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www.huawei.com

WCDMA Radio

Network Capacity

Planning

(2)

Foreword



WCDMA is a self-interference system



WCDMA system capacity is closely related to coverage



WCDMA network capacity has the “soft capacity” feature



The WCDMA network capacity restriction factors in the radio network

part include the following:



Uplink interference



Downlink power



Downlink channel code resources (OVSF)



Channel element (CE)

(3)

Objectives



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



Grasp the parameters of 3G traffic model



Understand the factors that restrict the WCDMA network capacity



Understand the methods and procedures of estimating

multi-service capacity

(4)

Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

(5)

Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

(6)

Contents

1. Traffic Model

1.1 Overview of traffic model

1.2 CS traffic model

(7)

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

o

n

re

a

l-t

im

e

c

a

te

g

o

ry

Streaming

multimedia

Streaming

Voice service,

videophone

Conversational

R

e

a

l-t

im

e

c

a

te

g

o

ry

(8)

Traffic Model

System Configuration

User Behaviour

Service Pattern

Traffic Model

Results

(9)

The Contents of Traffic Model



Service pattern refers to the service features



User behaviour refers to the conduct of people in using the

(10)

Typical Service Features Description



Typical service features include the following feature

parameters:



User type (indoor ,outdoor, vehicle)



User’s average moving speed



Service Type



Uplink and downlink service rates



Spreading factor

(11)

Contents

1. Traffic Model

1.1 Overview of traffic model

1.2 CS traffic model

(12)

CS Traffic Model



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

the Poisson distribution. Its time interval conforms to the exponent

distribution



Key parameters of the model



Penetration rate



BHCA: busy-hour call attempts



Mean call duration (s)



Activity factor

(13)

CS Traffic Model Parameters



Mean busy-hour traffic (Erlang) per user = BHCA

×

mean call duration

/3600



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

×

mean call

duration

×

activity factor

×

mean rate



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

(14)

Contents

1. Traffic Model

1.1 Overview of traffic model

1.2 CS traffic model

(15)

PS Traffic Model

Data Burst Data Burst Data Burst

Packet Call

Session

Packet Call

Packet Call

Downloading

Downloading

(16)

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)

(17)

Parameter Determining



The basic parameters in the traffic model are determined in the

following ways:



Obtain numerous basic parameter sample data from the existing

network



Obtain the probability distribution of the parameters through

processing of the sample data



Take the distribution most proximate to the standard probability as

the corresponding parameter distribution through comparison

with the standard distribution function

(18)

PS User Behaviour Parameters

User Behaviour

User Distribution

(High, Medium, Low end)

BHSA

(19)

PS User Behaviour Parameters



Penetration Rate



BHSA



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



User Distribution (High, Medium, Low end)

(20)

PS Traffic Model Parameters



Session Traffic Volume (Byte): Average traffic of single session of the

service



Busy hour throughput per user (Kb):



PS throughput equivalent Erlang formula (Erlang)

)

Session

Num

PacketCall

(

)

PacketCall

PacketNum

(

)

PacketSize

(

fficVolume

SessionTra

=

×

×

1000

/

8

fficVolume

SessionTra

BHSA

user

/

roughput

BusyHourTh

=

×

×

)

3600

(

_

=

ctor

ActivityFa

redRate

TypicalBea

nEviroment

Applicatio

derTypical

roughputUn

BusyHourTh

gRate

Penetratin

User

OfDiffrent

Percentage

Erlang

Data

(21)

PS Traffic Model Parameters



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

purpose of transmitting data.



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



Activity

factor:

e

HoldingTim

issionTime

DataTransm

or

ActiveFact

=

e

TypicalRat

BLER

fficVolume

SessionTra

issionTime

DataTransm

1

1

1000

/

8

×

×

=

issionTime

DataTransm

adingTime

Re

)

1

Session

lNum

PackketCal

(

e

HoldingTim

=

×

+

(22)

Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

(23)

Basic Principles



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.



The radio system capacity is decided by uplink and downlink.

When planning the capacity, we must analyze from both uplink

and downlink perspectives.

(24)

Contents

2.

Interference Analysis

2.1 Uplink Interference Analysis

(25)

Uplink Interference Analysis



Uplink interference analysis is based on the following formula:

N

other

own

TOT

I

I

P

(26)

Uplink Interference Analysis



Receiver noise floor: P

N



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

NF

W

T

K

(27)

Uplink Interference Analysis



: Interference from users of this cell



Interference that every user must overcome is :



is the receiving power of the user j , is UL activity factor



Under the ideal power control :



Hence:



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

the users arriving at the receiver:

own

I

j total

P

I

j

ρ

j

P

(

)

j j j TOT j No Eb

R

W

P

I

P

j Avg

ρ

1

10

10 / _

=

(

)

j j No Eb TOT j

R

W

I

P

j Avg

ρ

1

10

1

1

10 / _

+

=

=

N

j

own

P

I

1

(28)

Uplink Interference Analysis



:Interference from users of adjacent cell



The interference from users of adjacent cell is difficult to analyze

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

and antenna direction diagram.



Adjacent cell interference factor

own

other

I

I

f

=

other

I

(29)

Uplink Interference Analysis

(

)

(

)

N N j j No Eb TOT N other own TOT

P

R

W

I

f

P

I

I

I

j Avg

+

+

+

=

+

+

=

1 10 /

1

10

1

1

1

_

ρ

(

)

j j No Eb j

R

W

L

j Avg

ρ

1

10

1

1

1

10 / _

+

=

(

)

N

N

j

TOT

TOT

I

f

L

P

I

=

+

+

1

1

Define:

Then:

(

+

)

=

N

j

N

TOT

L

f

P

I

1

1

1

Obtain:

(30)

Uplink Interference Analysis



Suppose that:



All the users are 12.2 kbps voice users, Eb/No

Avg

= 5dB



Voice activity factor = 0.67



Adjacent cell interference factor f=0.55

j

(31)

Uplink Interference Analysis



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

(32)

Uplink Interference Analysis



Define the uplink load factor for one user:



Define the uplink load factor for the cell:

(

)

(

)

(

)

+

×

+

=

×

+

=

N

EbvsNo

N

j

UL

R

W

f

L

f

j Avg

1

1

1

1

1

1

1

1

_

ρ

η

(

)

(

)

(

)

j

j

EbvsNo

j

j

R

W

f

L

f

j Avg

ρ

η

1

10

1

1

1

1

1

10

_

+

×

+

=

×

+

=

(33)

Uplink Interference Analysis Limitation



The above mentioned theoretic analysis uses the following simplifying

explicitly or implicitly:



No consideration of the influence of soft handover



No consideration of the influence of AMRC and hybrid service



Ideal power control assumption



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

interference is constant



Considering the above factors, the system simulation is a more

accurate method:



Static simulation: Monte_Carlo method



Dynamic simulation

(34)

Contents

2.

Interference Analysis

2.1 Uplink Interference Analysis

(35)

Downlink Interference Analysis



Downlink interference analysis is based on the following

formula:

N

other

own

TOT

I

I

P

I

=

+

+

(36)

Downlink Interference Analysis



Receiver noise floor: P

N



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

NF

W

T

K

(37)

Downlink Interference Analysis



:Interference from downlink signal of this cell



The downlink users are identified with the mutually orthogonal

OVSF codes. In the static propagation conditions without

multi-path, no mutual interference exists.



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

j

own

P

I

)

=

α

×

(

α

(38)

Downlink Interference Analysis



: Interference from the downlink signal of adjacent cell



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



Hence we obtain:

other

I

TX

j

other

f

P

I

)

=

×

(

(39)

Downlink Interference Analysis



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

+

+

×

+

=

+

×

+

=

α

α

(40)

Downlink Interference Analysis



Under the ideal power control:



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

R

W

P

f

P

P

N j

/

)

10

(

10

10

/

)

(

10

)

/

(

+

+

+

×

×

×

=

α

ρ

(41)

Downlink Interference Analysis



Define the downlink load factor for user j:



Define the downlink load factor for the cell:

max

P

P

TX

DL

=

η

j

TX

P

CL

TX

j

No

Eb

j

j

R

W

P

f

P

P

P

P

N j

/

)

10

(

10

10

/

)

(

max

10

)

/

(

max

+

+

+

×

×

×

=

=

α

ρ

η

(42)

Downlink Interference Analysis



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

=

=

+

+

=

+

α

+

×

×

η

/

(43)

Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

(44)

Capacity Dimensioning Flow

Dimensioning Start

Assumed Subscribers

CS Peak Cell Load

(MDE)

Yes

Yes

Yes

Yes

No

No

No

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

=

+

+

(45)

Contents

3.

Capacity Dimensioning

3.1 R99 Capacity Dimensioning

(46)

Capacity Dimensioning Differences

GSM



Hard blocking



Capacity --- hardware dependent



Single service



Single GoS requirement



Capacity dimensioning ---ErlangB

WCDMA



Soft blocking



Capacity --- interference dependent



Multi services (CS&PS)



Respective quality requirements of

each service



Capacity dimensioning

---Multidimensional ErlangB

(47)

Multidimensional ElangB Principle (1)



Multidimensional ErlangB model is a Stochastic Knapsack Problem.



“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.



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

blocking probability of every object?

K classes of

services

Blocked

calls

Calls

arrival

Calls

completion

Fixed capaciy

(48)

Multidimensional ElangB Principle (2)



Case Study: Two dimensional ErlangB Model



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



C is the fixed capacity

n

2

Blocking States of Class 1

C

C-b1

n

1

n

2

Blocking States of Class 2

C C-b2

n

1 1 2 3 4 5 6 1 2 3 1 2 3 4 5 6 1 2 3

n

2 States Space C

n

1 1 2 3 4 5 6 1 2 3

(49)

CS Capacity Dimensioning (1)



CS services



Real time



GoS requirements



Multidimensional ErlangB



Resource sharing



Meeting GoS requirements

Capacity

Blocking probability Cell Loading

?

MDE

Channels

..

..

..

AM

R12

.2k

CS

64

k

(50)

CS Capacity Dimensioning (2)



Comparison between ErlangB and Multidimensional ErlangB

Multidimensional ErlangB - Resources shared

High Utilization of resources

ErlangB - Partitioning Resources

(51)

Best Effort for Packet Services



PS Services:



Best Effort



Retransmission



Burst Traffic



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

(52)

Capacity Dimensioning



Average load:



Peak load:



Query the peak connection through ErlangB table

j j j

Traffic

LoadFactor

d

AverageLoa

=

×

=

N j Total

AverageLoa

d

d

AverageLoa

1 j j j

PeakConn

LoadFactor

PeakLoad

=

×

)

(

j

Total

MDE

PeakLoad

(53)

Case Study (1)



Common parameters:



Maximum NodeB transmission power: 20W



Subscriber number per Cell: 800



Overhead of SHO (including softer handover): 40%



Retransmission of PS is 5%



R99 PS traffic burst: 20%



Activity factor of PS is 0.9

(54)

Case Study (2)



Traffic Model, GoS and load factors:

4.21%

4.99%

1.18%

Load Factors (UL)

0

0

50

0.001

0.02

UL

N/A

0

PS384 (Kbit)

5.94%

N/A

100

PS128k (Kbit)

2.96%

N/A

100

PS64k (Kbit)

4.65%

2%

0.001

CS64k (Erl)

0.83%

2%

0.02

AMR12.2k (Erl)

Load Factors (DL)

GoS

DL

(55)

Case Study (2)



Uplink Average Load



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

:

(56)

Case Study (3)



Uplink Peak Load



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%

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%)=5

Peak Load=5*4.65%=23.25%

(57)

Contents

3.

Capacity Dimensioning

3.1 R99 Capacity Dimensioning

(58)

HSDPA Capacity Dimensioning (1)



HSDPA Capacity Dimensioning



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

cell average throughput.



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

Dedicated channels (power controlled) Common channels

Unused power

Power

Dedicated channels (power controlled) Common channels

HS-DSCH

Power

3GPP Release 99 3GPP Release 5

(59)

HSDPA Capacity Dimensioning (2)



Capacity Based on Simulation



to simulate Ior/Ioc distribution in the

network with certain cell range



to simulate cell throughput distribution

based on Ec/Io distribution in the cell



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 Channel model-TU3 5 codes Simulation Ec/Io distribution Ior/Ioc distribution Cell coverage radius Cell average throughput Ec/Io =>throughput HSDPA Power Allocation

(60)

Case Study



Input parameters



Subscriber number per cell: 800



HSDPA Traffic model: 1200kbit per subs



HSDPA Retransmission rate: 10%



The power for HS-SCCH: 5%



Cell radius: 1km



HSDPA cell average throughput:



The needed power for HS-DSCH including that for HS-SCCH is

18.38%

kbps

293

%)

0

1

(1

*

3600

1200

*

800

=

+

(61)

Case Study



Uplink Total Load of the Cell :



CS Peak Load: 42.53%



CS&PS average load: 23.89%



Downlink Total Load of the Cell :



CS Peak Load: 42.33%



CS&PS average load: 27.82%



HSDPA load is 18.38%



CCH load: 20%

66.20%

%

.

MAX

Load

Load

Load

Load

Load

Load

cell total DL CS peak CS avg PS avg HSDPA CCH

=

+

+

=

+

+

+

=

%

20

%)

38

.

18

82

27

%,

33

.

42

(

}

,

max{

_

%

4

%

.

MAX

Load

Load

Load

Load

cell total UL CS peak CS avg PS avg

53

.

2

)

89

23

%,

53

.

42

(

}

,

max{

_

=

=

+

=

(62)

Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

(63)

Overview



Definition of a CE:



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.



NodeB Channel Element Capacity



One BBU3900



UL 1,536 CEs with full configuration

(64)

Huawei Channel Elements Features



Channel Elements pooled in one NodeB



No need extra R99 CE resource for CCH



reserved CE resource for CCH



No need extra CE resource for TX diversity



No need extra CE resource for Compressed Mode



reserved resources for Compressed Mode



No need extra CE resource for Softer HO



HSDPA does not occupy R99 CE resource



separate module for HSDPA



HSUPA shares CE resource with R99 services

(65)

CE Dimensioning Flow

)

,

(

_ _ _ _ _ _

_Total CS Peak UL CS Average UL PS UL A UL HSUPA

UL

Max

CE

CE

CE

CE

CE

CE

=

+

+

+

)

,

(

_ _ _ _ _ _

_Total CS Peak DL CS Average DL PS DL A DL

DL

Max

CE

CE

CE

CE

CE

=

+

+

Dimensioning Start

CS Average CE

Channel Elements per NodeB

Dimensioning End

--Subscribers per NodeB

--Traffic model

PS Average CE

(66)

CE Mappings for R99 Bearers

8

10

PS384k

4

5

PS144k

4

5

PS128k

2

3

PS64k

2

3

CS64k

1

1

AMR12.2k

Downlink

Uplink

Bearer

(67)

R99 CE Dimensioning Principle



Peak CE occupied by CS can be obtained through multidimensional ErlangB

algorithm



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



Average CE = Traffic * CE Factor

CE

Resources

..

..

..

AM

R12

.2k

CS

64

k

Multdimensional ErlangB Model

Total CE CS Peak CE CS Average CE CE occupied by CS CE occupied by PS and HSPA C E

CE resource shared

among each service

(68)

HSDPA CE Dimensioning



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

channel exists



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



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



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

One HSDPA link need

one A-DCH in uplink and

HS-DSC H

HS-SCCH HS-D

(69)

CE Mappings for HSDPA Bearers

1 CE

---DL A-DCH (DPCCH)

---3 CE

UL A-DCH (DPCCH)

---0 CE

HS-DPCCH

0 CE

---HSDPA Traffic

Downlink

Uplink

Traffic

(70)

Case Study (1)



Input Parameters



Subscribers number per NodeB: 2000



Overhead of SHO: 30%



R99 PS traffic burst: 20%



Retransmission rate of R99 PS: 5%



PS Channel element utilization rate: 0.7



Average throughput requirement per user of HSDPA: 400kbps



HSDPA traffic burst is 25%



Retransmission rate of HSDPA is 10%

0

0

50

0.001

0.02

UL

N/A

1200

HSPA (kbit)

N/A

80

PS128k (kbit)

N/A

100

PS64k (kbit)

2%

0.001

CS64k (Erl)

2%

0.02

AMR12.2k (Erl)

GoS

DL

Traffic Model

(71)

Case Study (2)



Uplink CE Dimensioning



Downlink CE Dimensioning

AMR12.2:

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

(72)



Uplink CE Dimensioning



Downlink CE Dimensioning

CE for PS64k:

Total CE for R99 PS services:

4CE

4CE

5%)

(1

*

20%)

(1

*

30%)

(1

*

3

*

3600

*

0.7

*

64

50

*

2000

=

+

+

+

CE for PS64k:

CE for PS128k:

Total CE for R99 PS services:

4+4=8CE

CE for HSDPA A-DCH:

3CE

10%)

(1

*

%)

5

2

(1

*

1

*

3600

*

400

1200

*

2000

=

+

+

4CE

5%)

(1

*

20%)

(1

*

30%)

(1

*

2

*

3600

*

0.7

*

64

100

*

2000

+

+

+

=

4CE

5%)

(1

*

20%)

(1

*

30%)

(1

*

4

*

3600

*

0.7

*

128

80

*

2000

+

+

+

=

Case Study (3)

(73)

Case Study (4)



Uplink CE Dimensioning



Downlink CE Dimensioning

Total CE

Total CE

CE

MAX

CE

CE

CE

Max

CE

UL Average PS UL Average CS UL Peak CS Total UL

80

)

4

61

,

80

(

)

,

(

_ _ _ _ _ _ _

=

+

=

+

=

CE

74

3)

8

58

Max(74,

)

CE

CE

CE

,

CE

(

Max

CE

DL _ A DL _ PS DL _ Average _ CS DL _ Peak _ CS Total _ DL

=

+

+

=

+

+

=

(74)

Contents

1. Traffic Model

2. Interference Analysis

3. Capacity Dimensioning

4. CE Dimensioning

(75)

Network Dimensioning Flow

UL/DL Link Budget

Cell Radius=Min (R

UL, RDL)

UL/DL Capacity

Dimensioning

Satisfy Capacity Requirement?

Capacity Requirement

Adjust Carrier/NodeB

No

Yes

CE Dimensioning

Output NodeB Amount/

NodeB Configuration

Coverage Requirement

start

(76)

Thank you

www.huawei.com

References

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