Subscriber Demands and Network Requirements –

the Spectrum Capex trade-off

Hugh Collins

Agenda

Traffic modelling principles Service modelling Data: the growth area Mobile network dimensioning Spectrum Efficiency Tool: modelling the

relation of spectrum, traffic and network dimensioning

Traffic Modelling Principles

Traffic modelling principles

The network must carry the offered traffic! … but carrying all traffic is hard to do – traffic peaks

can be very high– Partly a technical problem – spectrum is limited, so

networks have limited capacity but traffic peaks can be far above average traffic

– Therefore an economic problem also – if the network is built to handle the peaks, then it is very under-used for most of the time

“Grade of Service” – probability of network busy– Calls fail, data transmitted slowly or delayed– Wireless networks usually designed to reject about 2% of

voice calls in the busy hour

For voice use Erlang B; For Data use Erlang C

The Erlang B formula

Erlang B calculates the probability of blocking– The probability that a call arriving at a link or switch (with a

defined capacity) finds the link/switch busy Erlang B is used for low latency traffic such as voice

or video calls

– Pb = Probability of blocking (%)– m = number of servers/ circuits/ links/ lines– E = λh = total amount of traffic offered (Erlangs)

(Arrival rate x average holding time)

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m

b

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P

Calculating Erlang B

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0 10 20 30 40 50

Traffi

c (er

lang

s)

Number of lines

5%2%1%

The Erlang C formula Erlang C calculates the probability of waiting in a

queuing system– If all servers are busy when a request arrives, the request is

queued– An unlimited number of requests may be held in the queue

simultaneously Erlang C used for data traffic

– PW = probability of queuing for a time > 0 secs (%)– m = number of servers/ circuits/ links/ lines– E = total amount of traffic offered (Erlangs)

1m

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0 10 20 30 40 50

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Number of lines

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Calculating Erlang C

Service modelling

Categorising subscriber services Before we can dimension, we need to understand the

services and their traffic requirements Various methods of categorising can be used One potential way is presented in ITU-R Rec M.8161:

– Speech: Toll quality voice (64kb/s on a fixed network, much less than this on a mobile network)

– Simple messaging: User bit rate of 14 kb/s– Switched data: User bit rate of 64kb/s– Asymmetrical multimedia services

Medium multimedia: User bit rate of 64/384 kb/s High multimedia: User bit rate of 128/2000 kb/s

– High interactive multimedia: User bit rate of 128/128kb/s Faster services represented as multiples of this

However service speeds have risen in the past decade!

1 ITU-R Recommendation M.816 - Framework for services supported by International Mobile Telecommunications-2000

Typical service characteristics

Some typical values are shown below, but local data should be used where available

Busy Hour Call Attempts

Call duration (seconds)

Activity factor

Pedestrian Vehicular Pedestrian Vehicular Pedestrian Vehicular

Speech 0.8 0.4 120 120 0.5 0.5

Simple messaging 0.3 0.2 3 3 1 1

Switched data 0.2 0.02 156 156 1 1

Medium multimedia 0.4 0.008 3000 3000 0.003/

0.0150.003/ 0.015

High multimedia 0.06 0.008 3000 3000 0.003/

0.0150.003/ 0.015

High interactive multimedia

0.07 0.011 120 120 1 1

Source: ITU-R Report M.2023 – Spectrum requirements for IMT-2000

Service demands will also vary by location Different areas will provide:

– Different population densities– Different service mixes– Different service demands– Different service time profiles

Consider, for example:Hot spots– Airports– Railway or bus stations– Cafes– Sports stadiumsHot routes– Motorways/ highways – Railway lines

Service demands vary by time Our earlier service characteristics were partly defined

by Busy Hour Call Attempts (BHCA)– But voice and data busy hours are typically different– And data typically has similar use across a number of hours

0%

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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Perc

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affic

Time of day

Voice

Data

Data: the growth area

Data applications

E-mail:– Message 5-10 kbytes– Attachment 20-1000+ kbytes– 10 messages in busy hour?– average 1 Mbyte per

user in busy hour– Symmetrical up and down

Internet browsing:– Download 40 pages in busy

hour– Average 50 kbytes per page– average 2 Mbytes per

user in busy hour– Asymmetrical: more down

than up

Streamed audio:– 128 kb/s– Average say 5 mins in busy

hour– average 4.8 Mbytes per

user in busy hour– Downstream

Streamed video:– 512 kb/s– Average say 5 mins in busy

hour– average 19.2 Mbytes per

user in busy hour– Downstream

Data growth

Global mobile data traffic is growing very fast:– Nearly tripled year-on-year, for the past 3 years!– In March 2010, Ericsson reported that global mobile data

traffic overtook mobile voice traffic

CAGR 92%

Source: Cisco Visual Networking Index 2011

Driven by devices

The introduction of smarter mobile devices drivesdata increases (as well as the applications used!)

Source: Cisco Visual Networking Index 2011

Mobile network dimensioning

Example: A mobile network

Other Networks

GMSCBSC

VLR

MSC

VLR

VLR

MSC

HLR

BSC

BSC

BSC

BSC

BSC

BSC

BSC

BSC

MSC

BTS

BTS

BTS

BTS

BTS

GMSC

GMSC

Radio Layer MSC Layer Transit Layer. May not exist in all

networks

Network components to be dimensioned Radio Access Network:

– eNode-B/ Node-B/ BTS– RNC (Radio Network Controller) or BSC (Base Station Controller)– Access links/ backhaul

Core Network:– Links: for example STM-1, Gigabit Ethernet, 10GE– Routers, Switches– Databases: for example HLR, VLR– Network operations and management

Application Platforms:– Data/ Internet access– Voicemail– MMS/ SMS– etc

Network component capacities

In radio networks, the relevant measures of capacity are:– connected subscribers– voice minutes– megabytes of traffic– erlangs of traffic– service platform usage

Challenges created by traffic growth

There are many! And the whole network is affected Some examples:

–More sites/ smaller site radii– Increase in backhaul capacity

Movement towards high capacity microwave/ fibre–Need for Evolved Packet Core

To facilitate improved session, mobility and QoS management– Improvements in ‘back-office’

For example, the challenges faced in billing to measure ‘caps’ and charging

– Improvements in network monitoring and management To identify and removing bottlenecks To optimising equipment performance and interworking

… additional investment required

Spectrum Efficiency Tool:

modelling the relation of spectrum, traffic and network dimensioning

Main network dimensioning dependencies

RAN siteCapacity

TrafficServices

QoS

Site count /Network cost

Availablespectrum

A typical network dimensioning process

1. Set the objectives, for example:– The technology to be used– The geographic and population coverage– The traffic throughput – The Quality of ServiceWith the spectrum available, these parameters determine the network’s capacity

2. Obtain the geographic and population data– Population by administrative region– Define/ designate and use types; rural, suburban and urban

3. Compute the number of sites required to meet the objectives– Thereby the network design/architecture – Thereby the network cost

Site / spectrum requirements modelling

An engineering model to generate dimensioning of radio network under varying assumptions of:– Subscriber numbers / market share– Services provided / traffic offered– Spectrum available

Illustrates how changing subscriber demands can have a significant impact on the network– The spectrum versus sites trade-off– The cost versus capacity versus QoS trade-off

Developed to examine and optimise spectrum allotment / assignment decisions

Model overview

Traffic/service mix

Spectrum/technology mix

Regionalcoverage

Subscriberpopulation

Calculatorengine

Requiredspectrum,site count& costs

Graph store

Basis for spectrum calculation Based on ITU-R Recommendation M.1390 - Methodology for

the Calculation of IMT-2000 Terrestrial Spectrum requirements

For each service:

where:FTerrestrial= Terrestrial component spectrum requirement (MHz) = Guard band adjustment factor (dimensionless)es = Geographic weighting factor (dimensionless)Tes = Traffic (Mb/ s / cell)Ses = Net system capability (Mb/ s / MHz / cell)

es

eseseseslTerrestria

STαβFαβF

Net system capability Accounts for underlying modulation & multiple access

factors ...– ... as well as radio resource management factors– Such as power control, discontinuous transmission, frequency

reuse pattern, band splitting/grouping, frequency hopping, adaptive antennas

Net system capability for different evolutions of systems, Hideaki Takagi and Bernhard H. Walke (2008), Spectrum Requirement Planning in Wireless Communications, pp56, John Wiley & Sons Ltd

Spectrum requirements calculation overview

Cell area /Population density /

Penetration rate

Busy hour call attempts /

Call duration /Activity factor

Number of users / cell

Offered traffic / user

Offered traffic / group

Blocking probability(delay critical)

Queuing probability(non delay critical)

Channels / group

Offered traffic / cell

Required bit rate / cell

Required spectrum

Guard band adjustment factor

Geographic weighting factor

Channels / cellGroup size

Final total spectrum requirement

Service channel bit rate

Setting accessible population data

Defining how the population in each region is split between each geotype ....

... and then defining what percentage of this population is accessible

Total% # % # #

1 Region A 93.9 2,127,400 6.1 137,700 2,265,100 2 Region B 39.2 107,900 60.8 167,100 275,000 3 Region C 95.1 829,000 4.9 42,600 871,600 4 Region D 82.9 862,800 17.1 178,500 1,041,300 5 Region E 75.8 102,000 24.2 32,500 134,500 6 Region F 62.6 109,900 37.4 65,600 175,500 7 Region G 54.8 60,900 45.2 50,300 111,200 8 Region H 71.2 104,100 28.8 42,200 146,300 9 Region I 85.6 109,200 14.4 18,300 127,500

10 Region J 70.9 58,100 29.1 23,800 81,900 11 Region K 71.8 281,200 28.2 110,700 391,900 12 Region L 34.9 79,600 65.1 148,600 228,200

83 4,832,100 17 1,017,900 5,850,000

ID NamePopulation

Urban Rural

Total

Total% km2 % km2 km2

1 Region A Hilly Large 4.0 303 96.0 7,265 7,569 2 Region B Desert Small 0.6 147 99.4 26,496 26,646 3 Region C Flat Large 2.5 119 97.5 4,662 4,782 4 Region D Flat Large 11.9 186 88.0 1,380 1,568 5 Region E Hilly Small 5.0 21 95.0 393 413 6 Region F Hilly Small 6.7 27 93.3 381 409 7 Region G Desert Small 0.2 58 99.8 32,832 32,894 8 Region H Hilly Small 4.3 40 95.7 893 933 9 Region I Flat Small 0.7 45 99.3 6,840 6,886

10 Region J Hilly Small 1.3 28 98.7 2,178 2,205 11 Region K Hilly Small 6.2 69 93.8 1,040 1,109 12 Region L Hilly Small 2.0 72 98.0 3,548 3,621

1.3 1,115 98.7 87,908 89,035

Rural

Total

LandmassID Name Terrain City Type Urban

Setting administrative area data

Terrain type, city type and geotype define how signals propagate in the link budgets

Setting target coverage levels

Define the target coverage In this example, defined by existing operator coverage levels

Population factor estimates the ratio of population living in the coverage area

Landmass Population% km2 Factor # % km2 Factor # km2 #

1 Region A 87.7 266 0.90 1,818,927 4.0 291 0.50 65,408 557 1,884,335 2 Region B 66.0 97 0.90 92,255 0.5 140 0.50 79,373 237 171,627 3 Region C 92.1 110 0.90 708,795 2.5 116 0.50 20,235 226 729,030 4 Region D 87.9 164 0.90 737,694 11.9 164 0.50 84,788 328 822,482 5 Region E 94.9 20 0.90 87,210 5.0 20 0.50 15,438 40 102,648 6 Region F 93.2 26 0.90 93,965 6.7 26 0.50 31,160 51 125,125 7 Region G 52.0 30 0.90 52,070 0.2 58 0.50 23,893 88 75,962 8 Region H 87.4 35 0.90 89,006 4.3 38 0.50 20,045 73 109,051 9 Region I 81.9 37 0.90 93,366 0.7 45 0.50 8,693 82 102,059

10 Region J 96.3 27 0.90 49,676 1.2 27 0.50 11,305 54 60,981 11 Region K 93.8 64 0.90 240,426 6.2 64 0.50 52,583 128 293,009 12 Region L 92.4 66 0.90 68,058 2.0 70 0.50 70,585 137 138,643

84.4 941 4,131,446 1.2 1,059 483,503 2,001 4,614,948

Target Coverage

ID Name

Total

Urban RuralPopulationLandmass Landmass Population

Total

Calculating cell area

Link budget for most limiting

service

Antenna geometry

Urban geometry

Regiontopography

COST 231 Propagation

Models

Cell area

Cell rangeSectors / site

Cell area together with population, geographic and coverage data enable subscriber densities to be calculated

Setting services and use statistics

Service Pede

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ink

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ink

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Speech (S) 73 73 0.8 0.4 120 120 16 16 0.5 0.5 0.5 0.5 16 16 0.07 0.07Simple Message (SM) 40 40 0.3 0.2 3 3 14 14 1 1 1 1 14 14 0.125 0.125Switched Data (SD) 13 13 0.2 0.002 156 156 64 64 1 1 1 1 64 64 0.125 0.125Medium Multimedia (MMM) 15 15 0.4 0.008 3000 3000 64 384 0.003 0.015 0.003 0.015 64 384 0.125 0.125High Multimedia (HMM) 15 15 0.006 0.008 3000 3000 128 2000 0.003 0.015 0.003 0.015 128 2000 0.125 0.125High Interactive Multimedia (HIMM) 25 25 0.007 0.011 120 120 128 128 1 1 1 1 128 128 0.125 0.125

Net system capability

(bit/s/Hz/cell)Pedestrian Vehicular

Penetration rate (%)

Busy Hour Call

Attempts

Call Duration (s)

Net user rates (kb/s)

Activity Factors Service channel bit rate* (kb/s)

Define what services are used and how they are used The above example relates to 3G Traffic metrics based on ITU-R Report M.2023 -

Spectrum Requirements for IMT 2000, but real observed traffic figures should be used wherever possible

Calculating spectrum required

The traffic offered by each service can be calculated This can be aggregated and mapped to traffic

channels–Using Erlang B and Erlang C, as appropriate

From this, the amount of required spectrum can be derived (using the ITU-R Rec. M.1390 formula) –To meet demanded traffic, as driven by the subscriber

numbers–Based on calculated site numbers

Spectrum requirements planning

The spectrum calculation is made many times by varying the cell radius factor

The results can then be graphed, and interpreted ...

Maximumcell radius

(link budget)

CellularSite Minimum

cell radius(economic limit)

100%(radius factor)

0%

More spectrum requiredMore sites required

Typical output: spectrum versus site count

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Site

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Spectrum (MHz)

Spectrum Site Count (Capacity)

10%20%30%40%50%60%70%80%90%100%

Marketshare

Interpreting the curves

Sites

Spectrum

Block steps/packaging representing possible choices

Volatile choice (model viewpoint)

Greedy choice(Poor network design,spectrum hoarding)

Optimum area (purely technical perspective)

Unsatisfactory choice

(operator starved)

Improved capacity of networks, improved economy for operatorsBetter for re-farming, more competition possible

Simple 2-operator example, 36MHz available

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Operator A MHz Allotted

Operator A BTS

Operator B BTS

Total BTS

Thank you

Any questions?