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80%. Efficiency %. 41. Capacity, Erlangs. Traffic by Hour. 100%. 1. 50. 90%. 80%. 70%. 60%. 50%. 40%. 30%. 20%. 10%. 0%. Hour. Traffic Engineering. Objectives. Identify the role and functions of traffic engineering in a wireless system

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slide1

80%

Efficiency %

41

Capacity,

Erlangs

Traffic by Hour

100%

1

50

90%

80%

70%

60%

50%

40%

30%

20%

10%

0%

Hour

Traffic Engineering

slide2

Objectives

  • Identify the role and functions of traffic engineering in a wireless system
  • Understand the basic units and concepts of traffic engineering
  • Understand basic principles of system dimensioning
  • Develop operational familiarity with traffic tables
  • Understand and apply the concept of trunking efficiency to wireless systems
  • Examine current methods of wireless traffic forecasting and analysis
slide3

Outline

  • Traffic Engineering and System Dimensioning Objectives
  • Basics of Traffic Engineering
    • trunk concept
    • units of traffic measurement
    • offered traffic and call duration
    • blocking probability and grade of service
    • capacity and utilization efficiency as a function of number of trunks
  • Traffic Tables and Formulas
  • Variation of Traffic with Time
    • Real-System Example and Busy-hour determination
    • Typical Traffic Profile of Cellular System
  • Traffic Estimation and Cell Trunk Dimensioning
    • Geographic Distribution of Traffic and its estimation
      • for new systems, for growth cells
  • Exercise
slide4

$

7

6

1

9

3

7

4

1

2

8

9

3

6

7

1

2

5

8

10

9

3

11

2

8

4

6

Traffic Engineering Objectives

Traffic engineering is the intelligent art of having adequate capacity, but not spending too much to get it

  • Traffic engineering is applied during every stage in the development and operation of a cellular system
  • In Initial Design:
    • How many cells are needed?
    • What about switching resources?
    • What is the optimal way to backhaul?
  • Ongoing during Operation:
    • What BTS resources, and when?
    • When are new BTSs needed?
    • Anticipate resource requirements to allow budgeting and installation
slide5

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

BTS

Walking a Fine Line

The traffic engineer must walk a fine line between two problems:

  • Overdimensioning
    • too much cost
    • insufficient resources to construct
    • traffic revenue is too low to support costs
  • Underdimensioning
    • blocking
    • poor technical performance (interference)
    • capacity for billable revenue is low
    • revenue is low due to poor quality
    • users unhappy, cancel service
slide6

Basics of Traffic EngineeringTerminology & Concept of Trunks

  • Traffic engineering in telephony is focused on the voice paths users occupy. They are called by various names:
    • trunks
    • circuits
    • voice paths
  • Some other common terms are:
    • trunk group
      • a trunk group is several trunks going to the same destination, combined and addressed in switch translations as a unit , for traffic routing purposes
    • member
      • one of the trunks in a trunk group
  • In a CDMA system, the air interface is soft- squeezed. But there are other hard resources to be dimensioned:
    • Vocoders in the BSC
    • Channel elements in the BTS
slide7

Units of Traffic Measurement

Traffic is expressed in units of Circuit Time

General understanding of telephone traffic engineering began around 1910. An engineer in the Danish telephone system, Anger K. Erlang, was one of the first to develop the concepts of trunk dimensioning and publish the information for the benefit of others. In his honor, the basic unit of traffic is named the Erlang.

  • An Erlang of traffic is one circuit continuously used during an observation period normally one hour long -- I.e., one hour of talk.

Other units have become popular among various users:

  • CCS (Hundred-Call-Seconds)
  • MOU (Minutes Of Use)
  • It is easy to convert between traffic units if the need arises:

1 Erlang = 60 MOU = 36 CCS

slide8

Typical CDMA System

Design Blocking Probabilities

PSTN Office

BTS

P.005

BTS

P.02

MTX

BSC

BTS

P.001

P.005

Principles of Traffic EngineeringBlocking Probability / Grade of Service

  • Blocking is inability to get a circuit when one is needed
  • Probability of Blocking is the likelihood that blocking will happen
  • In principle, blocking can occur anywhere in a cellular system:
    • not enough channel elements, the BTS is full
    • not enough vocoders in the BSC
    • not enough paths through the switching complex
    • not enough trunks from switch to PSTN
  • Blocking probability is usually expressed as a percentage : :
  • P.02 is 2% probability, etc.
    • Blocking probability sometimes is called grade Of Service
  • Most blocking in cellular systems
  • occurs at the BTS level.
  • P.02 is a common goal
slide9

PSTN or other

Wireless user

Carried

Traffic

MTX

BSC

Offered

Traffic

Blocked

Traffic

BTS

BTS

BTS

BTS

BTS

BTS

Offered and Carried Traffic

  • Offered Traffic is what users attempt to originate.
  • Carried Traffic is the traffic actually successfully handled by the system
  • Blocked traffic is the traffic that could not be handled
    • since blocked call attempts never materialize, blocked traffic can only be estimated based on number of blocked attempts and average duration of successful calls

TO = CA x CD

TO= offered traffic (any desired units)

CA = total call attempts

CD = average successful call duration

(TO and CD must be in same units)

slide10

Ticket Counter Analogy

Servers

Queue

User Population

Traffic Engineering and Queuing Theory

  • Traffic Engineering is an application of a science called queuing theory
  • Queuing theory relates user arrival statistics, number of servers, and various queue or waiting strategies, with the probability of a user receiving service meeting specified criteria
  • If waiting is not allowed, and a blocked call simply goes away, Erlang-B formula applies (popular in wireless)
  • If unlimited waiting is allowed before service, the Erlang-C formula applies
  • If a wait is allowed but is limited in time, blocked calls held, Binomial & Poisson formulae apply
  • Fast, short transactions with no wait allowed: Engset formula applies

Queues we face in Everyday Life

1) for telephone calls,

2) at the bank

3) at the gas station

4) at the airline counter

slide11

Number of Trunks vs. Utilization Efficiency

Erlang-B P.02 GOS

Trks

Erl

Eff%

1

0.02

2%

2

0.22

11%

80%

Efficiency %

41

Capacity,

Erlangs

1

50

  • Imagine a BTS with just one voice channel. It can carry an erlang. But at a P.02 Grade of Service, how much traffic could it carry?
    • The trunk can only be used 2% of the time, otherwise the blocking will
    • be worse than 2%.
    • 98% availability forces 98% idleness. It can only carry .02 Erlangs. Efficiency 2%!
  • Adding just one trunk relieves things greatly. Now we can use
  • trunk 1 heavily, with trunk 2 handling the overflow.
  • Efficiency rises to 11%

The Principle of Trunking Efficiency

  • For a given grade of service, trunk utilization efficiency increases as the number of trunks in the pool grows larger.
    • For trunk groups of several hundred, utilization approaches 100%.

# Trunks

slide12

Capacity and Trunk Utilization

Erlang-B for P.02 Grade of Service

45

90

40

80

35

70

30

60

25

50

20

40

15

30

10

20

5

10

0

0

0

10

20

30

40

50

Trunks

Number of Trunks,Capacity, and Utilization Efficiency

  • The graph at left shows the capacity in erlangs for a given number of trunks, as well as the utilization efficiency
  • For accurate work, tables of traffic data are available
    • Capacity, Erlangs
    • Blocking Probability (GOS)
    • Number of Trunks
  • Notice how capacity and utilization behave for the numbers of trunks in typical cell sites

Utilization

Efficiency

Percent

Capacity,

Erlangs

slide13

Probability of blocking

E

0.0001 0.002

0.02

n

0.2

1

2

2.935

7

Number of available circuits

Capacity in Erlangs

300

Traffic Engineering & System Dimensioning

Using Erlang-B Tables to determine Number of Circuits Required

A = f (E,n)

slide14

#Trunks

#Trunks

Erlangs

Erlangs

#Trunks

#Trunks

#Trunks

Erlangs

#Trunks

Erlangs

Erlangs

Erlangs

#Trunks

Erlangs

#Trunks

Erlangs

1

0.0204

26

18.4

51

41.2

76

64.9

100

88

150

136.8

200

186.2

250

235.8

2

0.223

27

19.3

52

42.1

77

65.8

102

89.9

152

138.8

202

188.1

300

285.7

3

0.602

28

20.2

53

43.1

78

66.8

104

91.9

154

140.7

204

190.1

350

335.7

4

1.09

29

21

54

44

79

67.7

106

93.8

156

142.7

206

192.1

400

385.9

5

1.66

30

21.9

55

44.9

80

68.7

108

95.7

158

144.7

208

194.1

450

436.1

6

2.28

31

22.8

56

45.9

81

69.6

110

97.7

160

146.6

210

196.1

500

486.4

7

2.94

32

23.7

57

46.8

82

70.6

112

99.6

162

148.6

212

198.1

600

587.2

8

3.63

33

24.6

58

47.8

83

71.6

114

101.6

164

150.6

214

200

700

688.2

9

4.34

34

25.5

59

48.7

84

72.5

116

103.5

166

152.6

216

202

800

789.3

10

5.08

35

26.4

60

49.6

85

73.5

118

105.5

168

154.5

218

204

900

890.6

11

5.84

36

27.3

61

50.6

86

74.5

120

107.4

170

156.5

220

206

1000

999.1

12

6.61

37

28.3

62

51.5

87

75.4

122

109.4

172

158.5

222

208

1100

1093

13

7.4

38

29.2

63

52.5

88

76.4

124

111.3

174

160.4

224

210

14

8.2

39

30.1

64

53.4

89

77.3

126

113.3

176

162.4

226

212

15

9.01

40

31

65

54.4

90

78.3

128

115.2

178

164.4

228

213.9

16

9.83

41

31.9

66

55.3

91

79.3

130

117.2

180

166.4

230

215.9

17

10.7

42

32.8

67

56.3

92

80.2

132

119.1

182

168.3

232

217.9

18

11.5

43

33.8

68

57.2

93

81.2

134

121.1

184

170.3

234

219.9

19

12.3

44

34.7

69

58.2

94

82.2

136

123.1

186

172.4

236

221.9

20

13.2

45

35.6

70

59.1

95

83.1

138

125

188

174.3

238

223.9

21

14

46

36.5

71

60.1

96

84.1

140

127

190

176.3

240

225.9

22

14.9

47

37.5

72

61

97

85.1

142

128.9

192

178.2

242

227.9

23

15.8

48

38.4

73

62

98

86

144

130.9

194

180.2

244

229.9

24

16.6

49

39.3

74

62.9

99

87

146

132.9

196

182.2

246

231.8

25

17.5

50

40.3

75

63.9

100

88

148

134.8

198

184.2

248

233.8

Erlang-B Traffic TablesAbbreviated - For P.02 Grade of Service Only

slide15

Offered Traffic lost due to blocking

max # of

trunks

An

n!

Pn(A) =

A

An

1 + + ... +

1!

n!

Number

of

Trunks

average

# of busy

channels

Pn(A) = Blocking Rate (%)

with n trunks

as function of traffic A

A = Traffic (Erlangs)

n = Number of Trunks

Offered

Traffic,

A

time

Equation behind the Erlang-B Table

The Erlang-B formula is fairly simple to implement on hand-held programmable calculators, in spreadsheets, or popular programming languages.(factorial)

slide16

Typical Traffic Distribution

on a Cellular System

100%

90%

SUN

80%

MON

70%

TUE

60%

50%

WED

40%

THU

30%

FRI

20%

SAT

10%

0%

Hour

Wireless Traffic Variation with Time

  • Peak traffic on earlier cellular systems was usually daytime business-related traffic
    • Evening taper is more gradual than morning rise
    • Friday is the busiest day, followed by other weekdays in backwards order, then Saturday, then Sunday
  • Wireless systems for PCS will have peaks of residential traffic during early evening hours, like wireline systems
  • There are seasonal and annual variations, as well as long term growth trends

Actual traffic measured on a system in the mid-south USA in summer 1992. This system had 45 cells and served an area of approximately 1,000,000 population.

slide17

The Busy Hour

  • In telephony, it is customary to collect and analyze traffic in hourly blocks, and to track trends over months, quarters, and years
    • When making decisions about number of trunks required, we plan the trunks needed to support the busiest hour of a normal day
    • Special events (disasters, one-of-a-kind traffic tie-ups, etc.) are not considered in the analysis
    • Which Hour should be used as the Busy-Hour?
    • Some planners choose one specific hour and use it every day
    • Some planners choose the busiest hour of each individual day (floating busy hour)
    • Most common preference is to use floating (or bouncing) busy hour determined individually for each cell and for the total system, but excluding one-of-a-kind events and disasters
    • In example chart just presented, 4 PM was the busy hour every day
slide18

High-Level Traffic Forecasting and Business Planning

Year

0/Start

1

2

3

4

5

Population

1,000,000

1,000,000

1,000,000

1,000,000

1,000,000

1,000,000

Penetration

0.1%

2.5%

5.0%

7.0%

9.0%

12%

# Subscribers

1,000

25,000

50,000

70,000

90,000

120,000

BH Erlangs/Sub

.100

.05

.04

.03

.028

.025

BH Total Erlangs

100

1,250

2,000

2,100

2,520

3,000

# of Cell Sites

10

25

35

40

45

50

Avg. Erl/Cell

10

50

57

52.5

56

60

Avg. Chan./Cell

17

61

68

64

67

71

Total Voice Chans.

170

1,525

2,380

2,560

3,015

3,550

  • Every system deserves a business plan based on marketing and traffic assumptions.
    • The plan is used for forecasting equipment and capital needs.
    • The number of cells is driven both by coverage needs and the requirement to carry anticipated traffic without blocking.
    • Total is based on anticipated per-subscriber average usage & number of subs
    • The distribution of voice channels among cells is determined later.
slide19

Existing System

Traffic In Erlangs

8

11

5

7

10

7

2

6

11

16

5

19

8

7

7

16

7

6

3

9

9

Where is the Traffic?

  • Wireline telephone systems have a big advantage in traffic planning.
    • They know the addresses where their customers generate the traffic!
  • Wireless systems have to guess where the customers will be next
    • on existing systems, use measured traffic data by sector and cell
      • analyze past trends
      • compare subscriber forecast
      • trend into future, find overloads
    • for new systems or new cell, we must use all available clues
slide20

Population Density

Vehicular Traffic

920

5110

Land Use

Databases

4215

22,100

1230

3620

6620

Traffic Clues

  • Subscriber Profiles:
    • Busy Hour Usage, Call Attempts, etc.
  • Market Penetration:
    • # Subscribers/Market Population
    • use Sales forecasts, usage forecasts
  • Population Density
    • Geographic Distribution
  • Construction Activity
  • Vehicular Traffic Data
    • Vehicle counts on roads
    • Calculations of density on major roadways from knowledge of vehicle movement, spacing, market penetration
  • Land Use Database: Area Profiles
  • Aerial Photographs: Count Vehicles!

27 mE/Sub in BH

103,550 Subscribers

1,239,171 Market Population

adding 4,350 subs/month

new

Shopping Center

slide21

Vehicles per Mile

Vehicle

Speed,

MPH

Vehicle

Spacing,

feet

Vehicles

per mile,

per lane

0

20

264

10

42

126

20

64

83

30

86

61

45

119

44

60

152

35

Vehicle spacing 20 ft. @stop

Running Headway 1.5 seconds

VEHICLE SPACING AT COMMON ROADWAY SPEEDS

0

100

200

300

400

500

600

700

800 feet

0 MPH

10 MPH

20 MPH

30 MPH

40 MPH

50 MPH

Traffic Density along roadways

  • Speed is the main variable determining number of vehicles on major highways
    • typical headway ~1.5 seconds
    • table and figure show capacity of 1 lane
  • When traffic stops, users generally increase calling activity
  • Multiply number of vehicles by percentage penetration of population to estimate number of subscriber vehicles
slide22

Traffic

Density

3.5%

27mE

Land Use

Cell Grid

Systematic Estimation of Required Trunks

Modern propagation prediction tools allow experimentation and estimation of traffic levels

  • Estimate total overall traffic from subscriber forecasts
  • Form traffic density outlines from market knowledge, forecasts
  • Overlay traffic density on land use data; weight by land use
  • Accumulate intercepted traffic into serving cells,
    • obtain erlangs per cell & sector
  • From tables, determine number of trunks required per cell/sector
  • Modern software tools automate major parts of this process
slide23

Offered Traffic, mE per subscriber in busy hour

25 mE

Number of call attempts per subscriber in busy hour

1.667

Average Call Duration

150 sec. (41.7 mE)

Mobile originated calls

87 %

70 %

15 %

15 %

proportion of total calls on system

successful calls

Calls not answered

calls to a busy line

Mobile terminated calls

proportion of total calls on system

successful calls

Calls not answered

paging requests not answered

13 %

15 %

10 %

75 %

Percentage of Time in Soft Handoff

35%

Registration attempts per subscriber during busy hour

2

Example Wireless Usage Profile

slide24

Determining Number of Trunksrequired for a new Growth Cell

When new growth cells are added, they absorb some of the traffic formerly carried by surrounding cells

  • Two approaches to estimate traffic on the new cell and on its older neighbors:
    • if blocking was not too severe, you can estimate redistributed traffic in the area based on the new division of coverage
    • if blocking was severe, (often the case), users may have quit trying to call in locations where they expected blocking
      • reapply basic traffic assumptions in the area, like engineering new system, for every nearby cell
      • watch out! overall traffic in the area may increase to fill the additional capacity and the new cell itself may block as soon as it goes in service
slide25

Dimensioning System Administrative Functions

System administrative functions also require traffic engineering input. While these functions are not necessarily performed by the RF engineer, they require RF awareness and understanding.

  • Paging
    • The paging channels have a definite total capacity which must not be exceeded. When occupancy approaches this limit, the system must be divided into smaller zones, and registration parameters adjusted
    • Autonomous registration involves numerous parameters and the registration attempts must be monitored and controlled to avoid overloading.
  • Access Attempts
    • Access attempts must be monitored and the number of enabled access channels set appropriately. On busy systems, probing sequence parameters should be closely observed and optimized
slide26

CONVENTIONAL SECTORIZATION

1/3

1

1/3

1/3

CDMA SECTORIZATION

1

1

1

1

Trunking EfficiencyAn Important CDMA Implication

  • AMPS/TDMA/GSM sectorization distributes available channels among sectors
    • this results in a net decrease in capacity, although it gives better flexibility for managing interference
    • Example: 45 ch. omni = 35.6 Erl 3=sector: 15 ch. = 9.01 Erl, sector cell total cap. = 27.01 Erl
  • In CDMA, each additional sector is an additional independent signal
    • Each additional sector has almost as much capacity as the original omni configuration!
    • Inter-sector boundary interference places a practical limit somewhat above 6 sectors
slide27

1

DS-0

30

30

DS-0s

30

DS-0s

DS-1

T-1

480

16

DS-1s

16

DS-1s

DS-3

Digital Transmission Hierarchy

The digital signal hierarchy is the foundation of the PSTN:

  • DS-0
    • a two-way 64 kilobit/second digital circuit that carries a single conversation
  • DS-1 (sometimes called a E1 circuit)
    • a 2.048 megabit/second combination of 30 DS-0s: it carries 30circuits
    • you can lease a E1 from a LEC or an IXC, or you can build microwave to haul DS-1s
  • DS-3
    • a 34 megabit/second combination of 16 DS-1s: 16X30= 480 circuits
    • you can lease a DS-3 from a LEC or an IXC or you can build microwave to haul DS-3s
  • Optical Formats: OC1, OC3, OC24, OC48
    • OC-1 =55 mb/s
slide28

Busy-Hour

Contribution

0.2 Erlangs

1.0 Erlangs

3.0 Erlangs

Traffic Engineering Exercise

slide29

Busy-Hour

Contribution

0.2 Erlangs

1.0 Erlangs

3.0 Erlangs

Traffic Engineering Exercise

  • Imagine you have been assigned to plan this new cellular system. You have already predicted traffic densities, and set up the cell grid to meet basic requirements and fit with adjoining systems.
  • The matrix of squares ( represents predicted busy hour offered traffic.
  • The hexagonal cell grid represents the coverage areas of planned cells
  • Q: For each cell, determine the traffic intercepted, and the number of channels needed to give a P.02 Grade of Service
  • Q: In 12 months, traffic is expected to increase 40%. Then, what will be the channel requirements for each cell?
  • Refer to the preceding page for a readable traffic density diagram. Following pages provide forms to help speed and organize your work.
slide30

0.2

1.0

3.0 Erlangs

Form 1 for Traffic Engineering Exercise

  • Suggested Procedure:
    • Refer to the enlarged traffic density diagram on an earlier page.
    • For each cell, tally its intercepted bins of each type.
    • Convert bin counts into Erlangs.
    • Determine channels required from the P.02 Erlang B table

Traffic Bin

Counts

Traffic,

Erlangs

Channels

Required

(see next page to continue for traffic growth part)

slide31

Form 2 for Traffic Engineering Exercise

  • At the end of 12 months, traffic will have increased 40%.
  • Suggested procedure:
    • Multiply your originally-determined Erlang figures by 1.4, then
    • Determine channels required from the P.02 Erlang B table

Original Erlangs

New Erlangs

Channels Required

slide32

11

2

-

11

2

-

4.2

4.2

9

9

15

7

-

17

9

-

8

7

1

10

12.4

11.6

17

20

19

13

12

2

12

9

5

-

3

6

20.6

26.4

29

35

19

3

-

-

5

3

13

3

-

21

29

-

4

5

6.8

14

5.6

13

21

11

19

27

6

16

6

14

13

1

35.2

18.8

45

27

17

5

-

13

3

-

12

11

3

8.4

22.4

5.6

15

31

11

2-

2

-

19

4

-

6

7.8

12

14

7

-

-

6

2

-

5

-

-

1.4

3.2

1.0

5

8

4

0.2

1.0

3.0 Erlangs

Traffic Engineering Solution, Part 1

  • One bin-counter answers are shown below.
  • Your bin count may differ slightly, depending on how you resolve close cases, but your channel answers should be approximately the same as shown.

Traffic Bin

Counts

Traffic,

Erlangs

Channels

Required

(see next page to continue for traffic growth part)

slide33

12

12

4.2

4.2

5.88

5.88

21

25

24

10

12.4

11.6

14

17.36

16.24

38

47

20.6

26.4

28.84

36.96

29.4

39

21

19.6

16

28

14

6.8

14

5.6

9.52

7.84

36

19

26.6

60

35

35.2

18.8

49.28

26.32

19

41

14

8.4

22.4

5.6

11.76

31.36

7.84

15

18

6

7.8

8.4

10.92

6

10

5

1.4

3.2

1.0

1.96

4.48

1.4

Traffic Engineering Solution, Part 2

  • An exercise like this increases appreciation of software tools!
  • Traffic increased 40%; the required channel increases ranged from 25% in the smallest cells to 34% in the biggest cells.
  • Food for thought:
    • How many CDMA carriers are needed for each sector?
    • Can you do a PN offset plan for this system?

Original Erlangs

New Erlangs

Channels Required