efficiency %
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
Efficiency %
Capacity,Erlangs
1 50
80%
41
Traffic Engineering
Traffic by Hour
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Hour
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 wir
eless systems• Examine current methods of wireless traffic forecasting and an
alysis
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
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
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2
1
3
24
5
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7
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9
7
8
9
1
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2
6
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6
10
11
$
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 co
sts• Underdimensioning
– blocking– poor technical performance (interfere
nce)– capacity for billable revenue is low– revenue is low due to poor quality– users unhappy, cancel service
BTS BTS BTS BTS BTS BTS
BTS BTS BTS BTS BTS BTS
BTS BTS BTS
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
Units of Traffic Measurement
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
Traffic is expressed in units of Circuit Time
• 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
Principles of Traffic EngineeringBlocking Probability / Grade of Service
PSTN Office
P.001 P.005
P.02
P.005
Typical CDMA SystemDesign Blocking Probabilities
BTS
BTS
BTS
BSCMTX
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
CarriedTraffic
BTS BTS BTS BTS BTS BTS
OfferedTraffic
BSCMTX
BlockedTraffic
PSTN or otherWireless user
TO = CA x CDTO = offered traffic (any desired units)
CA = total call attemptsCD = average successful call duration(TO and CD must be in same units)
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
Ticket Counter Analogy
User Population
Queue
Servers
Queues we face in Everyday Life
1) for telephone calls,2) at the bank3) at the gas station4) at the airline counter
Number of Trunks vs. Utilization Efficiency
• 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. Efficien
cy 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 efficienc
y increases as the number of trunks in the pool grows larger.– For trunk groups of several hundred, utilization appro
aches 100%.
# Trunks
Efficiency %
Capacity,Erlangs
1 50
80%
41
Erl Eff%Trks
1
2
0.02
0.22
2%
11%
Erlang-B P.02 GOS
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
051015202530354045
Capacity and Trunk UtilizationErlang-B for P.02 Grade of Service
Trunks
0102030405060708090
50403020100UtilizationEfficiencyPercent
Capacity,Erlangs
Traffic Engineering & System Dimensioning
Using Erlang-B Tables to determine Number of Circuits Required
A = f (E,n)
Probability of blocking
0.0001 0.002 0.02
7
E
n
12
300
2.935
0.2
Capacity in Erlangs
Number of available circuits
Erlang-B Traffic TablesAbbreviated - For P.02 Grade of Service Only
#TrunksErlangs #TrunksErlangs #Trunks #TrunksErlangs #TrunksErlangs #TrunksErlangs #TrunksErlangs #TrunksErlangs1 0.0204 26 18.4 51 41.2 76 64.9 100 88 150 136.8 200 186.2 250 235.82 0.223 27 19.3 52 42.1 77 65.8 102 89.9 152 138.8 202 188.1 300 285.73 0.602 28 20.2 53 43.1 78 66.8 104 91.9 154 140.7 204 190.1 350 335.74 1.09 29 21 54 44 79 67.7 106 93.8 156 142.7 206 192.1 400 385.95 1.66 30 21.9 55 44.9 80 68.7 108 95.7 158 144.7 208 194.1 450 436.16 2.28 31 22.8 56 45.9 81 69.6 110 97.7 160 146.6 210 196.1 500 486.47 2.94 32 23.7 57 46.8 82 70.6 112 99.6 162 148.6 212 198.1 600 587.28 3.63 33 24.6 58 47.8 83 71.6 114 101.6 164 150.6 214 200 700 688.29 4.34 34 25.5 59 48.7 84 72.5 116 103.5 166 152.6 216 202 800 789.310 5.08 35 26.4 60 49.6 85 73.5 118 105.5 168 154.5 218 204 900 890.611 5.84 36 27.3 61 50.6 86 74.5 120 107.4 170 156.5 220 206 1000 999.112 6.61 37 28.3 62 51.5 87 75.4 122 109.4 172 158.5 222 208 1100 109313 7.4 38 29.2 63 52.5 88 76.4 124 111.3 174 160.4 224 21014 8.2 39 30.1 64 53.4 89 77.3 126 113.3 176 162.4 226 21215 9.01 40 31 65 54.4 90 78.3 128 115.2 178 164.4 228 213.916 9.83 41 31.9 66 55.3 91 79.3 130 117.2 180 166.4 230 215.917 10.7 42 32.8 67 56.3 92 80.2 132 119.1 182 168.3 232 217.918 11.5 43 33.8 68 57.2 93 81.2 134 121.1 184 170.3 234 219.919 12.3 44 34.7 69 58.2 94 82.2 136 123.1 186 172.4 236 221.920 13.2 45 35.6 70 59.1 95 83.1 138 125 188 174.3 238 223.921 14 46 36.5 71 60.1 96 84.1 140 127 190 176.3 240 225.922 14.9 47 37.5 72 61 97 85.1 142 128.9 192 178.2 242 227.923 15.8 48 38.4 73 62 98 86 144 130.9 194 180.2 244 229.924 16.6 49 39.3 74 62.9 99 87 146 132.9 196 182.2 246 231.825 17.5 50 40.3 75 63.9 100 88 148 134.8 198 184.2 248 233.8
Erlangs
Equation behind the Erlang-B Table
Pn(A) =
An
n!
1 + + ... +A1!
An
n!
Pn(A) = Blocking Rate (%)with n trunksas function of traffic A
A = Traffic (Erlangs)n = Number of Trunks
Offered Traffic lost due to blocking
Numberof
Trunks
time
max # oftrunks
average# of busychannelsOffered
Traffic,A
The Erlang-B formula is fairly simple to implement on hand-held programmable calculators, in spreadsheets, or popular programming languages.(factorial)
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
Typical Traffic Distributionon a Cellular System
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Hour
SUN
MON
TUE
WED
THU
FRI
SAT
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.
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
High-Level Traffic Forecasting and Business Planning
• 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.
Year
Population
Penetration
# Subscribers
BH Erlangs/Sub
BH Total Erlangs
# of Cell Sites
Avg. Erl/Cell
Avg. Chan./Cell
Total Voice Chans.
0/Start
1,000,000
0.1%
1,000
.100
100
10
10
17
170
1
1,000,000
2.5%
25,000
.05
1,250
25
50
61
1,525
2
1,000,000
5.0%
50,000
.04
2,000
35
57
68
2,380
3
1,000,000
7.0%
70,000
.03
2,100
40
52.5
64
2,560
4
1,000,000
9.0%
90,000
.028
2,520
45
56
67
3,015
5
1,000,000
12%
120,000
.025
3,000
50
60
71
3,550
• 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
117
1110
19
85
76
52
73
816
7 166
99
7
Existing SystemTraffic In Erlangs
Where is the Traffic?
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!
22,100
3620 66201230
5110
4215
920
Vehicular Traffic
Land UseDatabases
Population Density
27 mE/Sub in BH
103,550 Subscribers1,239,171 Market Population
adding 4,350 subs/month
new Shopping Center
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
Vehicle Speed,MPH
Vehicle Spacing,
feet
Vehicles per mile,per lane
0 20 26410 42 12620 64 8330 86 6145 119 4460 152 35
Vehicle spacing 20 ft. @stopRunning Headway 1.5 seconds
Vehicles per Mile
VEHICLE SPACING AT COMMON ROADWAY SPEEDS0
50 MPH40 MPH30 MPH20 MPH10 MPH
0 MPH
100 200 300 400 500 600 700 800 feet
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 t
runks required per cell/sector• Modern software tools automate m
ajor parts of this process
Cell Grid
Land Use
TrafficDensity 3.5%
27mE
Example Wireless Usage Profile
Number of call attempts per subscriber in busy hour
Mobile originated calls
Mobile terminated calls
Percentage of Time in Soft Handoff
Registration attempts per subscriber during busy hour
proportion of total calls on systemsuccessful callsCalls not answeredcalls to a busy line
proportion of total calls on systemsuccessful callsCalls not answeredpaging requests not answered
25 mE
35%
2
87 %70 %15 %15 %
13 %15 %10 %75 %
Offered Traffic, mE per subscriber in busy hour
Average Call Duration1.667
150 sec. (41.7 mE)
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
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
Trunking EfficiencyAn Important CDMA Implication
• AMPS/TDMA/GSM sectorization distributes available channels among sectors– this results in a net decrease in capaci
ty, although it gives better flexibility for managing interference
– Example: 45 ch. omni = 35.6 Erl3=sector: 15 ch. = 9.01 Erl,sector cell total cap. = 27.0
1 Erl• In CDMA, each additional sector is an ad
ditional 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
CONVENTIONAL SECTORIZATION
1/31/3
1/31
CDMA SECTORIZATION
11
11
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
Digital Transmission Hierarchy
DS-0
1
30DS-0s
30DS-0sDS-1
T-1
30
16DS-1s
16DS-1s
DS-3
480
Traffic Engineering
Exercise
0.2 Erlangs
1.0 Erlangs
3.0 Erlangs
Busy-Hour Contribution
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.
0.2 Erlangs
1.0 Erlangs
3.0 Erlangs
Busy-HourContribution
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
(see next page to continue for traffic growth part)
Channels Required
Traffic,Erlangs
Traffic BinCounts
0.2 1.0 3.0 Erlangs
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
New Erlangs Channels RequiredOriginal 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.
Channels Required
(see next page to continue for traffic growth part)
157-
112-
13122
179-
112-
871
1295
193-
6166
14131
133-
133-
175-
2-2-
12113
7--
62-
194-
5--
-36
-53
-45
Traffic,Erlangs
Traffic BinCounts
10
4.2
12.4
4.2
20.6
14
11.6
6.821
26.4
35.2
19
1.4 3.2
6
8.4
1.0
7.8
22.4
18.8
5.6
5.6
17
9
20
9
29
21
19
1329
35
45
27
5 8
12
15
4
14
31
27
11
11
0.2 1.0 3.0 Erlangs
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?
New Erlangs Channels RequiredOriginal Erlangs
10
4.2
12.4
4.2
20.6
14
11.6
6.821
26.4
35.2
19
1.4 3.2
6
8.4
1.0
7.8
22.4
18.8
5.6
5.6
21
12
25
12
38
28
24
1639
47
60
36
6 10
15
19
5
18
41
35
14
14
14
5.88
17.36
5.88
28.84
19.6
16.24
9.52
29.4 36.96
49.28
26.6
1.96 4.48
8.4
11.76
1.4
10.92
31.36
26.32
7.84
7.84