# Network Economics Appraising Investment - TT

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 Em Pb m! i m E i0 i! Pb = Probability of blocking (%) m = number of servers/ circuits/ links/ lines E = h = total amount of traffic offered (Erlangs) (Arrival rate x average holding time) Traffi c (erlangs) Calculating Erlang B 50 45 40 35 30 25 20 15 10 5 0

5% 2% 1% 0 10 20 30 Number of lines 40 50 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 Em m m! m E Pw i m 1 E Em m i0 i! m! m E PW = probability of queuing for a time > 0 secs (%) m = number of servers/ circuits/ links/ lines E = total amount of traffic offered (Erlangs) Traffi

c (erlangs) Calculating Erlang C 50 45 40 35 30 25 20 15 10 5 0 5% 2% 1% 0 10 20 30 Number of lines 40 50 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/ 0.015 0.003/ 0.015 High multimedia 0.06 0.008 3000 3000 0.003/ 0.015 0.003/ 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 stadiums Hot 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 7% 6% Voice 5% Data 4% 3% 2% 1% 0% 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 Percentage of daily traffi c 8% Time of day 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 drives data increases (as well as the applications used!) Source: Cisco Visual Networking Index 2011 Mobile network dimensioning Example: A mobile network BTS BSC

GMSC BSC BTS MSC BSC BSC BTS BSC VLR O t h e r HLR MSC GMSC VLR BSC BTS BSC MSC VLR BSC BTS GMSC

BSC Radio Layer MSC Layer Transit Layer. May not exist in all networks N e t w o r k s Network components to be dimensioned Radio Access Network: Core Network: eNode-B/ Node-B/ BTS RNC (Radio Network Controller) or BSC (Base Station Controller)

Access links/ backhaul 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 QoS QoS Services Services Traffic Traffic Site Site count count // Network Network cost cost Available Available spectrum spectrum RAN RAN site

site Capacity Capacity 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 Service With the spectrum available, these parameters determine the networks 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 Subscriber Subscriber population population Regional Regional coverage coverage Calculator Calculator engine engine Spectrum/ Spectrum/ technology technology mix mix Traffic/ Traffic/ service service mix mix Graph Graph store store Required Required spectrum, spectrum, site site count count & & costs

costs Basis for spectrum calculation Based on ITU-R Recommendation M.1390 - Methodology for the Calculation of IMT-2000 Terrestrial Spectrum requirements For each service: Tes FTerrestria l esFes es Ses where: FTerrestrial= Terrestrial component spectrum requirement (MHz) es = Guard band adjustment factor = Geographic weighting factor Tes = Traffic Ses = Net system capability (dimensionless) (dimensionless) (Mb/ s / cell) (Mb/ s / MHz / cell) 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 Busy Busy hour hour call call attempts attempts // Call Call duration duration // Activity Activity factor factor Cell Cell area area // Population Population density density // Penetration Penetration rate rate Number Number of of users users // cell cell Geographic Geographic

weighting weighting factor factor Service Service channel channel bit bit rate rate Guard Guard band band adjustment adjustment factor factor Offered Offeredtraffic traffic // user user Offered Offeredtraffic traffic // cell cell Group Group size size Offered Offeredtraffic traffic // group group Channels Channels //

cell cell Required Required bit bit rate rate // cell cell Blocking Blocking probability probability (delay (delay critical) critical) Queuing Queuing probability probability (non (non delay delay critical) critical) Channels Channels // group group Required Required spectrum spectrum Final Final total spectrum total spectrum requirement requirement

Setting accessible population data ID Name % 1 Region A 2 Region B 3 Region C 4 Region D 5 Region E 6 Region F 7 Region G 8 Region H 9 Region I 10 Region J 11 Region K 12 Region L Total Urban # 93.9 2,127,400 39.2 107,900 95.1 829,000 82.9 862,800 75.8 102,000 62.6 109,900 54.8 60,900 71.2 104,100

85.6 109,200 70.9 58,100 71.8 281,200 34.9 79,600 83 4,832,100 Population Rural Total % # # 6.1 137,700 2,265,100 60.8 167,100 275,000 4.9 42,600 871,600 17.1 178,500 1,041,300 24.2 32,500 134,500 37.4 65,600 175,500 45.2 50,300 111,200 28.8 42,200 146,300 14.4 18,300

127,500 29.1 23,800 81,900 28.2 110,700 391,900 65.1 148,600 228,200 17 1,017,900 5,850,000 Defining how the population in each region is split between each geotype .... ... and then defining what percentage of this population is accessible Setting administrative area data ID Name Terrain Urban City Type 2 % 1 2 3 4 5 6 7 8

9 10 11 12 Region A Region B Region C Region D Region E Region F Region G Region H Region I Region J Region K Region L Hilly Desert Flat Flat Hilly Hilly Desert Hilly Flat Hilly Hilly Hilly Total Large Small Large Large Small Small

Small Small Small Small Small Small Landmass Rural km 4.0 0.6 2.5 11.9 5.0 6.7 0.2 4.3 0.7 1.3 6.2 2.0 1.3 % 303 147 119 186 21 27 58 40 45 28 69 72 1,115

Total 2 km2 km 96.0 99.4 97.5 88.0 95.0 93.3 99.8 95.7 99.3 98.7 93.8 98.0 98.7 7,265 26,496 4,662 1,380 393 381 32,832 893 6,840 2,178 1,040 3,548 87,908 Terrain type, city type and geotype define how signals propagate in the link budgets 7,569 26,646 4,782

1,568 413 409 32,894 933 6,886 2,205 1,109 3,621 89,035 Setting target coverage levels Target Coverage ID Urban Name Landmass 1 Region A 2 Region B 3 Region C 4 Region D 5 Region E 6 Region F 7 Region G 8 Region H 9 Region I 10 Region J 11 Region K 12 Region L Total km 87.7 66.0

92.1 87.9 94.9 93.2 52.0 87.4 81.9 96.3 93.8 92.4 84.4 266 97 110 164 20 26 30 35 37 27 64 66 941 Factor 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90 0.90

# 1,818,927 92,255 708,795 737,694 87,210 93,965 52,070 89,006 93,366 49,676 240,426 68,058 4,131,446 Landmass Population 2 % km 4.0 0.5 2.5 11.9 5.0 6.7 0.2 4.3 0.7 1.2 6.2 2.0 1.2 291 140 116

164 20 26 58 38 45 27 64 70 1,059 Factor 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 # 65,408 79,373 20,235 84,788 15,438 31,160 23,893 20,045 8,693 11,305 52,583 70,585 483,503

Total Landmass Population km2 557 237 226 328 40 51 88 73 82 54 128 137 2,001 # 1,884,335 171,627 729,030 822,482 102,648 125,125 75,962 109,051 102,059 60,981 293,009 138,643 4,614,948 Define the target coverage Population 2

% Rural In this example, defined by existing operator coverage levels Population factor estimates the ratio of population living in the coverage area Calculating cell area Link Link budget budget for for most limiting most limiting service service Urban Urban geometry geometry Region Region topography topography COST COST 231 231 Propagation Propagation Models Models Antenna Antenna geometry geometry Sectors

Sectors // site site Cell Cell range range Cell Cell area area Cell area together with population, geographic and coverage data enable subscriber densities to be calculated Setting services and use statistics Speech (S) Simple Message (SM) Switched Data (SD) Medium Multimedia (MMM) High Multimedia (HMM) High Interactive Multimedia (HIMM) 73 40 13 15 15 25 73 0.8 0.4 120 120 40 0.3 0.2 3 3

13 0.2 0.002 156 156 15 0.4 0.008 3000 3000 15 0.006 0.008 3000 3000 25 0.007 0.011 120 120 16 16 0.5 0.5 0.5 0.5 14 14 1 1 1 1 64 64 1 1 1 1 64 384 0.003 0.015 0.003 0.015 128 2000 0.003 0.015 0.003 0.015 128 128 1 1 1 1 Uplink 16 16 0.07 14 14 0.125 64

64 0.125 64 384 0.125 128 2000 0.125 128 128 0.125 Define what services are used and how they are used Downlink Downlink Vehicular Uplink Downlink Pedestrian Service Net channel bit cap rate* (kb/s) (bit/s/ Uplink Activity Factors Uplink Downlink Net user rates (kb/s) Uplink

Vehicular Call Duration (s) Pedestrian Vehicular Busy Hour Call Attempts Pedestrian Vehicular Service Pedestrian Penetration rate (%) 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 0% Cellular Site Minimum cell radius (economic limit) 100% (radius factor) Maximum cell radius (link budget) More spectrum required More sites required The results can then be graphed, and interpreted ... Typical output: spectrum versus site count Spectrum Site Count (Capacity) 7000 Market share 6000 10% Site Count 5000 20% 30%

4000 40% 50% 3000 60% 70% 2000 80% 90% 1000 100% 0 0 5 10 15 Spectrum (MHz) 20 25 30 Interpreting the curves Sites Volatile choice (model viewpoint) Optimum area (purely technical perspective)

Unsatisfactory choice (operator starved) Greedy choice (Poor network design, spectrum hoarding) Spectrum Block steps/packaging representing possible choices Improved capacity of networks, improved economy for operators Better for re-farming, more competition possible Simple 2-operator example, 36MHz available 9000 8000 7000 Number of BTS sites 6000 5000 Operator A BTS Operator B BTS 4000 Total BTS 3000 2000 1000 0

2 4 6 8 10 12 14 16 18 Operator A MHz Allotted 20 22 24 26 28 30 Thank you Any questions?

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