05 wo np02 e1_1 umts capacity estimation-64

UMTS Capacity Estimation

ZTE University

Content

UMTS Service mode

Common Capacity Design Methods

Uplink Capacity Estimation

Downlink Capacity Estimation

Estimation Examples

CS Domain Service Model

Key parameter: call frequency, call duration,

blocking probability

Average Erlang ＝ call frequency ×duration /

3600

Call DurationCall Duration Call DurationCall Duration

Call SetupCall Setup Call ReleaseCall Release Call SetupCall Setup Call ReleaseCall Release

PS Domain Service Model

Session (WWW)Session (WWW) Session (WWW)Session (WWW)

CallCall CallCall Call (Web Page)Call (Web Page)

ClickClick ClickClick ClickClick

ActiveActive ActiveActive ActiveActive

DormantDormant DormantDormant

PacketPacket PacketPacket PacketPacket

ActiveActive


Dormant status and Active status conversion

Every session can contain several packet calls,

different data services and different user types

have different features

Resource occupied by packet call varies alone

with the burst transmission

PS Service Model - Example

service Bearer

rate(k

bps)

Mean

packet

size(byte)

Mean

packets

in a call

Mean

calls/s

ession

Reading

time

between

calls(second)

Email 64 480 32 2 5

www 144 480 25 5 5

Download 64 480 62 2 5

MMS 64 480 32 2 5

Streaming 384 480 267 1 0

Parameter Name Parameter definition Unit

DL Bit rate Downlink service bit rate kbps

DL Mean Packet Size Mean downlink packet

size

Byte

DL Mean ＃ Packets Mean downlink packet

quantityDL Mean Calls/session Mean calls of downlink

sessionDL Reading time between

callsTransmission duration

between downlink calls

second

DL Mean packets in a call Mean packets in one

downlink sessionDL BLER Downlink service quality

requirementDL PS Activity Factor Downlink activating factor


UL Bit rate Uplink service bit rate kbps

UL Mean Packet Size Mean uplink packet size Byte

UL Mean ＃ Packets Mean uplink packet

quantityUL Mean Calls/session Mean calls of uplink

sessionUL Reading time between

callsTransmission duration

between uplink calls

second

UL Mean packets in a call Mean packets in one

uplink sessionUL BLER Uplink service quality

requirementUL PS Activity Factor Uplink activating factor

BHSA Busy hour sessions

attempt


Service Category

Service type Basic characteristic Example

Conversation The time relationship

between information entities

in the stream must be kept,

session mode (small delay,

strict delay jitter requirement)

Voice, video phone

Streaming The time relationship

between information entities

in the stream must be kept

Multimedia data

stream

Interactive Request/response mode,

data integrity must be kept

Web browser,

internet game

Background Data integrity must be kept,

high delay tolerance

Email download in

background

User Group Classification

Classification principle

Based on user consumption capability and consumption behavior

Note: User groups are distinguished by service type, service rate, service quality and service intensity.

User type Group features

High－end High income group, enterprises and managers.

Providing high rate access service.

Medium－end General enterprises and some high income consumers.

Providing information inquiry, mobile entertainment and

mobile financial services.

Lower－end Middle income class and students. Providing data

services such as SMS and some mobile game services

Service Penetration

Percentage of user distribution in different application

environments are different

Percentage of high-end, middle-end and lower-end users

in different application environments are different

Service model statistic characteristic relates to

percentages mentioned above

A B C D

Total 10% 30% 30% 30%

High End 30% 10% 5% 0%

Medium End 40% 50% 40% 10%

Low End 30% 40% 55% 90%

Traffic Analysis for Single Subscriber

CS Domain

Mean busy hour Erl. Per user=mean busy hour

calls*mean call duration/3600

Service

type

Mean busy

hour calls

Mean

call

duration

Activate

factor

Mean

speed

(kbps)

Mean busy hour

erl per user

Tel. 1.25 72 0.5 12.2 0.025

Video

phone

0 (lower end)

0.05 (medium

end)

0.1 (high end)

54 1 64 0 (lower end)

0.00075 (middle

end)

0.0015 (high end)


PS Domain

Node: penetration rate means the percentage of UEs which support this service in total UEs.

Busy hour throughput per user = BHSA* mean calls in a session *mean packets in a call*mean packet size*8/1000

Equivalent Erl = Busy hour throughput per user / (Bearer rate *3600)

Service type Penetration

rate

BHSA Mean

packet

size

(byte)

Mean

packets

in a call

Mean

calls/s

ession

Busy hour

throughput

per user

（kbit）

Web

service

Low-end

user

50% 0.01 480 25 5 4.8

Medium

end user

75% 0.02 480 25 5 9.6

High-end

user

100% 0.03 480 25 5 14.4


The average traffic according to the Service Model

in each transmission environment is :

Average traffic for each subscriber = ∑ Ratio of

subscriber group* Service penetration * average

traffic of this group

Content

UMTS Service mode




Estimation Examples

Input:system load requirment and

coverage requirement

Uplink coverage

estimation

Quantity of BSs

satisfying uplink

coverage

Downlink coverage

estimation

Quantity of BSs

satisfying downlink

coverage

Compare the results

and evaluate the

larger one

Uplink capacity

estimation

Quantity of BSs

satisfying uplink

capacity

End

Based on traffic type Based on power

Quantity A of

channels to be

provided by every cell

on the downlink

Quantity B of

channels availably

provided by every

cell on the downlink

Add B

Ss

No

Yes

A<B

Dow

nlin

k ca

paci

ty

estim

atio

n

UMTS Network Dimensioning Procedure

Capacity Estimation Procedure

Hybrid service intensity analysis

The UMTS system provides multiple services and the hybrid

service intensity analysis makes the system capacity consumed by

various services equivalent to that consumed by a single service.

Uplink capacity estimation

Estimate the NodeB number that meets the service demand based

on the hybrid service intensity analysis.

Downlink capacity estimation

It is a verification process. The NodeB transmission power formula

is used to calculate the channel number that can be provided by

the current NodeB scale so as to verify whether this channel

number can meet the capacity requirement, and if it cannot,

stations need be added.


Equivalent Erlangs method

Post Erlang-B method

Campbell method

Equivalent Erlangs Method

Principle: Make a service equivalent to another service and

calculate the total Erl.

Example

Service A: 1 channel for each connection and the total is 12 erl.

Service B: 3 channels for each connection and the total is 6 erl.

If 1 erl service B = 3 erl service A, altogether 30 erl service A shall

be equivalent and 39 channels shall be required (under 2%

blocking rate).

If 3 erl service A = 1 erl service B, altogether 10 erl service B shall

be equivalent and 17 service B channels shall be required (equal

17*3=51 service A channels under 2% blocking rate).

+

Low speed

service

equivalent

High speed service

equivalent

2 Erl low

speed

service

1 Erl high

speed service

Capacities meeting the same GoS are different

The calculation result is related to the equivalent mode

Equivalent Erlangs Method

Post Erlang-B Method

Principle: Calculate the capacity required by each service respectively and add them.

Example Service A: 1 channel for each connection and the total

is 12 erl.

Service B: 3 channels for each connection and the total is 6 erl.

Service A requires 19 channels (under 2% blocking rate).

Service B requires 12 service B channels (equal 12*3=36 service A channels, under 2% blocking rate).

These two services require 19+36=55 channels


Suppose services A and B are the same kind, where, Service A: 1 channel for each connection and the total is 12 erl.

Service B: 1 channel for each connection and the total is 6 erl.

Based on the Post Erlang-B method Service A requires 19 channels (under 2% blocking rate).

Service B requires 12 channels (under 2% blocking rate).

Altogether 19+12=31 channels are required.

Based on traditional Erlang-B method

The total traffic of services A and B is 12+6=18 erl and altogether 26 channels are required under 2% blocking rate.

Required channel number estimated through the Post Erlang-B method is too large.

1 Erl service A

1 Erl service B

+

1 Erl service A and

1 Erl service B

Capacities meeting the

same GoS are different

The calculation

result is too

pessimistic


Campbell Method

Principle: Make multiple services equivalent to a virtual

service and calculate the capacity on the basis of the

virtual service.

c

aCCapacity ii

cfficOfferedTra

i

ii

i

ii

aerl

aerl

c

2

ic

iserviceofcapacityCiiserviceofamplitudea

niancevnmeana

factorcapacityc

i

......

*var*

.

3036112 ii aerl

6636112 222ii aerl

Campbell Method

Example

Service A: 1 channel for each connection and the total is 12 erl.

Service B: 3 channels for each connection and the total is 6 erl

Mean & variance

2.230

66

c

63.132.2

30 Traffic Offered c

α

Campbell Method

Capacity factor c

Virtual traffic

21 channels (virtual channels) are required to

meet the virtual traffic under 2% blocking rate.

471)2.221(1 C

493)2.221(2 C

Campbell Method

Under 2% blocking rate, channel number required by each

service is shown as follows:

Service A:

Service B:

Different channel numbers are required to meet the GOS

requirements of diversified services.

Compared with the former two methods, the calculation

result through the Campbell method is more reasonable.

Campbell Method

If the reference service is the voice service：

voicevoicevoice

serviceserviceservice

servicevNoEbR

vNoEbRAmplitude

*/*

*/*

Content

UMTS Service mode




Estimation Examples

jtotal

j

jjj

PI

P

Rv

WNoEb

)/(

W: indicates the chip rate.

vj: indicates user j’s activation factor.

Rj: indicates user j’s data rate.

Pj : indicates user j’s signal receive power

Itotal: indicates total broadband receive power with

the thermal noise power included in the NodeB.

Uplink Load Analysis

Eb/No the receive signal in the NodeB must reach

Eb/No required by the service demodulation.

totaljtotal

jjj

j ILI

vRNo

Eb

WP

)(1

1

jjj

total

jj

vRNo

Eb

WI

PL

)(1

1

N

j

totalj

N

j

j ILP11


The receive power at the NodeB receive end should meet the following formula so that the user signal can meet the demodulation requirement:

Define a connection load factor Lj:

The total receive power of all N users from one cell is:


The total receive power at the NodeB receive end

consists of three parts:

Neighbor cell’s interference factor I

i= Other cell interference /Local cell interference

Notherintatal PPPI

indicates the total interference power of in-cell users.

indicates the total interference power of out-cell users.

indicates the NodeB thermal noise power.

inP

otherP

NP

N

j

tataljotherin ILiPP

1

)1(

N

j

jotherintatal

tatal

N

total

LiPPI

I

P

INR

1

)1(1

1


The total user receive power of the NodeB:

Define the noise lifting as the ratio of total

broadband receive power to the noise power of

the NodeB:

N

j

jjj

N

j

jUL

vRNoEb

WiLi

11

)/(1

1)1()1(

UL

NR

1

1

)1(10)( 10 ULLOGdBNR


Define the uplink load factor to be:

The noise lifting can be represented to be:

25 30 35 40 45 50 55 60 65

2

3

4

5

6

7

8

9

10

11

user number

nois

e ris

e(dB

)

Shanghai dialectMinnan

dialect

mandarin

Cantonese


The uplink capacity is limited by interference

increase:


In the case of a single service, evaluate the channel

quantity provided by every cell according to the load

formula and further evaluate the total number of base

stations satisfying the uplink capacity requirement.

To budget composite traffic, based on the Campbell

algorithm, make different services consumption on the

system resource equivalent to the single service

consumption on the system resource, and then evaluate

the quantity of channels to be provided by every cell

according to load formula, and further evaluate the number

of base stations satisfying the composite traffic

requirement.

R99/HSUPA mixed calculation

During the uplink capacity calculation ,decide how

much uplink load will be designed in R99 and

HSUPA

By simulation, calculate how much PS throughput

can be carried by HSUPA

Calculate how much of the remaining PS service

to be carried by R99

Calculate equivalent

intensity of services

Calculate the variance, average value and

capacity factor of the composite service

System virtual traffic A

Calculate the quantity of

equivalent voice channels

in the cell

Quantity of virtual

channels in the cell

Virtual service capacity

B of the cell

Number of

cells

A/B

R99 Uplink Capacity Algorithm

Content

UMTS Service mode




Estimation Examples

Downlink Load Analysis

To correctly demodulate useful signals, the UE must

overcome interference from the following three aspects

Nothertatal PPPI )1(

P represents total power of signals from current cell

represents total interference power of signals

from the outside of the cell

represents thermal noise power from the UE

represents orthogonal factor of the downlink

otherP

NP


By referring to the derivation means of uplink load

factor, denote the downlink load factors as follows:

N

j j

j

jDL iRW

NoEbv

1

])1[(/

)/(

W represents chip rate at 3.84M chip/s

vj represents activation factor of the user j

jR represents bit rate of the user j

represents the average orthogonal factor in a cell

irepresents the average ratio of the NodeB power from

other cell to that from this cell


Total downlink power allocation

DL

N

jj

j

b

jMS

TXBS

RW

NE

LWN

P

1

1

0

_

Where, represents the noise power spectrum density

on the front of the receiver in the mobile station

represents the average path loss of the cellL

)(suppose KTNFNFKTNMS 290174 =+-+

MSN

46 48 50 52 54 56 58 60 62 64

32

34

36

38

40

42

44

46

user number

Tx P

ow

er

(dB

m)

Public channel

Two users

One user

Three users

.

.

.

Downlink

power


The downlink capacity is limited by transmission

power of the base station

Downlink Load and Scale Analysis

Estimate downlink capacity after analyzing the

channel quantity required by uplink capacity, and

observe whether the downlink can support the

mobile station to work in the designated coverage

area and its channel quantity reaches the channel

quantity generated by the uplink

Calculate the quantity of equivalent voice

channels to be provided by every cell

Calculate the quantity of equivalent voice

channels availably provided by every cell

Compare the above two results

Content

UMTS Service mode




Estimation Examples

Assumed Conditions

Channel environment: downtown area TU 3 km/h

System design load: 50%

Voice service blocking rate: 2%

Interference factor from the adjacent cell: 0.65

Area of the city zone: 40.8 square kilometers

Voice CS64 PS64/64 PS64/128 PS64/384

Data rate(k) 12.2 64 64 64 64

Activity factor 0.67 1 1 1 1

Eb/No 4.2 2.87 1.6 1.6 1.6

Forecast traffic 3000 400 100 5 2

Voice CS64 PS64/64 PS64/128 PS64/384

Data rate(k) 12.2 64 64 128 384

Activity factor 0.58 1 1 1 1

Eb/No 7.7 7.7 7.4 6.4 8

Forecast traffic 3000 400 100 35 20

Uplink:

Downlink:

Assumed Conditions

Input: system load requirement and coverage requirement

Uplink coverage

estimation

Downlink coverage

estimation

Uplink capacity

estimation

Quantity of base stations

satisfying uplink coverage


satisfying coverage

requirement


satisfying downlink coverage

Quantity B of channels

provided by the cell

Compare the results and evaluate the larger one

End

Quantity A of channels

required by the cell

A<BAdd base stations

Based on traffic

modelBased on power

Yes

No

Estimation Flow Chart

Emission

end

Maximal emission power

(dbm)

Antenna gain (dbi)

Human body loss (db)

Effective emission power

Receiving

end

Thermal noise power

spectrum density (dbm/HZ)

Thermal noise power (dbm)

Receiver noise

coefficient (db)

Receiver noise (dbm)

Interference margin (db)

Bit rate (kbit)

Processing gain (db)

Receiving Eb/No (db)

Receiver sensibility

Antenna gain (dbi)

Line loss

Other

Power control margin

Soft handoff gain

Shade fading margin

Penetration loss

Maximal path loss

Uplink Coverage Estimation

1. Uplink budget

2. Calculate the cell coverage radius based on a specific propagation model:

Path loss k1 k2log(d) k3Hms k4log(Hms) k5log(Heff) +

k6log(Heff)log(d) k7(diffraction loss) clutter loss

30Heff-6.55k6

-13.82k5

44.6k2

152.4k1

0.540.540.540.50.65Radius

（Km）

PS64/384PS64/128PS64CS64Voice

Uplink coverage is limited by the CS64 kps service


3. Calculate the quantity of base stations required by uplink

Coverage area of the three-sector base station

22 488.05.05.095.138

9KmRS

The quantity of base stations is 40.8/0.488=84


af amplitudefor 1 amplitudefor ratebit

servicefor servicefor ratebit

amplitude Relative

0

0

NE

NE

b

b

Voice: 1

CS64: 64 x 1 x 100.287/12.2 x 0.67 x = 5.76

PS64/64: 64 x 1 x 100.16/12.2 x 0.67 x = 4.3

PS64/128: 64 x 1 x 100.16/12.2 x 0.67 x = 4.3

PS64/384: 64 x 1 x 100.16/12.2 x 0.67 x = 4.3

Equivalent

intensity of

each service

Variance, mean and

capacity factor of the

composite service

Virtual

traffic A of

the system

Quantity of

equivalent

voice

channels in

the cell

Quantity of

virtual

channels in

the cell

Number of

cells

A/B Virtual

traffic A of

the cell

Equivalent intensity of each service


42.010

42.010

42.010

42.010

i

iiaerlmean 1.57663.423.453.410067.540013000

i

iiaerliance 7.182713.423.453.410067.540013000var 2222

Mean

Virtual traffic of the system mean/capacity factor 5766.1/3.17 1818.96(Erl)

Equivalent

intensity of

each service

Variance, mean and


composite service

Virtual

traffic A of

the system

Quantity of

equivalent

voice channels

in the cell

Quantity of

virtual channels in

the cell

Number of

cells

A/B

Virtual traffic

A of the cell

Capacity factor variance/mean 3.17

Variance


Quantity of equivalent voice channels availably


N

j

o

bj

N

EvR

Wf

1*

1*1

1*)1(

%50 65.0f

Get the quantity of equivalent voice channels N 54

Where, and

Equivalent

intensity of

each service

Variance, mean and


composite service

Virtual

traffic A of

the system

Quantity of

equivalent

voice channels

in the cell

Quantity of

virtual channels in

the cell

Number of

cells

A/B

Virtual

traffic A of

the cell


Equivalent

intensity of

each service

Variance, mean and


composite service

Virtual

traffic A of

the system

Quantity of

equivalent

voice channels

in the cell

Quantity of

virtual channels in

the cell

Number of

cells

A/B Virtual traffic

A of the cell

Quantity of virtual channels in every cell

c

aCCapacity ii )(

Quantity of virtual channels in the cell (54 1)/3.17 16

Virtual traffic of every cell

Look up the Erl B table, and provide 9.83Erl for 16 virtual

channels in the case of 2% of call loss ratio


Equivalent

intensity of

each service

Variance, mean and


composite service

Virtual

traffic A of

the system

Quantity of

equivalent

voice channels

in the cell

Quantity of

virtual channels in

the cell

Number of

cells

A/B Virtual traffic

A of the cell


Number of cells=Virtual traffic of the system/virtual

traffic of every =1818.96/9.83=186

Number of three-sector base stations=186/3=62


Integrate uplink and downlink coverage budget and uplink capacity

budget to determine that there are 84 base stations currently and

authenticate whether downlink power meets the requirement.

Quantity A of channels to be


Average traffic of every

cell


Quantity of virtual

channels in every cell

Determine the number of

stations

Qu

antity

B o

f chan

nels av

ailably

pro

vid

ed b

y th

e ce;;

End A<BYes NO

Ad

d b

ase station

s

Voice: 3000/84/3 11.9 Erl

CS64: 400/84/3 1.59 Erl

PS64/64: 100/84/3 0.4 Erl

PS64/128: 35/84/3 0.14 Erl

PS64/384: 20/84/3 0.079 Erl


Average traffic of various

services in every cell

Determine the number

of stations

Quantity A of

channels to be

provided by the

cell

Average

traffic of

every cell

Virtual traffic of

every cell

Quantity of

virtual channels

in every cell

Qu

antity

B o

f chan

nels av

ailably

pro

vid

ed b

y th

e cell

End

A<B

Yes


Equivalent service intensity of each service on

the downlink

Voice: 1, CS64: 7.8, PS64/64: 7.3

PS64/128: 13.1, PS64/384: 50

Mean of composite traffic

Variance of composite traffic

355.19=50 0.079+13.1 0.14+7.3 0.4+7.8 1.59＋ 11.9var 2222 iance

Traffic factor capacity factor variance/mean

355.19/33.04 10.75

Virtual service capacity of the cell mean/capacity factor

33.04/10.75 3.07 (Erl)

33.04=50 0.079+13.1 0.14+7.3 0.4+7.8 1.59＋ 11.9 mean


of stations

Quantity A of

channels to be

provided by the

cell

Average

traffic of

every cell

Virtual traffic

of every cell

Quantity of

virtual channels

in every cell

Qu

antity

B o

f chan

nels av

ailably

pro

vid

ed b

y th

e cell

End

A<B

Yes


c

aCCapacity ii )(

Quantity of equivalent voice channels:

7 10.75 1 76

Quantity of virtual channels in every cell

Look up the Erl B table and obtain that

the quantity of virtual channels required

by 3.07 Erl virtual traffic is 7

Quantity of equivalent voice channels to

be provided by every cellQuantity A of

channels to be


Average

traffic of

every cell

Virtual traffic

of every cell

Quantity of

virtual channels

in every cell


of stations

Qu

antity

B o

f chan

nels av

ailably

pro

vid

ed b

y th

e cell

End

A<B

Yes


Calculate the quantity of channels availably provided

by every cell based on power

])1[(/

)/(*1

/

)/(***

1

1

jj

N

j j

jj

N

j j

jjN

RW

NoEbv

RW

NoEbvLP

P

P represents the maximum service transmission power, which is 13 W

represents the noise power spectrum density on the front of the mobile

station receiver, and its value is -169 dBm

L represents the average path loss, which is evaluated by subtracting

6 dBm from the maximum path loss

j represents orthogoal factor, which is 0.6 for the multipath channel

represents interference factor from an adjacent cell. It is 0.65 for the three-

sector antenna macro cellj

Obtain that the quantity of equivalent voice channels actually provided by every cell is 71

NP

Quantity A of

channels to be

provided by the

cell

Average

traffic of

every cell

Virtual traffic

of every cell

Quantity of

virtual channels

in every cell


of stations

Quant

ity B

of

chann

els

availa

bly

provid

ed by

the

cell

End

A<B

Yes


Quantity A of

channels to be

provided by the

cell

Average

traffic of

every cell

Virtual traffic

of every cell

Quantity of

virtual channels

in every cell


of stations

Qu

antity

B o

f chan

nels av

ailably

pro

vid

ed b

y th

e cell

End

A<B

Yes


Comparison

The quantity of channels

to be provided by every

cell is 76

The quantity of channels

actually provided by every

cell is 71

There are 84 base stations

currently, and it cannot

satisfy downlink capacity

requirement, and some

stations should be added.

726588

717287

717286

717685

707684

697683

Number of

channels provided

Number of

channels required

Number of base

stations

488.095.1/88/8.40 Km


Iterative calculation

If there are 88 base stations, the uplink and downlink coverage

capacity requirement can be met

In the case, the base station coverage radius is

05 wo np02 e1_1 umts capacity estimation-64

Technology

service rate

ratedownlink service

rateuplink service

service intensity

mean callssession

ps domain service model

cs domain service model

uplink calls