHCA * mean call duration

/3600

Mean busy hour throughput per user (kbit) (G) = BHCA * mean call

duration * activation factor * mean rate

Mean busy hour throughput per user (bps) (H) = mean busy hour

throughput per user * 1000/3600


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PS traffic model

The most frequently used model is the packet service session process

model described in ETSI UMTS30.03.

Figure 2.- Packet service session.

Figure 3.- Packet session description.


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PS Traffic Model Parameters

Figure 4.- Parameters used in the PS traffic model.

The service pattern-related parameters in the traffic model include: these

parameters commonly determine the pattern of one session.

We identify the service types through the different values of the parameters.

Packet Call Num/Session: Takes on the geometric random distribution

Reading Time (sec): Takes on the geographic random distribution

Packet Num/Packet Call: Takes on the geographic random distribution

Packet size: Takes on the Pareto random distribution

When using the parameters, the average values will apply.

Parameter Determining

The basic parameters in the traffic model are determined in the following

ways:

Obtain numerous basic parameter sample data from the existing

network.

Obtain the probability distribution of the parameters through

processing of the sample data.

Take the distribution most proximate to the standard probability as

the corresponding parameter distribution through comparison with the

standard distribution function.


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We have determined the traffic model parameters. The linchpin is to determine such

parameter values. The parameter value varies between different services.

ParetoGeneral standard probability distributions include: logarithmic normal distribution,

Pareto distribution, geometrical distribution, and negative exponent distribution.

Typical Bearer Rate (kbps)

Bearer rate is variable in the actual transmission process.

BLER:

In the PS service, when calculating the data transmission time, the

retransmission caused by erroneous blocks should be considered.

Suppose the data volume of service source is N, the air interface block

error rate is BLER, the total required data volume to be transmitted via the

air interface is:

During the planning, according to the actual situation, we select the typical value of

the bear rate. It will affect the activation factor, but will not affect the correctness of the

planning result.

Block error rate belongs to QoS. The service control mechanism will retransmit the

erroneous blocks. This will increase the traffic to be transmitted.

PS User Behavior Parameters

Figure 5.- User behavior parameters for PS.


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The country, region, life custom and economic level will affect the service

distribution. In the planning, we divide the users into high-end users, mid-end users and

low-end users, and believe that the BHSA and penetration rate are different between

different types of user groups. Currently, we can only use the existing analysis to make

prediction. In the future, the progress of the construction of the WCDMA pilot system will

provide us with reference.

Penetration Rate

The percentage of the users that activates this service to all the

users registered in the network.

BHSA

The times of single-user busy hour sessions of this service

User Distribution (High, Medium, Low end)

The users are divided into high-end, mid-end and low-end users.

Different operators and different application situations will have different

user distributions.

PS Traffic Model Parameters

Session traffic volume Byte Average traffic of single session of the

service

Data transmission time (s) The time in a single session of service for

purpose of transmitting data.


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Holding Time s Average duration of a single session of service

Active factor:

The weight of the time of service full-rate transmission among the

duration of a single session.

Busy hour throughput per user (Kb):

PS throughput equivalent Erlang formula (Erlang)


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2 Uplink capacity analysis

Uplink Interference AnalysisUplink Interference Composition

Basic Principles

In the WCDMA system, all the cells share the same frequency, which is

beneficial to improve the system capacity. However, co-frequency multiplexing

causes interference between users. This multi-access interference restricts the

capacity. The radio system capacity is decided by uplink and downlink. When

planning the capacity, we must analyze from both uplink and downlink

perspectives.

Interference is the main factor that decides the system performance of the cellular

system. The interference in a cellular system consists of two parts: co-frequency and

adjacent frequency interference. All users in the WCDMA system use the same band. All

the users are different by modulating the respective signal to the code sequences thatare mutually orthogonal. Therefore, the receiving signal is the sum of all user signals and

the channel noise.


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Receiver noise floor PN

K Boltzmann constant, 1.38

T Kelvin temperature, normal temperature: 290 K

W Signal bandwidth, WCDMA signal bandwidth 3.84MHz

10lg(KTW) = -108dBm/3.84MHz

NF = 3dB (typical value of macro cell BTS)

IOwn Interference from users of this cell

Interference that every user must overcome:

is the receiving power of the user j , is active factor

Under the ideal power control :

Hence :

The interference from users of this cell is the sum of power of all the

users arriving at the receiver:

:Interference from users of adjacent cell


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The interference from users of adjacent cell is difficult to analyze

theoretically, because it is related to user distribution, cell layout, and

antenna direction diagram.

Adjacent cell interference factor

When the users are distributed evenly

For omni cell, the typical value of adjacent cell interference

factor is 0.55

For the 3-sector directional cell, the typical value of adjacent

cell interference factor is 0.65

Uplink Interference Analysis

Define


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Uplink Interference AnalysisUplink Load Factor

Define the uplink load factor

When the load factor is 1, is infinite, and the corresponding capacity is called

threshold capacity.

Under the above assumption, the threshold capacity is approx 96 users.

Uplink Interference AnalysisLoad Factor and Interference

According to the above mentioned relationship, the noise will rise:

Suppose that:

All the users are 12.2 kbps voice users,the demodulation threshold Eb/No = 5dB

Voice activation factor vj = 0.67Adjacent cell

interference factor i = 0.55

Figure 6.- Total Interference calculation.


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Figure 7.- Noise raise against Load factor.

Uplink Interference AnalysisLimitation of the Current Method

The above mentioned theoretic analysis uses the following simplifying

explicitly or implicitly:

No consideration of the influence of soft handover

The users in the soft handover state generates the

interference which is slightly less than that generated by ordinary

users.No consideration of the influence of AMRC and hybrid service

AMRC reduces the voice service rate of some users, and

makes them generate less interference, and make the system

support more users. (But call quality of such users will be

deteriorated)


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Different services have different data rates and demodulation

thresholds. So, we should use the previous methods for analysis,

but it will complicate the calculation process.

Since the time-variable feature of the mobile transmission

environment, the demodulation threshold even for the same service

is time-variable.

Ideal power control assumption

The power control commands of the actual system have

certain error codes so that the power control process is not ideal,

and reduces the system capacity

Assume that the users are distributed evenly, and the adjacent cell

interference is constant.

Considering the above factors, the system simulation is a more

accurate method:

Static simulation: Monte Carlo method

Dynamic simulation


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3 Downlink Capacity Analysis

Downlink Interference AnalysisDownlink Interference Composition


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Suppose the power control is desired, we obtain

Then

Because


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Then

Resolve PT to obtain

where ij is the adjacent cell interference factor of the user,

defined as:

According to the above analysis, we can define the downlink load factor:

When the downlink load factor is 100%, the transmitting power of the BTS

is infinite, and the corresponding capacity is called threshold capacity.

As different from the theoretic calculation of uplink capacity, and in

the downlink capacity formula are variable related to user position. Namely, the

downlink capacity is related to the spatial distribution of the users, and can only be

determined through system simulation.


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Downlink Interference AnalysisSimulation Result

Figure 8.- Result simulation for downlink interference analysis.

Downlink Interference AnalysisSimulation Result Analysis

When the transmitting power of the BTS is 43dBm (20W), the supported

maximum number of users is approx 114.

In order to ensure system stability, we do not allow the mean transmitting


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power of the BTS to be more than 80% of the maximum transmitting power,

namely, 42dBm. This way, the supported number of users is 111.

4 Multi-service capacity estimation

Network capacity restriction factors

The WCDMA network capacity restriction factors in the radio network part

include the following:

Uplink interference

Downlink power

Downlink channel code resources (OVSF)

Channel element (CE)

Iub interface transmission resources

Uplink interference

If the uplink interference of the BTS reaches a certain extent, the terminal will be

impossible to meet the requirements of demodulation quality through improving the

transmitting power, and the terminal will be impossible for access or service.

Downlink power

When the downlink transmitting power of the BTS reaches the load threshold, no

redundant power is available for allocation. This will make the terminal impossible for

access or service.


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Downlink channel code resources

In the downlink direction, scrambles are used for identifying the cells, while the

channel codes are used for identifying the channels. The WCDMA system uses the

orthogonal variable spread factor (OVSF) code sequence in a tree distribution. The

actually usable code sequence set is made up of the code words of SF=4~128.

Channel processing unit

In view of cost, the Channel element will be configured to full capacity. In this case,

the circumstance may occur that no channel units are available for allocation.

Iub interface capacity

The Iub interface currently still uses the E1 link as physical media, which may a

bottleneck to the radio network capacity.

Downlink Transmit Power

The downlinktransmit power has two parts: one part is used for common

channel, and the other part for dedicated (traffic) channel.

The transmit power is allocated by the cell to each user varies with service

demodulation threshold, propagation path loss and the interference received by

the user

The downlink transmit power of the cell is shared by all the users in the cell

We generally use the simulation method to analyze the downlink

interference.


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Figure 9.- UE number against downlink NodeB power.

The transmitting power allocated by the cell to each user varies with service

demodulation threshold, propagation path loss and the interference received by the user.

The propagation path loss is related to the users position relative to this cell. The users

position relative to the adjacent cell BTS and this cells BTS, and the transmitting power

of this cells BTS and the adjacent cell BTS decide the interference received.

The downlink transmitting power of the cell is shared by all the users in the cell.

When the maximum transmitting power among the downlink transmitting powers that

arrive at the BTS reaches a certain threshold, the new users will be impossible to access.

Therefore, we can define the ratio of the downlink power of cell to the maximum

transmitting power of the BTS as the downlink load of the cell.

Due to the complexity of the downlink capacity analysis, we generally use the

emulation method to analyze it.

Downlink Channel Code Resources

The WCDMA network use the codes whose SF is 4~512. The smaller the

SF is, the higher the supported data rate will be.


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In the code tree, the allocable codes should meet the following conditions:

No codes on the path from this code to the root node of code tree

are allocated

No codes in the sub-tree whose root node is this code are allocated

Try to reserve the code words whose SF is small, so as to improve

the utilization efficiency.

Figure 10.- OVSF codes.

The generation of the channel code uses the Hadamard matrix. The downlink

OVSF codes are like a code tree, and the SF is spread factor.

In the process of code allocation, it is appropriate to try to reserve the code wordswhose SF is small for purpose of improving utilization, because the code words whose

SF is small can support higher data rates and can be split into code words whose SF is

larger.


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Downlink Channel Code Resources

Figure 11.-Example of code resources allocation.

Channel Element (CE)

The Channel element the quantitative data that measures the resources


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logically occupied for service processing.

The resource occupied by the service processing is mainly related to the

spreading factor of this service. The smaller the SF is, the greater the data traffic

will be, and more resources will be occupied.

The SF of typical services are:

AMR12.2kbps SF=128

CS64kbps SF=32

PS64kbps SF=32

PS144kbps SF=16

PS384kbps SF=8

Due the technical features of the WCDMA, compared with the 2G systems such as

GSM, the RNC and Node B present enormous capacity. For example, for the fully

configured NodeB, the number of channels of one carrier is 128, which is more than 10

times of that supported by a TRX of GSM. One uplink processing unit of our NODEB 1.3has the processing capacity of 128 12.2kbps voice channels. One 3*1 WCDMA BTS is

equivalent to the GSM sites of one S10/10/10. At the beginning of the WCDMA network

construction, so high a capacity is not a necessity, and only a portion of it is required

(e.g., 10%). If we offer the quotation based on the maximum hardware channel capacity

of TRX like the GSM, it will make the operators incur enormous cost and mismatch the

user quantity. To reduce the initial investment, the operator is bound to pay the

equipment price to the supplier according to the actual use capacity, and, subsequently,

pay more equipment prices with the increase of the user quantity. This way, the operatorwill reduce the initial investment and mitigate the risks.

If we define the resources required for processing AMR 12.2kbps services

as a channel processing unit, the number of channel processing units occupied by

other services is:


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AMR12.2kbps 1

CS64kbps 4

CS144kbps 8

CS384kbps 16

PS64kbps 4

PS144kbps 8

PS384kbps 16

The relative proportion of the services with different SFs can be calculated in the

following formula (related to version):

Num_SF128/128 + Num_SF64/64 + Num_SF32/32 + Num_SF16/16 + Num_SF8/8=

1

The channel unit of service can represent the channel resources occupied when

establishing the connection. It will be used when calculating the hybrid service capacity

of the cell. It is used for calculating the number of required channel boards and thenumber of channel processing units configured on the board.

Iub Interface Capacity

The contents transmitted on the Iub interface include:

The user data encapsulated in the AAL2 format (common channel

and dedicated channel)

Signaling data encapsulated in the AAL5 formatBTS operation & maintenance data


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Figure 12.- Protocol stack for Iub interface.

When calculating the Iub interface traffic, it is necessary to calculate the throughput

rate of each service type. According to the planned user quantity, we obtain the total

traffic of the Iub interface, and estimate out the transmission configuration of the Iub

interface.

Factors to be considered when estimating the interface capacity:

Frame coding efficiency. Through segmentation and encapsulationof the application data at each layer, the data quantity at the bottom layer

will be increased to different extents compared with the application data at

the upper layers.

Traffic. More users will generate more data traffic.

Maintenance efficiency. Certain bandwidth is required in the

background maintenance for BTS data transmission.

Typical capacity design methods

Erlang-B Formula

The Erlang-B formula is used for estimating the peak traffic that meets


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certain call loss rate when the average traffic (Erlang) is given.

The Erlang-B formula is only used for

Circuit switched services

Single service

The WCDMA system provides CS and PS domain multi-services which are

determined by the radio network planning.

Figure 13.- Variation of demand with time.

In the CS domain, we use the Erlang quantity to express the traffic volume. Assumethe traffic arrival takes on a Poisson distribution.

The prerequisite of the Erlang-B is the requests of resources take on a

Poisson distribution, namely, its variance is equal to its mean value.

If, when a service establishes a link, the service requires the resources

which are more than the unit resources, the resource request is no longer equal to

its mean value, and the Erlang-B formula is not applicable in this case.

Comparison of multi-service capacity estimation methods :

Post Erlang-B

Equivalent Erlangs

Campbells Theorem

For the unitary CS services, the resources are estimated in unit resources, e.g., a


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64kbps timeslot.

Post Erlang-B

By summing up the capacities required for different services, we obtain the

capacities required for the combined services.

No consideration of the resource efficiency of different services

Figure 14.- Post Erlang B (-) resources calculation.


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Method of using the Post Erlang-B: First, calculate the channel resources required

according to the traffic volume of each service, then sum up the channel resources

required for all services. This method is vulnerable to overestimation of the channel

resources. We will understand this through the following example.

Consider that two services share resources

Service 1: 1 unit resource/connection.12 Erlang

Service 2: 3 unit resources/connection.6 Erlang

Calculate capacity required for each service

Service 1: 12 Erlangs require 19 connections (19 unit resources),

meeting the 2% blocking rate

Service 2: 6 Erlangs require 12 connections (equivalent to the 36

unit resources of service 1), meeting the 2% blocking rate

Total 55 unit resources

Consider that two services use the same resources



Calculate capacity required for each service

Service 1: 12 Erlangs require 19 connections, meeting the 2%

blocking rateService 2: 6 Erlangs require 12 connections, meeting the 2%

blocking rate

Total 31 unit resources

However, the reasonable results should be: 18 Erlangs require 26


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connections for meeting the 2% blocking rate.

As seen from the above example, two services with the same unit resources have

18Erlangs in total. The actually required channel resources are 26 resources. However,

according to the Post Erlang-B method, 31 resources are required. So this method

obviously overestimates the required channel resources.

Equivalent Erlangs

By converting the bandwidth from one service to another service, combine

different services and then calculate the required capacity.

Selecting different services as the measurement benchmark will lead to

different capacity requirements.


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Figure 15.- Equivalent Erlang estimations.

The equivalent Erlang method is to convert the service of two service with different

unit channel resources to the total Erlangs of one of the services, then search the

Erlang-B table to obtain the total channel resources required. In this method, if selecting

different services as measurement benchmark, different channel resource requirements

will result.

Consider that two services share resources


Service 2: 3 unit resources/connection.6 Erlang

If using service 1 as measurement benchmark, the two services are

equivalent to 30 Erlangs in total.

30 Erlangs require 39 connections (39 unit resources), meeting the2% blocking rate

If using service 2 as measurement benchmark, the two services are

equivalent to 10 Erlangs in total.

10 Erlangs require 17 connections (equivalent to 51 unit resources

of service 1), meeting the 2% blocking rate

As seen from the above example, if the calculation uses service 1 as benchmark,

the result is 39 channel resources; if the calculation uses service 2 as benchmark, the

result is 51 channel resources required. The difference between the two results is 12

channel resources.


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Campbells Theorem (I)

The Campbell theorem introduces the mean value and variance, so that the multi-

service capacity calculation result is more proximate to the actual value compared with

the foregoing two methods. Here, the amplitude ai represents the channel resources

required for a single connection. Generally, we specify the amplitude of the Voice12.2k

service as 1, hence:

Amplitude of other service relative to the Voice12.2k service = (service bit rate *

Eb/No) / (Voice12.2k service bit rate * Eb/No of Voice service)


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For the same GoS, different services require different capacities. According to the

calculation method of the Campbell theorem, as calculated respectively on the

benchmark of service 1 and service 2, the obtained two results will be only 2 channel

resources different from each other.

The comparison of the different capacity method

Post Erlang-B

Service 1 (1 unit resource/connection, 12Erl) and service 2 (3 unit

resources / connection, 6Erl), requiring 55 unit resources in total

Equivalent Erlangs

Calculated according to benchmark of service 1 (1 unitresource/connection, 12Erl), a total of 39 unit resources are required

Calculated according to benchmark of service 2 (3 unit

resources/connection, 6Erl), a total of 51 unit resources are required

Campbells Theorem

In the same conditions, 47~49 unit resources are required in total.

As illustrated for the three methods above, we assume that the conditions are

identical, calculation result through the Post Erlang-B method is 55 channel resources

required; the calculation result through the Erlang method is 39~51 channel resources

required; and the calculation result through the Campbell method is 47~49 channel

resources required. The calculation result through the Campbell theorem is more


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proximate to the actual value compared with the other two methods.

5 Network estimation procedure


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Figure 16.- Network estimation flow.

6 Capacity Enhancement Technologies

Transmission Diversity

TxDiv

Txdiv has two types in WCDMA system:

Open loop TxDiv


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Closed loop TxDiv

TxDiv could improve downlink capacity

Need additional amplifier

Need equipment support

Dont need additional antenna

Figure 17.- Transmission Diversity feature.

Gain of TxDiv

The gain is obtained due to additional amplifier

Pure gain is obtained due to TxDiv technology


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Figure 18.- Downlink capacity with Tx diversity.

Gain of TxDiv

The gain is obtained due to additional amplifier

Pure gain is obtained due to TxDiv technology

TxDiv should reduce downlink power

TxDiv should reduce requirement of Eb/N0

Usually ,closed loop TxDiv would obtain more gain than open loop TxDiv.

Figure 19.- Comparison of target Tx Eb/No.

Transmission diversity can enhance the downlink capacity and coverage.

Conclusion of capacity enhancement of transmission diversity

STTD mode: Capacity increase of 17 ~ 24%


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TxAA(1) mode: Capacity increase of 16 ~ 23%

TxAA(2) mode: Capacity increase of 31 ~ 37%

For the single-antenna transmitting, transmitting diversity can obtain extra

gain to enhance the capacity and coverage.

In the WCDMA system, transmitting diversity breaks down into two types:

open loop transmitting diversity, and closed loop transmitting diversity. The latter

is subdivided into two modes. Different transmitting diversity modes obtain

different gains.

Here the calculation of capacity and coverage of gain is similar to that of

receiving diversity. The main affecting factor is the downlink capacity coverage

and capacity.

Sectorization

In the dense urban areas and the normal urban areas with high traffic,

increasing sectors of the BTS is a method of improving the capacity. 6-sectors BTS generally use the antenna whose horizontal lobe is 33

The capacity of a 6-sector BTS is 1.67 times that of a 3-sector BTS

The capacity of a 3-sector BTS is 2.77 times that of a omni- BTS

When there are many sectors, e.g., 6 sectors, it is necessary to plan the

mount height, azimuth angle and down tilt angle of the antenna carefully.

In order to obtain higher capacity, the sector azimuth angle should be

designed as mutually complementary to prevent blind area of coverage. For 3-

sector and 6-sector circumstances, the azimuth angle can be planned with the


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regular hexagon apex excitement method.

The down tilt angle of the antenna should be designed properly to align

the upper half power point of the antenna lobe with the cell edge.

From perspective of the BTS capacity, when the cell radius is small, the

capacity of a 3-sector BTS is 2.77 times that of an omnidirectional BTS, and the

capacity of a 6-sector BTS is 1.67 times that of a 3-sector BTS.

When the cell radius increases, the sectors will increase, and the sector

antenna gain will be higher. For the uplink, the coverage performance will be

better; for the downlink, the coupling loss will be less, and the downlink capacity

will be higher.


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wcdma radio network capacity planning

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