2 WCDMA Radio Network Capacity Planning

8/11/2019 2 WCDMA Radio Network Capacity Planning

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WCDMA Radio Network Capacity Planning

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Copyright 2008 Huawei Technologies Co., Ltd. All rights reserved.

WCDMA RadioNetwork CapacityPlanning

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Page1Copyright 2008 Huawei Technologies Co., Ltd. All rights reserved.

Forewordl WCDMA is a self-interference system

l WCDMA system capacity is closely related to coverage

l WCDMA network capacity has the soft capacity ! feature

l The WCDMA network capacity restriction factors in the radio networkpart include the following:

p Uplink interference

p Downlink power

p

Downlink channel code resources (OVSF)p Channel element (CE)



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Objectives

l Upon completion of this course, you will be able to:p Grasp the parameters of 3G traffic model

p Understand the factors that restrict the WCDMA network capacity

p Understand the methods and procedures of estimating multi-service capacity

p Understand the key technologies for enhancing network capacity



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Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

5. Network Dimensioning Flow



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Contents

1. Traffic Model

1.1 Overview of traffic model

1.2 CS traffic model

1.3 PS traffic model



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QoS Type

Data integrity should be maintained. Small delay

restriction, requiring correct transmission

Request-response mode, data integrity must be

maintained. High requirements on error tolerance,

low requirements on time delay tolerance

Typically unidirectional services, high requirements

on error tolerance, high requirements on data rate

It is necessary to maintain the time relationshipbetween the information entities in the stream.

Small time delay tolerance, requiring data rate

symmetry

Background

download of

EmailBackground

Web page

browse,

network gameInteractive

N onr e al -t i m

e c at e g or y

Streaming

multimediaStreaming

Voice service,videophone

ConversationalR e al -t i m

e c at e g or y

l For the session-type service, requirement on end-to-end delay is strict. For example, for the voiceservice, the delay is required to be smaller than 150ms, and must not exceed 400ms, otherwise, itwill be difficult to understand the voice. The session-type services are typically carried by the CSdomain. For the session-type services, the system can perform no queue processing for the calls. Inthis case, we can use the Erlang B formula or the extended Erlang B formula to calculate.

l Compared with the session-type service, the stream-type service imposes low requirement on theend-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 tocalculate the blocking probability of this type of users (defined as the probability of the call waitingfor a specified time).

l Interaction-type service refers to the service through which the user requests data from the server. The service is described with the terminal user "s request response pattern. Therefore, round-trip

delay is the most important index of this service type. The interaction-type services are typicallycarried on the CS domain. The background-service tolerates delay to the greatest extent, and cantolerate the delay of a magnitude of an hour. Due to such great delay tolerance, the system cansave such requests in the busy hour, and respond when the channel becomes idle; meanwhile, forsuch services, once a request with higher QoScomes in, the processing can be stopped at any time.

The system decides startup and termination at any time, the above formulas # Erlang B formula andErlang C formula are not applicable. Generally, according to the difference between the maximumnumber of channels and the busy-hour average occupied channels, we can calculate the traffic ofthe background-type service. The users of traffic-type services also tolerate the call waiting to someextent. The system provides a queue mechanism, and uses the Erlang C formula to calculate theblocking rate.



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Traffic Model

System Configuration

User Behaviour

Service Pattern

Traffic ModelResults

l By determining the service pattern and the user behaviour parameters, we determine thetraffic 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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The Contents of Traffic Model

l Service pattern refers to the service features

l User behaviour refers to the conduct of people in using the

service

l Service pattern is a means of researching the capacity features of each service type and theQoSexpected by the users who are using the service from perspective of data transmission.

In the actual application, service pattern is closely related to, and sometimes is no strictlydifferent from, the traffic measurement model.

l In the data application, the user behaviour research mainly forecasts the service typesavailable from the 3G, the number of users of each service type, frequency of using theservice, and the distribution of users in different regions



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Typical Service Features Description

l Typical service features include the following feature

parameters:

p User type (indoor ,outdoor, vehicle)

p User " s average moving speed

p Service Type

p Uplink and downlink service rates

p Spreading factor

p Time delay requirements of the service

l For each service, since the channel structure and demodulation method are different, therequired 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 isuplink or downlink rate. A typical service can be described by the following parameters:

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

p User "s average moving speed (km/h)

p Voice, real-time data, non real time data

p Uplink and downlink service rates (kbps)

p Spread factor (SF)

p Signal delay requirement of the service (ms).

l The above parameters ultimately determine the QoSrequirements of the service.



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Contents

1. Traffic Model






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

the Poisson distribution. Its time interval conforms to the exponentdistribution

l Key parameters of the model

p Penetration rate

p BHCA: busy-hour call attempts

p Mean call duration (s)

p Activity factor

p Mean rate of service (kbps)

l Penetration rate: The percentage of the users that activates this service to all the usersregistered in the network.

l Activity Factor: The weight of the time of service full-rate transmission among the durationof a single session.



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CS Traffic Model Parameters

l Mean busy-hour traffic (Erlang) per user =BHCA mean call duration/3600

l Mean busy hour traffic volume per user (kbit) =BHCA mean call

duration activity factor mean rate

l Mean busy hour throughput per user (bps) =mean busy hour traffic

volume per user 1000/3600

l (Erl) For CS service, mean busy-hour traffic (Erlang) per user =BHCA * mean call duration/3600 (Erl)

l (kbps) Mean busy-hour throughput per user =BHCA * mean call duration * activity factor *mean rate of service*1000/3600 (kbps)



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Contents

1. Traffic Model






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PS Traffic Model

Data Burst Data Burst Data Burst

Packet Call

Session

Packet Call Packet Call

Downloading Downloading

Active Dormant Dormant Active

l The most frequently used model is the packet service session process model described inETSI UMTS30.03.



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PS Traffic Model Parameters

Traffic Model

Packet Call Num/Session

Packet Num/Packet Call

Packet Size (bytes)

BLER

Typical Bear Rate (kbps)

Reading Time (sec)

l The service pattern-related parameters in the traffic model include: these parameterscommonly determine the pattern of one session.

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

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

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

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

p Packet size: Takes on the Pareto random distribution

l When using the parameters, the average values will apply.



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Parameter Determiningl The basic parameters in the traffic model are determined in the

following ways:

p Obtain numerous basic parameter sample data from the existingnetwork

p Obtain the probability distribution of the parameters throughprocessing of the sample data

p Take the distribution most proximate to the standard probabilityas the corresponding parameter distribution through comparisonwith the standard distribution function

l We have determined the traffic model parameters. The linchpin is to determine suchparameter values. The parameter value varies between different services. Pareto General

standard probability distributions include: logarithmic normal distribution, Paretodistribution, geometrical distribution, and negative exponent distribution.



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PS User Behaviour Parameters

User Behaviour

User Distribution

(High, Medium, Low end)

BHSA

Penetration Rate

l The country, region, life custom and economic level will affect the service distribution. Inthe 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 ofuser groups. Currently, we can only use the existing analysis to make prediction. In thefuture, the progress of the construction of the WCDMA pilot system will provide us withreference.



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PS User Behaviour Parameters

l Penetration Rate

l BHSA

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

l User Distribution (High, Medium, Low end)

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

l Penetration Rate: The percentage of the users that activate this service to all the usersregistered in the network. It varies between different service types, user types, and

operators. More importantly, it is related to the penetration rate and time. With the elapseof time, the penetration rate will increase gradually.

l BHSA: Times of the single-user busy hour sessions of the service. It varies between servicetypes and user types.

l User Distribution (High, Medium, Low end): The users are divided into high-end, mid-end and low-end users according to the ARPU. Different operators and differentapplication situations will have different user distributions.



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PS Traffic Model Parametersl Data Transmission time (s): The time in a single session of service for

purpose of transmitting data.

l Holding Time (s): Average duration of a single session of service

l Activity Factor:

e HoldingTimissionTime DataTransm

ctor ActivityFa =

eTypicalRat BLER fficVolumeSessionTra

issionTime DataTransm 1

11000/8

=

issionTime DataTransmadingTime Re )1Session

lNum PackketCal ( e HoldingTim +=

l In the PS service, when calculating the data transmission time, the retransmission causedby 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 transmittedvia the air interface is

N BLER

BLER N BLER N BLER N BLER N N n *1

1**** 32

=+++++ LL



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Contents

1. Traffic Model



4. CE Dimensioning




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Basic Principles

l In the WCDMA system, all the cells use the same frequency,

which is conducive to improving the WCDMA system capacity.

However, for reason of co-frequency multiplexing, the system

incurs interference between users. This multi-access

interference restricts the capacity in turn.

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

When planning the capacity, we must analyze from both uplink

and downlink perspectives.

l 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 usersare different by modulating the respective signal to the code sequences that are mutuallyorthogonal. Therefore, the receiving signal is the sum of all user signals and the channelnoise.



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Contents


2.1 Uplink Interference Analysis

2.2 Downlink Interference Analysis



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Uplink Interference Analysis

l Uplink interference analysis is based on the following formula:

N other ownTOT P I I I ++=

l Where:

p : Total interference received by NodeB

p : Interference from the users of this cell

p : Interference from the users of adjacent cells

p : Noise floor of the receiver

own I

other I

N P

TOT I



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l Receiver noise floor: P N

p For Huawei NodeB, the typical value is -106.4dBm/3.84MHZ

NF W T K P N += )**log(10

l K : Boltzmann constant, 1.38 10 -23 J/K

l T : Temperature in Kelvin, normal temperature: 290 K

l W : Signal bandwidth, WCDMA signal bandwidth 3.84MHz

l N th =10log(K*T*W)=-108dBm/3.84MHz

l NF : For Huawei NodeB, typical value is 1.6dB.



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l : Interference from users of this cell

p Interference that every user must overcome is :

p is the receiving power of the user j , is UL activityfactor

p Under the ideal power control :

p Hence:

p

The interference from users of this cell is the sum of power of allthe users arriving at the receiver:

own I

jtotal P I

j j P ( )

j j jTOT

j No Eb

RW

P I

P j Avg

110 10

/ _

=

( ) j j

No Eb

TOT j

RW

I P

j Avg

1

10

11

10

/ _ +

=

= N

jown P I 1

l Activity Factor: The weight of the time of service full-rate transmission among the durationof a single session. Which is defined by the following formula:

e HoldingTimissionTime DataTransm

or ActiveFact =



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l :Interference from users of adjacent cell

p 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.

p Adjacent cell interference factor

own

other

I

I f =

other I

l When the users are distributed evenly

p For omni cell, the typical value of adjacent cell interference factor is 0.55

p For the 3-sector directional cell, the typical value of adjacent cell interference factoris 0.65



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( )( )

N N

j j No Eb

TOT N other ownTOT P

RW

I f P I I I

j Avg

++

+=++= 1

10

/

1

10

11

1

_

( ) j j

No Eb

j

RW

L

j Avg

1

10

11

1

10

/ _ +

=

( ) N N

jTOT TOT P L f I I ++= 1

1

Define:

Then:

( ) +=

N

j

N TOT

L f P I

1

11

1Obtain:

l Where:

p N is the number of users in the cell.



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Uplink Interference Analysisl Suppose that:

p All the users are 12.2 kbps voice users, Eb/No Avg =5dB

p Voice activity factor =0.67

p Adjacent cell interference factor f =0.55

j

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



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Uplink Interference Analysisl According to the above mentioned relationship, the noise will rise:

UL N

j N

TOT

L f P I

NoiseRise

=+

==

11

)1(1

1

1

l The NoiseRise is used in link budget to estimate the Interference Margin

l If uplink cell load is 50%, NoiseRisewill be 3dB





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l Define the uplink load factor for one user:

l Define the uplink load factor for the cell:

( ) ( )( )

++=+= N

j j EbvsNo

N

jUL

RW f L f

j Avg

1

10

1 1

10

11

111

_

( ) ( )( )

j j EbvsNo

j j

RW

f L f

j Avg

1

10

11

111

10 _

++=+=

l When the uplink load factor is 1, is infinite, and the corresponding capacity is calledthreshold capacity ! .

TOT I



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Uplink Interference Analysis Limitation

l The above mentioned theoretic analysis uses the following simplifyingexplicitly or implicitly:

p No consideration of the influence of soft handoverp No consideration of the influence of AMRC and hybrid service

p Ideal power control assumption

p Assume that the users are distributed evenly, and the adjacent cellinterference is constant

l Considering the above factors, the system simulation is a moreaccurate method:

p Static simulation: Monte_Carlo methodp Dynamic simulation

l No consideration of the influence of soft handover

p The users in the soft handover state generates the interference which is slightly lessthan that generated by ordinary users.

l No consideration of the influence of AMRC and hybrid service

p AMRC reduces the voice service rate of some users, and makes them generate lessinterference, and make the system support more users. (But call quality of suchusers will be deteriorated)

p Different services have different data rates and demodulation thresholds. So, weshould use the previous methods for analysis, but it will complicate the calculationprocess.

p Since the time-variable feature of the mobile transmission environment, thedemodulation threshold even for the same service is time-variable.

l Ideal power control assumption

p The power control commands of the actual system have certain error codes so thatthe power control process is not ideal, and reduces the system capacity

l Assume that the users are distributed evenly, and the adjacent cell interference is constant



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Contents


2.1 Uplink Interference Analysis

2.2 Downlink Interference Analysis



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Downlink Interference Analysis

l Downlink interference analysis is based on the following

formula:

N other ownTOT P I I I ++=

l Where:

p : Total interference received by UE

p : Interference from downlink signal of this cell

p : Interference from downlink signal of adjacent cells

p : Noise floor of the receiver

own I

other I

N P

TOT I



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l :Interference from downlink signal of this cell

p The downlink users are identified with the mutually orthogonal

OVSF codes. In the static propagation conditions without multi-

path, no mutual interference exists.

p In case of multi-path propagation, certain energy will be detected

by the RAKE receiver, and become interference signals. We define

the non-orthogonal factor to describe this phenomenon:

own I

TX jown P I = )(

l Compared to the uplink load equation, the most important new parameter is , whichrepresents the non-orthogonality factor in the downlink. WCDMA employs orthogonal

codes in the downlink to separate users, and without any multi-path propagation theorthogonalityremains when the base station signal is received by the mobile. However, ifthere is sufficient delay spread in the radio channel, the mobile will see part of the basestation signal as multiple access interference. The orthogonality of 1 corresponds toperfectly orthogonal users. Typically, the non-orthogonalityis between 0.1 and 0.6 inmulti-path channels.

l Where:

p P TX is the actual transmission power of NodeB



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l : Interference from the downlink signal of adjacent cell

p The transmitting signal of the adjacent cell NodeB will cause

interference to the users in the current cell. Since the scrambling

codes of users are different, such interference is non-orthogonal

p Hence we obtain:

other I

TX jother P f I =)(

l Where:

p is Adjacent cell interference factor

p P TX is the actual transmission power of NodeB

f



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l Under the ideal power control:

l Then we can get:

j j j

No Eb

RW

Io Ec j

1)(10 10

)/(

=

j

TX

P CL

TX j

No Eb

j RW

P f P

P

N j

/

)10

(1010/)(

10

)/( +

++=

l Where:

p W is the chip rate, which is 3.84Mcps

p R j is the bit rate of service.

p is the activity factor. j



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Downlink Interference Analysisl According to the above mentioned relationship, the noise will rise:

( ) N

DL Max

N

other own N

N

total

P CL P f No

P I I P

P I

NoiseRise / ++=

++==

l The NoiseRise is used in link budget to estimate the Interference Margin



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Contents

1. Traffic Model



4. CE Dimensioning




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Capacity Dimensioning FlowDimensioning Start

Assumed Subscribers

CS Peak Cell Load(MDE)

Yes

No

CS Average Cell Load PS Average Cell Load

=Target Cell Load?

Dimensioning End

Total Cell Load

Load per Connection of R99

HSPA Cell Load

} Load Load Load , Load max{ Load HSUPAavg PS avg CS peak CS UL _ total cell ++=

CCH HSDPAavg PS avg CS peak CS DL _ total cell Load } Load Load Load , Load max{ Load +++=

l For UL, the load per connection of R99 is calculated by the following formula:

l For DL, the load per connection of R99 is calculated by the following formula:

l Typical Value: ( for AMR 12.2k is 0.67, is 0.65, is 50%, is 75%, load of CCHis 20%, Channel model is TU3, DL CL is 135dB, is 0.5, NodeBmax transmission poweris 43dBm)

( ) ( )( )

j j EbvsNo

j j

RW f L f

j Avg

1

10

11

111

10 _

++=+=

j

TX

P CLTX

j

No Eb

ii RW

P f

P P

P P

N j

/

)10

(1010/)(

max

10

)/(

max

+

++==

19.59%21.35%PS384k

8.03%8.69%PS128k

4.11%4.77%PS64k

5.81%4.99%CS64k

1.05%1.19%AMR12.2k

DownlinkUplinkLoad per User

j f UL DL



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Capacity Dimensioning Differences

GSM

l Hard blocking

l Capacity --- hardware dependent

l Single service

l Single GoS requirement

l Capacity dimensioning ---ErlangB

WCDMA

l Soft blocking

l Capacity --- interference dependent

l Multi services (CS&PS)

l Respective quality requirements of

each service

l Capacity dimensioning ---

Multidimensional ErlangB

l The GSM capacity is decided by the number of carriers, it is hard capacity. But WCDMAcapacity is related to interference, coverage, channel condition, it is soft capacity.

l The Erlang-B formula is only used for

p Circuit switched services

p Single service

l Multidimensional ErlangB(MDE) is suitable for:

p Multi service with different GoS

p Different service will share the same resource.



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Multidimensional ElangB Principle (1)

l Multidimensional ErlangBmodel is a Sto chastic Knapsack Pro blem .

l Knapsack ! means a system with fixed capacity, various objects arrive at the

knapsack randomly and the states of multi-objects in the knapsack are

stochastic process.

l Then when various objects attempt to access in this system, how much is the

blocking probability of every object?

K classes ofservices

Blockedcalls

Callsarrival

Callscompletion

Fixed capaciy

l Multidimensional ErlangBis a public algorithm. Now Huawei selects it. Operators can usedifferent algorithmto calculate the load.



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Multidimensional ElangB Principle (2)

l Case Study: Two dimensional ErlangB Model

p The size of service 2 is twice as that of service 1

p C is the fixed capacity

n 2Blocking States of Class 1

C

C-b 1

n 1

n 2Blocking States of Class 2

C

C-b 2

n 11 2 3 4 5 6

1

2

3

1 2 3 4 5 6

1

2

3

n 2States Space

C

n11 2 3 4 5 6

1

2

3

l b1:size of service 1, which means the resource required by service 1 .

l b2:size of service 2, which means the resource required by service 2 .

l b2=2*b1

l n1: number of service 1 connection

l n2: number of service 2 connection

l The left graph describes all the states (blue dots) that satisfies: n1*b1+n2*b2


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CS Capacity Dimensioning (1)l CS services

p Real time

p GoS requirements

l Multidimensional ErlangB

p Resource sharing

p Meeting GoS requirements

Capacity

Blocking probability Cell Loading

?MDE

Channels . . . . . .

A M R 1 2 . 2 k

C S 6 4

k

Multidimensional ErlangB Model

l MDE is used to calculate the peak load.



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CS Capacity Dimensioning (2)

l Comparison between ErlangBand Multidimensional ErlangB

Multidimensional ErlangB - Resources shared

High Utilization of resources

ErlangB - Partitioning Resources

Low Utilization of resources

l ErlangBallocate the resource according to the peak load of each service. Different serviceare separate, they cannot share the resource.

l MDE considers the probability that different service reach the peak load at the same timeis very low, then the services can share the same resource, and decrease the resourcerequirement.

l If there is only one service, MDE is the same with ErlangB.



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Best Effort for Packet Services

l PS Services:

p Best Effort

p Retransmission

p Burst Traffic

l PS will use the spare load apart from that used by CS

Total Load

CS Peak Load

CS Average Load

Load occupied by CS

Load occupied by PS

L o a

d

Time

l Best effort means that the packet service can utilize the resource that is available. PSservice can be considered as BE service.

l Retransmission of PS =BLER/(1-BLER)

l PS traffic burst is a method to ensure the QoS, it is obtained from simulation based ontime delay requirement.



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Capacity Dimensioning

l Average load:

l Peak load:

p Query the peak connection through ErlangBtable

j j j LoadFactor Trafficd AverageLoa =

= N

jTotal d AverageLoad AverageLoa1

j j j LoadFactor PeakConn PeakLoad =

)( jTotal PeakLoad MDE PeakLoad =

l Where:

p AverageLoad j is the average load for service j

p For the total average load, the result is the sum of AverageLoad for differentservice

p PeakLoadj is the peak load for service j

p For the total peak load, we should calculate it by MDE. The result is lower than thesum of peak load for different service.



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Case Study (1)l Common parameters:

p Maximum NodeB transmission power: 20W

p Subscriber number per Cell: 800

p Overhead of SHO (including softer handover): 40%

p Retransmission of PS is 5%

p R99 PS traffic burst: 20%

p Activity factor of PS is 0.9

p Power allocation for CCH is 20% in downlink



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Case Study (2)l Traffic Model, GoS and load factors:

4.21%

4.99%

1.18%

Load Factors (UL)

0

0

50

0.001

0.02

UL

N/A0PS384 (Kbit)

5.94%N/A100PS128k (Kbit)

2.96%N/A100PS64k (Kbit)

4.65%2%0.001CS64k (Erl)

0.83%2%0.02AMR12.2k (Erl)

Load Factors (DL)GoSDL



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Case Study (2)l Uplink Average Load l Downlink Average Load

AMR12.2k :

0.02*800*1.18%=18.88%

CS64k :

0.001*800*4.99%=3.99%

PS64k :

50*800*(1+5%)*(1+20%)/0.9/64/3600

*4.21%=1.02%

CS&PS uplink average load :

18.88%+3.99%+1.02%= 23.89%

AMR12.2k :

0.02*800*(1+40%)*0.83%=18.59%

CS64k :

0.001*800 *(1+40%)* 4.65%=5.2%

PS64k :

100*800*(1+5%)*(1+40%)*(1+20%)/0.9/64/3600*2.96%=2.01%

PS128k : 2.02%

CS&PS downlink average load :

18.59%+5.2%+2.01%+2.02%= 27.82%

l The difference between UL and DL is: DL should consider the soft handover, but ULdoesn "t need.



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Case Study (3)l Uplink Peak Load l Downlink Peak Load

AMR12.2k :

Traffic=0.02*800=16Erl

Peak Conn=ErlangB(16, 2%)=24

Peak Load=24*1.18%=28.32%

CS64k :

Traffic=0.001*800=0.8Erl

Peak Conn=ErlangB(0.8, 2%)=4Peak Load=4*4.99%=19.96%

CS Peak Load : 42.53%

AMR12.2k :

Traffic=0.02*800*(1+40%)=22.4Erl

Peak Conn=ErlangB(22.4, 2%)=31

Peak Load=31*0.83%=25.73%

CS64k :

Traffic=0.001*800 *(1+40%)=1.12Erl

Peak Conn=ErlangB(1.12, 2%)=5Peak Load=5*4.65%=23.25%

CS Peak Load : 42.33%



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N-55


HSDPA Capacity Dimensioning (1)

l HSDPA Capacity Dimensioning

p The purpose is to obtain the required HSDPA power to satisfy the

cell average throughput.

p HS-DSCH will use the spare power apart from that of R99

Dedicated channels (power controlled)

Common channels

Power usage with dedicatedchannels channels

t

Unused power

Power

HS-DSCH with dynamic power allocation t

Dedicated channels (power controlled)

Common channels

HS-DSCH

Power3GPP Release 99 3GPP Release 5

Pmax-R99

l HSDPA Capacity Dimensioning

p to obtain the average cell throughput

p based on HSDPA simulation result

p considering the gain of HSDPA scheduling

p the maximum data rate is limited by the available power, available codes resourceand UE capacity

p higher cell target load can be available for HSDPA



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HSDPA Capacity Dimensioning (2)l Capacity Based on Simulation

p to simulate Ior/Ioc distribution in the

network with certain cell range

p to simulate cell throughput distribution

based on Ec/Io distribution in the cell

l Dimensioning Procedure

0.00%0.50%

1.00%1.50%2.00%

2.50%

3.00%

3.50%4.00%

4 . 2 2

1 5 9 6

1 7

2 . 7 1

5 4 9 3

6 8

1 . 6 8

2 1 6 5

4 4

1 . 0 5

3 5 7 8

4 1

0 . 6 5

8 8 3 3

3

0 . 4 0

9 7 7 5

1 5

0 . 2 5

7 3 9 9

7 8

0 . 1 5

9 3 7 0

1

0 . 1 0

0 5 4 1

7 6

0 . 0 6

2 3 0 9

6 7

0 . 0 3

8 7 6 5

2 7

0 . 0 2

3 9 9 5

4 6

0 . 0 1

4 8 8 4

8 2

0 . 0 0

9 4 4 9

2 2

0 . 0 0

5 3 6 0

9 7

0 . 0 0

3 4 7 5

3 6

0 . 0 0

1 3 1 5

2 2

Ioc/Ior

D i

s t

r i b

u t i

o n

p r o

b a

b i l i t

yDU Cell coverage Radius=300m

Conditions of Simulation Channel model-TU3 5 codes

Simulation

Ec/Io distribution

Ior/Ioc distribution

Cell coverageradius

Cell averagethroughput

Ec/Io =>throughput

HSDPA PowerAllocation

l During the HSDPA capacity dimensioning procedure, we know the Cell Coverage Rad ius (obtained from the coverage planning) and Cell Average Throughput (obtained from the

traffic model), and we want to get the HSDPA Pow er Allo cat ion based on simulation.

l Ior means the power received by UE from the serving cell.

l Ioc means the power received by UE from other cells.



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N-57


Case Studyl Input parameters

p Subscriber number per cell: 800

p HSDPA Traffic model: 1200kbit per subs

p HSDPA Retransmission rate: 10%

p The power for HS-SCCH: 5%

p Cell radius: 1km

l HSDPA cell average throughput:

l The needed power for HS-DSCH including that for HS-SCCH is 18.38%

kbps293%)01(1*

3600

1200*800 =+



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Case Studyl Uplink Total Load of the Cell :

p CS Peak Load: 42.53%

p CS&PS average load: 23.89%

l Downlink Total Load of the Cell :

p CS Peak Load: 42.33%

p CS&PS average load: 27.82%

p

HSDPA load is 18.38%p CCH load: 20%

66.20%%. MAX

Load Load Load Load Load Load CCH HSDPAavg PS avg CS peak CS DLtotal cell =++=

+++=

%20%)38.188227%,33.42(

},max{ _

%4%. MAX

Load Load Load Load avg PS avg CS peak CS ULtotal cell 53.2)8923%,53.42(

},max{ _ ==

+=

l Base on this capacity dimensioning result, we can check whether the cell load of thenetwork is beyond the network target. If it is, we should adjust the cell radius.



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N-60


Overviewl Definition of a CE:

p A Channel Element is the base band resource required in the Node-B to

provide capacity for one voice channel, including control plane signaling,

compressed mode, transmit diversity and softer handover.

l NodeB Channel Element Capacity

p One BBU3900

n UL 1,536 CEs with full configuration

n DL 1,536 CEs with full configuration

l 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 thatsupported by a TRX of GSM. One uplink processing unit of our NODEB has the processingcapacity of 128 12.2kbps voice channels. One 3*1 WCDMA BTS is equivalent to the GSMsites of one S10/10/10. At the beginning of the WCDMA network construction, so high acapacity is not a necessity, and only a portion of it is required (e.g., 10%). If we offer thequotation based on the maximum hardware channel capacity of TRX like the GSM, it willmake the operators incur enormous cost and mismatch the user quantity. To reduce theinitial investment, the operator is bound to pay the equipment price to the supplieraccording to the actual use capacity, and, subsequently, pay more equipment prices with

the increase of the user quantity. This way, the operator will reduce the initial investmentand mitigate the risks.

l WBBP Board : the WCDMA Baseband Process Unit, which processes basebandsignals.

2562566WBBPb33843846WBBPb4

1281283WBBPb2

64643WBBPb1

2561283WBBPa

DL CE Number UL CE Number Number of CellsBoard



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N-61


Huawei Channel Elements Featuresl Channel Elements pooled in one NodeBl No need extra R99 CE resource for CCH

p reserved CE resource for CCH

l No need extra CE resource for TX diversity

l No need extra CE resource for Compressed Mode

p reserved resources for Compressed Mode

l No need extra CE resource for Softer HO

l HSDPA does not occupy R99 CE resource

p separate module for HSDPA

l HSUPA shares CE resource with R99 servicesl No additional CE resource for AGCH RGCH and HICH

l Softer HO CE: 3900 series NodeBdoesn "t need extra CE resource, but 3800 series NodeBneeds extra CE resource

l HSUPA shares CE resource with R99 services: that means the HSUPA E-DCH shares CE resource withR99 services



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N-62


CE Dimensioning Flow

),( _ _ _ _ _ _ _ HSUPAUL AUL PS UL AverageCS UL Peak CS Total UL CE CE CE CE CE MaxCE +++=

),( _ _ _ _ _ _ _ DL A DL PS DL AverageCS DL Peak CS Total DL CE CE CE CE MaxCE ++=

Dimensioning Start

CS Average CE

Channel Elements per NodeB

Dimensioning End

--Subscribers per NodeB--Traffic model

PS Average CECS Peak CE (MDE) HSPA CE



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N-63


CE Mappings for R99 Bearers

810PS384k

45PS144k

45PS128k

23PS64k

23CS64k

11AMR12.2k

Downlink Uplink Bearer

Channel Elements Mapping for R99 Bearers

l The mapping relationship of Channel Elements consumption for each bearer is based onUplink 2-way diversity

l In the case of uplink 4-way diversity, the CE consumption is shown below:

p Bearers CE (4-way diversity)

p AMR12.2k 2

p CS64k 4

p PS64k 4

p PS128k 8

p

PS384k 16l Detailed and recently updated data should be referred to the newest issued notice of

"UMTS RAN Product Specificaiton".



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N-64


R99 CE Dimensioning Principlel Peak CE occupied by CS can be obtained through multidimensional ErlangB

algorithm

l Average CE needed by CS and PS depend on the traffic of each service, i.e.

l Average CE =Traffic * CE Factor

CEResources . . . . . .

A M R 1 2 . 2 k

C S 6 4

k

Multdimensional ErlangB Model

Total CE

CS Peak CE

CS Average CE

CE occupied by CS

CE occupied by PSand HSPA

C E

Time

CE resource sharedamong each service

l The CE dimensioning principle is similar with capacity dimensioning.



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N-65


HSDPA CE Dimensioningl In uplink, no CE consumption for HS-DPCCH if corresponding UL DCH

channel exists

l In uplink, CE consumed by one A-DCH depends on its bearing rate

l In downlink, A-DCH is treated as R99 DCH.

l No additional CE needed for HS-DSCH and HS-SCCH

One HSDPA link needone A-DCH in uplink and

downlink respectively

H S - D S C H H S - S C C H H S - D P C C H

Associated Dedicated Channels

Site 1 Site 2

l HSDPA channels doesn "t occupy R99 CE resource, but we should calculate the A-DCH CE.



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N-66


CE Mappings for HSDPA Bearers

1 CE---DL A-DCH (DPCCH)---3 CEUL A-DCH (DPCCH)---0 CEHS-DPCCH

0 CE---HSDPA Traffic

Downlink Uplink Traffic

HSDPA Channel Elements Consumption

l HSDPA Traffic:

p Separate dedicated module processing HSDPA Traffic so HSDPA traffic does notoccupy any R99 CE resource.

p HS-DSCH and HS-SCCH does not affect base band capacity for R99 services.

l HS-DPCCH

p HS-DPCCH does not consume any R99 Channel Element since its base bandresource is reserved in BBU module.

l UL A-DCH (DPCCH)

p PS64k is recommended to bear uplink user data, TCP acknowledgement andsignaling.

p One PS64k consumes 3 CE in uplink.

l DL A-DCH (DPCCH)

p A-DCH bears DL signaling control.

p Signaling can be carried byHSDPA since RAN10.0.



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N-67


Case Study (1)

l Input Parametersp Subscribers number per NodeB: 2000

p Overhead of SHO: 30%

p R99 PS traffic burst: 20%

p Retransmission rate of R99 PS: 5%

p PS Channel element utilization rate: 0.7

p Average throughput requirement per user of HSDPA: 400kbps

p HSDPA traffic burst is 25%

p Retransmission rate of HSDPA is 10%

0

0

50

0.001

0.02UL

N/A1200HSPA (kbit)

N/A80PS128k (kbit)

N/A100PS64k (kbit)

2%0.001CS64k (Erl)

2%0.02AMR12.2k (Erl)GoSDLTraffic Model

l In this case, the R99 traffic model includes the traffic of HSDPA UL A-DCH. That means50kbits for UL PS64k includes the R99 UL DCH and HSDPA UL A-DCH.



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Case Study (2)l Uplink CE Dimensioning l Downlink CE Dimensioning

AMR12.2:

Traffic =0.02*2000*(1+30%) =52ErlPeak CE =ErlangB(52,0.02)*1=63 CEAverage CE =52*1=52 CECS64:

Traffic =0.001*2000*(1+30%) =2.6ErlPeak CE =ErlangB(2.6,0.02)*3 =21 CEAverage CE =2.6*3=9 CETotal peak CE for CS: 80CE

Total average CE for CS: 52+9=61CE

AMR12.2:

Traffic =0.02*2000*(1+30%) =52ErlPeak CE =ErlangB(52,0.02)*1 =63CEAverage CE =52*1=52CETraffic of VP:

Traffic =0.001*2000*(1+30%) =2.6ErlPeak CE =ErlangB(2.6,0.02)*2 =14CEAverage CE =2.6*2=6CETotal peak CE for CS: 74CE

Total average CE for CS: 52+6=58CE

l Different with capacity dimensioning, the UL CE dimensioning should consider the softhandover.

l For the peak CE, we should use MDE to calculate.



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l Uplink CE Dimensioning l Downlink CE Dimensioning

CE for PS64k:

Total CE for R99 PS services:4CE

4CE 5%)(1*20%)(1*30%)(1*3*3600*0.7 *6450*2000 =+++

CE for PS64k:

CE for PS128k:

Total CE for R99 PS services:

4+4=8CE

CE for HSDPA A-DCH:3CE10%)(1*%)52(1*1*

3600*4001200*2000 =++

4CE5%)(1*20%)(1*30%)(1*2*3600*0.7*64

100*2000 =+++

4CE5%)(1*20%)(1*30%)(1*4*3600*0.7*12880*2000 =+++

Case Study (3)

l In this case, the R99 traffic model includes the traffic of HSDPA UL A-DCH, therefore it isno need to calculate the HSDPA UL CE

l For the HSDPA DL A-DCH CE, strictly speaking, it can perform soft handover. But usuallythe CE requirement is low, so in Huawei strategy, the soft handover is not considered.



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Case Study (4)l Uplink CE Dimensioning l Downlink CE Dimensioning

Total CE Total CE

CE MAX

CE CE

CE MaxCE

UL Average PS UL AverageCS

UL Peak CS Total UL

80)461,80(

)

,(

_ _ _ _

_ _ _

=+=

+

=

CE 743)858 Max(74,

)CE CE CE

,CE ( MaxCE

DL _ A DL _ PS DL _ Average _ CS

DL _ Peak _ CS Total _ DL

=++=

++

=



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Contents

1. Traffic Model



4. CE Dimensioning




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WCDMA Radio Network Capacity Planning N-73

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2 WCDMA Radio Network Capacity Planning

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