15 CDMA Capacity Theory-43.ppt
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Transcript of 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