15 cdma capacity theory-43.ppt

Capacity Theory

ZTE University

CDMA-BSS Team

Main Content

Basic Elements and Calculation of Traffic Capacity

Recognized Busy Hour Methodologies

Determine Erl B Table and GOS

Determine the Call Mix and It’s Effects

Calculating Um Interface Capacity

What is “ capacity”?

Capacity more typically refers to the amount of activity that a

particular device or group of devices can facilitate support for

without experiencing a failure or fault.

In telephone switching system, demand for the server from the

source is called traffic, whereas it is called traffic load from the

perspective of the server. The definition is as follows: the traffic (or

traffic load) produced (or shouldered) by a source (or a server)

during the period T is the total of the lasted time for each of all

services during this period

Note: Grade of Service (GOS) is defined as the probability that a

random call will be delayed, or receive a busy signal, under a given

traffic load.

Components of a Typical Cellular System

Two major components that effect traffic:

Access components

Network components

MSC and BSC BTS

PSTN Antenna

E1

Network Access

“Capacity” can be seen everywhere”

Units for Capacity

Centi-call second (CCS)

The sum of the number of busy circuits, providing the busy t

runks were observed every 100 seconds (36 observations i

n 1 hour)

Erlangs

Most common measurement of traffic

One circuit continuously used for one hour

Observed once every 100 seconds

One Erlang equals 36 CCSs

Minutes of Use

1 Erlang = 60 MOU = 36 CCS

1 MOU = .16 Erlang = .6 CCS

1 CCS = .028 Erlang = 1.67 MOU

Conversion Triangle

CC

S/36

Erla

ngs

x 36

CCS/.6 min x .6

Erlangs x 60 min/60

Erlangs

CCS MOU

Capacity Flow Definition

Traffic flow through an office is defined as the product of the number of calls during a period of time and their average length, called the holding time.

A = ACHT x BHCA/3600 BHCA designates the number of calls originated during a period of

one hour ACHT is the average holding time, Typically, between 60 seconds

and 120 seconds. A is the traffic flow in Erl For example: 200 calls of an average duration of two minutes a

re generated during a period of one hour, then the traffic flow equals:

200(BHCA) x 120(ACHT)/3600 = 6.67Erl(traffic flow) Traffic flow expressed in hour-calls is referred to as traffic inten

sity. In the example, the traffic intensity equals: 6.67Erl

Capacity Intensity

Traffic intensity is the ratio of the time during which a facility is o

ccupied continuously to the time this facility is available.

A traffic intensity of one traffic unit (one Erlang) means continuo

us occupancy of a facility during the time period under consider

ation, regardless of whether or not information is transmitted.

In one day the capacity intensity is different in different hour.

So we usually use “busy hour” as capacity intensity in planning.

For example: in China the capacity intensity model for one us

er is 0.025Erl/sub

Main Content

Basic Elements and Calculation of Traffic Capacity

Recognized Busy Hour Methodologies

Determine Erl B Table and GOS

Determine the Call Mix and It’s Effects

Calculating Um Interface Capacity

Busy Hour Methodologies

Network elements should be engineered to provide an acceptable level of service during an average busy hour of the day, during the busiest seasons of the year.

Busy hour methodologies are based on measurement of call traffic intensity for discrete periods, carried on over an extended period of time.

These periods of measurement can vary based on hour of day, day of week, and season.

All above we should take care, that our planning should satisfy all the time requirement.

Daily Traffic VariationsT

raff

ic

07:0

0

08:0

0

09:0

0

10:0

0

11:0

0

12:0

0

13:0

0

14:0

0

15:0

0

16:0

0

17:0

0

18:0

0

19:0

0

Exploded view of measured hour

peak trafficmeasured traffic

(=average traffic)

Actual busiest 60-minute period

Busiest hour as measured

Time of Day

Key:

Tra

ffic

07:0

0

08:0

0

09:0

0

10:0

0

11:0

0

12:0

0

13:0

0

14:0

0

15:0

0

16:0

0

17:0

0

18:0

0

19:0

0

Exploded view of measured hour

peak trafficmeasured traffic

(=average traffic)

Actual busiest 60-minute period

Busiest hour as measured

Time of Day

Key:

Hourly Traffic Variation

0

500

1000

1500

2000

2500

Hourly traffic variation is usually selected for traffic characterization over a day because an hour is a convenient frame of reference.

Daily Traffic Variation

0

500

1000

1500

2000

2500

3000

3500

4000

Mon Tues Wed Thurs Fri Sat Sun

Oringinating Busy Hour Calls

Falling off traffic occurs during the course of the week. Higher average intensities occur on business days with lower activity during weekends and holidays.

Seasonal Traffic Variations

2700

2900

3100

3300

3500

3700

Ja

n. . . . . . . . . .

Au

g. . .

Oc

t. . . . .

Within a busy season, each system experiences weekly and daily traffic variations. Due to conditions peculiar to the area served by the system, some weeks have more traffic than others.

Main Content

Basic Elements and Calculation of Traffic Capacity

Recognized Busy Hour Methodologies

Determine Erl B Table and GOS

Determine the Call Mix and It’s Effects

Calculating Um Interface Capacity

Blocking probability and GOS

Blocking probability is the likelihood that a caller is unable

to get a circuit when one is requested

Blocking probability is usually expressed as a percentage,

using a type of shorthand notation:

P.02, implying 2% blocking probability

Blocking probability is often referred to as GOS, and P.02

is a common goal at the air interface.

Capacity Efficiency

The efficiency or capacity of how a facility handles traffic is ef

fected by the number of channels or trunks.

How do we relate traffic, grade of service (GoS), and Erlang t

ables to provide the proper number of channels /trunks to su

pport traffic?

Let’s begin by examining the Erlang Tables.

Erl _tabl e. exe

Grade of Service - GOS

Defined as service quality component of a system

Indicates the call blocking percentage by congestion

Design values in planning:

Trunks for land-based network: 1% GOS

Subscriber unit: 2-5% GOS

Distributed by the system

Main Content

Basic Elements and Calculation of Traffic Capacity

Recognized Busy Hour Methodologies

Determine Erl B Table and GOS

Determine the Call Mix and It’s Effects

Calculating Um Interface Capacity

Call Mix

Differences in mobility affects the capacity of the wireless

system. Calls can originate and terminate at a variety of

locations. This is known as call mix. It is important to know the

call mix of your system and develop call models.

Call transfers between cells generates considerable work in the

system.

Subscriber Features such as Short Message Service also affect

traffic and capacity.

Since call processing behavior changes constantly, it must be

measured again whenever definitive capacity analysis is done.

H-diagram – Termination of Calls

Mobile

Trunks

Land

Trunks

TANDEM(Call Delivery,Call Forward,

voice mail, etc)

INTRA(Mobile-to-Mobile)

Output( PSTN,

another CCC)

Input(PSTN,

GATEWAY, etc)

MobileOrigination

MobileTermination

MM

ReorderStimeoutDouborig

Invalid attempts(Tones + announcements)

Pagingtimeout

Inactive Mobile(Treatment)

Invalid attempts(Tones + announcements)

M - L

L - M

LL

Mobile

Trunks

Land

Trunks

TANDEM(Call Delivery,Call Forward,

voice mail, etc)

INTRA(Mobile-to-Mobile)

Output( PSTN,

another CCC)

Input(PSTN,

GATEWAY, etc)

MobileOrigination

MobileTermination

MMMM

ReorderStimeoutDouborig

Invalid attempts(Tones + announcements)

Pagingtimeout

Inactive Mobile(Treatment)

Invalid attempts(Tones + announcements)

M - L

L - M

LL

Main Content

Basic Elements and Calculation of Traffic Capacity

Recognized Busy Hour Methodologies

Determine Erl B Table and GOS

Determine the Call Mix and It’s Effects

Calculating Um Interface Capacity

Network Model In Reality

First,we shouldKnow one singleCell capacity?

For an Isolated Cell, Pole Point capacity is defined as:

Pole Point capacity = 1 + Processing Gain Eb/No

For an Isolated Cell, Pole Point capacity is defined as:

Pole Point capacity = 1 + Processing Gain Eb/No

Note: We know Eb/No as 7dB. Converting this to a numerical ratiowe get 5. Assumes : Perfect Power Control No Voice Activity Factor No Sectorization Gain

Student Exercise

Calculated the Pole Point for Rate Set 1 or 9,600 bps, with a spreadbandwidth of 1.2288 MHz.

CDMA Pole Capacity - Isolated Cell

BTS Receiver Noise RiseVoice Activity Factor (VAF)

VOICE VOICENO VOICE NO VOICE

FULL-RATEFRAMES

1/8th RATEFRAMES

Average TX Poweris lower by VAF

40% 60%

Capacity is increased by 1 = 2.5 times 0.40

CDMA Reverse Capacity

BTS Receiver Noise RiseIn-Cell vs Out-of-Cell Interference

A1-A7 In-Cell Interferers

B1,B2,C1,C2 Out-of-CellInterferers

CDMA Reverse Capacity

BTS Receiver Noise RiseIn-Cell vs Out-of-Cell Interference

60%6%

6%

6%

6%

6%

6%.2%

.2%

.2%

.2%

.2%.2%

.2%

.2%

.2%.2%

.2%.2%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%

.03%.03%

.03%

.03%

.03%

In-Cell Out-of-Cell

30% 2.4% 0.36%

Other

0.24%

33%60%

Ratio Out-of-Cell to In-Cell Interference = 33% = 0.55 60%

CDMA Reverse Capacity

What happens if we SECTORIZE the BTS?

We have excludedall these interferersfrom the Alpha sector

Interference in thisSector is much lower

CDMA Reverse Capacity

What happens if we SECTORIZE the BTS?

We have excludedall these interferersfrom the Alpha sector,assuming ‘perfect’sectorization!

We can now bringeach sector backto full Pole Capacity

CDMA Reverse Capacity

What happens if we SECTORIZE the BTS?

We can now bringeach sector backto full Pole CapacitySite (BTS) Pole

Capacity Increases3 times users

‘Not Quite!’

Why?

CDMA Reverse Capacity

These userscontributeInterferenceinto AdjacentSectors of theSite

What happens if we SECTORIZE the BTS?

OverlappingZone betweenSectors

For a 3-sector configuration, the sectorzation gain is about SF = 2.2 to 2.7.For a 6-sector configuration, the gain is about SF = 3.5 to 4.5.

REALITY!

CDMA Reverse Capacity

Theoretical equation of calculating reverse capacity

SfvIE

GMfb

cp

)1(/

10

Loading factor

Total Received Power-to-Noise Ratio vs. Cell loading

Theoretical equation of calculating reverse capacity

SfvIE

GMfb

cp

)1(/1

0

Gp is Processing Gain (numerical)

Eb/No is numerical 7dB in IS-95; 4.9dB in 1XRtt

f is ratio of out-of-cell to in-cell interference (estimated at 55% or 0.55)

SG is Sectorization Gain (eg: 2.55for a 3-sector, due to handoff boundaries)

Vf is the Voice Activity Factor eg: 45% or 0.45

Nc is non-accurate power control factor 0.8 in IS-95; 0.9 in 1XRtt

Student Exercise: Rate Set 1 8kb/s Data Rate 9,600 bps Spreading Rate 1.2288 Mcps

How

many ?

Processing Gain 128 Loading Factor 0.7

Eb/No 7dB Sectorzation Gain 2.55

Voice Activity Factor 0.4 Non-accurate power

Control

0.8

Interference Factor 0.55 Capacity

Processing Gain 128 Loading Factor 0.6

Eb/No 4.9dB Sectorzation Gain 2.55

Voice Activity Factor 0.4 Non-accurate power

Control

0.9

Interference Factor 0.55 CapacityHow many ?

IS-95

IXR

tt

CDMA Reverse Capacity

TRI-SECTOR

1BTS(S111)

35Users

35Users

35Users

ErlB Table (GOS:2%)

ErlB Table (GOS:2%)

ErlB Table (GOS:2%)

26.4Erl26.4Erl26.4Erl

26.4Erl*3

=79.2Erl

GOS:2%

Traffic Capacity in One BTS?

1X Capacity Planning Example1 The total subscribers (voice and data) 50000

2 The voice subscribers ratio 100%

3 The data subscribers ratio 25%

4 The busy hour traffic capacity of voice 0.02Erl/Sub

5 GOS 2%

6 The total traffic capacity requirement for voice (Erl) 1000Erl

7 ZXC10-BSS Single sector capacity (Erl) 26.4Erl

8 The sectors number to support voice 1000/26.4=38

9 The total data subscribers 5000*25%=12500

10 The average data throughput of subscriber in voice busy hour

(This parameter prediction decided by operator and manufacture together. )

50 bps

11 The uplink and downlink data ratio 1:4

12 The average downlink throughput of subscriber 40 bps

13 The average uplink throughput of subscriber 10 bps

14 The total downlink throughput of subscriber 40bps*12500=500Kbps

15 The total uplink throughput of subscriber 10bps*12500=125Kbps

16 ZXC10-BSS single sector downlink data throughput threshold 450Kbps

17 ZXC10-BSS single sector uplink data throughput threshold 400Kbps

18 The sectors number to support data 500Kbps/450Kbps=2

19 The total sectors 38+2=40

In reality, voice and data are used together , but in planning, we consider them

separately for convenience calculation.

Capacity Analysis and Network Optimization

Limited capacityLimited capacityIncreasing

dropped call rate

Increasing dropped call rate

Difficult accessDifficult access

Degressive voice quality

Degressive voice quality

F1

OMNI 1BTS

Network Expanding

F1

TRI-SECTOR

1BTS

OMNI

F1 F2+

1BTS

Network Expanding

F1 F2+

1BTS