07_wcdma radio network capacity planning

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Confidential Information of Huawei. No Spreading Without Permission

N-0

www.huawei.com

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

WCDMA Radio

Network Capacity

Planning

http://www.huawei.com/




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

Foreword

l 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

network part 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



4. CE Dimensioning




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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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UMTS 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 relationship

between the information entities in the stream.

Small time delay tolerance, requiring data rate

symmetry

Background

download of

Email

Background

Web page

browse,

network game

Interactive

N onr e al - t

i m e c a t e g or y

Streaming

multimediaStreaming

Voice service,

videophoneConversation

al

R e al - t i m e c a t e g or y

l 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 servicesare 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.

l 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).

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 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 system decides startup and termination at any time, the above formulas#Erlang 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.



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Traffic Model

System Configuration

User Behaviour

Service Pattern

Traffic Model

Results

l 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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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 the QoS expected 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 strictly different from, the traffic

measurement model.

l 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



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Typical Service Features

Descriptionl 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, 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:

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 QoS requirements of the

service.



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Contents

1. Traffic Model






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CS Traffic Model

l Voice service is a typical CS services. Voice data arrival conforms

to the Poisson distribution. Its time interval conforms to the

exponent distribution

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 users registered in the network.

l Activity Factor: The weight of the time of service full-rate transmission among

the duration of 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 in ETSI 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

parameters commonly 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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l Typical Rate (kbps)

l BLER ( Block error ratio ):

p The retransmission caused by error blocks should be

considered

p Assume that PS service data volume is N, block error rate is

BLER, the total data volume to be transmitted is:

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

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

of the planning result.

l Block error rate (BLER) belongs to QoS. The service control mechanism will

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

l Actually, retransmission rate is equal to 1/(1-BLER)



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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. 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.



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PS User Behaviour Parameters

l Penetration Rate

p The percentage of the users that activate this service to all the

users registered in the network

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 users registered 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 elapse of time, the penetration rate will increase gradually.

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

between service types 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 different application situations will have different user distributions.



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l Session Traffic Volume ( byte ) : mean traffic volume of one

session in one PS service

l Data transmission time ( second ) : mean duration of data

transmission in one session at one PS service

l

Holding Time ( second ) : mean duration of one session inone PS service

l Based on the traffic model figure, it is easy to calculate the session traffic

volume. The transmission time should include the retransmitting times.



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l Active Factor : The weight of the time of service full-rate

transmission among the duration of a single session

l Throughput per user at busy hour :

l PS throughput equivalent Erlang Formula :

l Based on Busy hour throughput per user and the Active factor, we can calculate

the Erlang which similar with CS service.

l Erlang = Busy hour throughput per user /!typical rate * Active factor * 3600"

l Busy hour throughput per user, Active factor, Session traffic volume and Data

transmission time are based on PS traffic model basic parameters. In another

word, for one whole PS traffic model, the parameters should be determined are :

Penetration Rate, BHSA, typical rate, BLER, Packetcallnum/session,

Packetnum/Packetcall, Packet size and reading time/session.



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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 users are different by modulating the respective

signal to the code sequences that are mutually orthogonal. Therefore, the

receiving signal is the sum of all user signals and the channel noise.



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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 -23J/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 activity factor

p Under the ideal power control :

p Hence:

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

all the users arriving at the receiver:

own I

jtotal P I −

jρ

j P

( )

j j jTOT

j

No Eb

R

W

P I

P j Avg

ρ

110 10

/ _

⋅⋅−

=

( ) j j

No Eb

TOT j

R

W

I P

j Avg ρ

1

10

11

10

/ _ ⋅⋅+

=

∑= N

jown P I 1

l Activity Factor: The weight of the time of service full-rate transmission among

the duration of a single session. Which is defined by the following formula:

e HoldingTim

issionTime DataTransmor 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 factor is 0.65



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( )

( )

N

N

j j

No Eb

TOT N other ownTOT P

R

W

I f P I I I

j Avg

+

⋅⋅+

+=++= ∑1

10

/

1

10

11

1

_ ρ

( ) j j

No Eb

j

R

W L

j Avg ρ

1

10

11

1

10

/ _ ⋅⋅+

=

( ) N

N

jTOT TOT P L f I I +⋅+⋅=

∑11

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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l 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

jρ

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



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

UL

N

j N

TOT

L f P

I NoiseRise

η−=

+−

==

∑1

1

)1(1

1

1

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

l If uplink cell load is 50%, NoiseRise will 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

R

W f L f

j Avg

1

10

11

10

11

111

_ ρ

η

( ) ( )

( ) j j

EbvsNo

j j

R

W f L f

j Avg ρ

η1

10

11

111

10

_ ⋅⋅+

×+=×+=

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

is called threshold capacity!.

TOT I



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Uplink Interference Analysis Limitation

l The above mentioned theoretic analysis uses the following

simplifying explicitly or implicitly:

p No consideration of the influence of soft handover

p 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 cell

interference is constant

l Considering the above factors, the system simulation is a more

accurate method:

p Static simulation: Monte_Carlo method

p 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 less than 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 less interference, and make the system support more users.

(But call quality of such users will be deteriorated)

p 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.p Since the time-variable feature of the mobile transmission environment,

the demodulation 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 that the 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 Receiver noise floor: P N

p For commercial UE, the typical value is -101dBm/3.84MHZ

NF W T K P N +××= )log(10

l K : Boltzmann constant, 1.38 10 -23J/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 commercial UE, typical value is 7dB.



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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 ×=α)(

α

l Compared to the uplink load equation, the most important new parameter is ,

which represents the non-orthogonality factor in the downlink. WCDMA employs

orthogonal codes in the downlink to separate users, and without any multi-path

propagation the orthogonality remains when the base station signal is received

by the mobile. However, if there is sufficient delay spread in the radio channel,

the mobile will see part of the base station signal as multiple access

interference. The orthogonality of 1 corresponds to perfectly orthogonal users.

Typically, the non-orthogonality is between 0.1 and 0.6 in multi-path channels.

l Where:

p P TX is the actual transmission power of NodeB

α



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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 Ec/Io for User j is:

10/)(10/

10/

10/

10)(10

10

)(10)(

N N

P CL

TX

j

P

CL

TX

CL

j

j P f

P

P f

P

Io

Ec+

+×+=

+×+

=αα

l Where:

p P j

is the transmission power of NodeB for User j

p CL is Downlink Coupling Loss, is equals to:

n PL_DL: Downlink path loss

n Lf_BS: cable loss of NodeB

n Ga_antenna: Gain of UE antenna and NodeB antenna

n Lb: Body loss

n SFM NSHO

: Slow fading margin without soft handover

n Lp: Penetration loss

l Therefore:

p is the useful power received by user j

p is the interference from own cell and adjacent

cell, and it includes I own and I other

p is the noise floor of UE

LpSFM LbantennaGa BS Lf DL PLCL NSHO +++−+= _ _ _

10/10

CL

j P

10/

max _

10

)(CL

Total DL P f ××+ ηα

10/10 N P



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l Under the ideal power control:

l Then we can get:

j j

j

No Eb

R

W

Io

Ec j

ρ

1)(10 10

)/(

××=

j

TX

P CL

TX j

No Eb

j RW

P f P

P

N j

/

)10

(1010/)(

10

)/( +

++×××

=

αρ

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. jρ



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l Define the downlink load factor for user j:

l Define the downlink load factor for the cell:

max P

P TX DL =η

j

TX

P CL

TX j

No Eb

j

j RW

P f

P

P

P

P

N j

/

)10

(1010/)(

max

10

)/(

max

+

++×××

==

αρ

η

l The downlink load factor are defined in the transmitter side (NodeB).



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l 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

/ηα ××++=

++==

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 CCH is 20%, Channel model is TU3, DL CL is 135dB, is 0.5, NodeB

max transmission power is 43dBm)

( ) ( )( )

j j

EbvsNo

j j

R

W f L f

j Avg ρ

η 1

10

11

111

10

_

⋅⋅+×+=×+=

j

TX

P CL

TX j

No Eb

ii

RW

P f

P

P

P

P

N j

/

)10

(1010/)(

max

10

)/(

max

+

++×××

==

αρ

η

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

jρ f ULη ULη

α



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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

WCDMA capacity 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 ErlangB model is a Stochastic Knapsack Problem.

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 of

services

Blockedcalls

Callsarrival

Callscompletion

Fixed capaciy

l Multidimensional ErlangB is a public algorithm. Now Huawei selects it.

Operators can use different algorithm to 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

n2

Blocking States of Class 1

C

C-b1

n1

n2

Blocking States of Class 2

C

C-b2

n11 2 3 4 5 6

1

2

3

1 2 3 4 5 6

1

2

3

n2

States Space

C

n11 2 3 4 5 6

1

2

3

Ω

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<=C

l The red dots in the central graph describe the blocking states for service 1, that

means in these red states, service 1 cannot access the network.

l The red dots in the central graph describe the blocking states for service 1, that

means in these red states, service 1 cannot access the network.



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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 ErlangB and Multidimensional

ErlangB

Multidimensional ErlangB - Resources shared

High Utilization of resources

ErlangB - Partitioning Resources

Low Utilization of resources

l ErlangB allocate the resource according to the peak load of each service.

Different service are separate, they cannot share the resource.

l MDE considers the probability that different service reach the peak load at the

same time is very low, then the services can share the same resource, and

decrease the resource requirement.

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



Course Name


N-50


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

CSPeak 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. PS service 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 on time delay requirement.



Course Name


N-51


Capacity Dimensioning

l Average load:

l Peak load:

p Query the peak connection through ErlangB table

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

different service

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 the sum of PeakLoad for different service, Because it



Course Name


N-52


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



Course Name


N-53


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



Course Name


N-54


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%)/0.9/64/360

0*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 UL doesn"t need.



Course Name


N-55


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%)=4

Peak Load=4*4.99%=19.96%

CS Peak Load: 42.53%

AMR12.2k:

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


Peak Load=31*0.83%=25.73%

CS64k:

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


Peak Load=5*4.65%=23.25%

CS Peak Load: 42.33%



Course Name


N-56


Contents


3.1 R99 Capacity Dimensioning

3.2 HSDPA Dimensioning



Course Name


N-57


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 dedicated

channels channels

t

Unused power

Power

HS-DSCH with dynamic power allocationt

Dedicated channels (power controlled)

Common channels

HS-DSCH

Power 3GPP 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

resource and UE capacity

p higher cell target load can be available for HSDPA



Course Name


N-58


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

2 . 9 8

2 . 0 4

1 . 3 9

0 . 9 6

0 . 6 6

0 . 4 5

0 . 3 1

0 . 2 1

0 . 1 4

0 . 1

0 . 0 7

0 . 0 5

0 . 0 3

0 . 0 2

0 . 0 1

0 . 0 1

0 . 0 1 0 0 0 0

Ioc/Ior

D i s t r i b u t i o n p r o b a b i l i t y

DU Cell coverage Radius=300m

Conditions of Simulation

ü Channel model-TU3

ü 5 codes

Simulation

Ec/Io distribution

Ior/Ioc distribution

Cell coverageradius

Cell averagethroughput

Ec/Io =>throughput

HSDPA Power Allocation

l During the HSDPA capacity dimensioning procedure, we know the Cell

Coverage Radius (obtained from the coverage planning) and Cell Average

Throughput (obtained from the traffic model), and we want to get the HSDPA

Power Allocation based on simulation.



Course Name


N-59


Case Study

l 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=+



Course Name


N-60


Case Study

l 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 the network is beyond the network target. If it is, we should adjust the cell

radius.



Course Name


N-61


Contents

1. Traffic Model



4. CE Dimensioning




Course Name


N-62


Overview

l Definition of a CE:

p A Channel Element is the base band resource required in the NodeB

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 that supported by a TRX of GSM. One uplink processing

unit of our NODEB has 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 operator will reduce the initial investment and mitigate the risks.



Course Name


N-63


Huawei Channel Elements

Featuresl Channel Elements pooled in one NodeB

l 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 services

l No additional CE resource for AGCH RGCH and HICH

l Softer HO CE: 3900 series NodeB doesn"t need extra CE resource, but 3800

series NodeB needs extra CE resource

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

CE resource with R99 services



Course Name


N-64


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



Course Name


N-65


CE Mappings for R99 Bearers

810PS384k

45PS144k

45PS128k

23PS64k

23CS64k

11AMR12.2k

DownlinkUplinkBearer

Channel Elements Mapping for R99 Bearers

l The mapping relationship of Channel Elements consumption for each bearer is

based on Uplink 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 16

l Detailed and recently updated data should be referred to the newest issued

notice of "UMTS RAN Product Specification".



Course Name


N-66


R99 CE Dimensioning Principle

l 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

CE

Resources .

.

.

. . .

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 PS

and HSPA

C E

Time

CE resource shared

among each service

l The CE dimensioning principle is similar with capacity dimensioning.



Course Name


N-67


HSDPA CE Dimensioning

l 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 need

one 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.



Course Name


N-68


CE Mappings for HSDPA Bearers

1 CE---

DL A-DCH

(DPCCH)

---3 CEUL A-DCH

(DPCCH)

---0 CEHS-DPCCH

0 CE---HSDPA Traffic

DownlinkUplinkTraffic

HSDPA Channel Elements Consumption

l HSDPA Traffic:

p Separate dedicated module processing HSDPA Traffic so HSDPA traffic

does not occupy 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 doesn"t consume any R99 Channel Element since its base

band resource is reserved in BBU module.

l UL A-DCH (DPCCH)

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

and signaling.

p One PS64k consumes 3 CE in uplink.

l DL A-DCH (DPCCH)

p A-DCH bears DL signaling control.

p A-DCH can be beared on HSDPA since RAN10.0.



Course Name


N-69


Case Study (1)

l Input Parameters

p 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

0.02

UL

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 means 50kbits for UL PS64k includes the R99 UL DCH and HSDPA UL A-

DCH.



Course Name


N-70


Case Study (2)

l Uplink CE Dimensioning l Downlink CE

DimensioningAMR12.2:

Traffic =0.02*2000*(1+30%) = 52Erl

Peak CE =ErlangB(52,0.02)*1= 63 CE

Average CE =52*1=52 CE

CS64:

Traffic =0.001*2000*(1+30%) = 2.6Erl

Peak CE =ErlangB(2.6,0.02)*3 = 21 CE

Average CE =2.6*3=9 CE

Total peak CE for CS: 80CE

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

AMR12.2:

Traffic =0.02*2000*(1+30%) = 52Erl

Peak CE =ErlangB(52,0.02)*1 = 63CE

Average CE =52*1=52CE

Traffic of VP:

Traffic =0.001*2000*(1+30%) = 2.6Erl

Peak CE =ErlangB(2.6,0.02)*2 =14CE

Average CE =2.6*2=6CE

Total 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 soft handover.

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



Course Name


N-71


l Uplink CE Dimensioning l Downlink CE

DimensioningCE for PS64k:

Total CE for R99 PS services:

4CE

4CE 5%)(1*20%)(1*30%)(1*3*36000.7 64

50*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*400

1200*2000=++

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

100*2000=+++

4CE5%)(1*20%)(1*30%)(1*4*3600*0.7*128

80*2000=+++

Case Study (3)

l In this case, the R99 traffic model includes the traffic of HSDPA UL A-DCH,

therefore it is no need to calculate the HSDPA UL CE

l For the HSDPA DL A-DCH CE, strictly speaking, it can perform soft handover.

But usually the CE requirement is low, so in Huawei strategy, the soft handover

is not considered.



Course Name


N-72


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

=++=

++

=



Course Name


N-73


Contents

1. Traffic Model



4. CE Dimensioning




Course Name


N-74


Network Dimensioning Flow

UL/DL Link Budget

Cell Radius=Min (RUL, RDL)

UL/DL Capacity

Dimensioning

Satisfy Capacity Requirement?

Capacity Requirement

Adjust Carrier/NodeBNo

Yes

CE Dimensioning

Output NodeB Amount/

NodeB Configuration

Coverage Requirement

start

End



Course Name N-75

Thank youwww.huawei.com



07_wcdma radio network capacity planning

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