NITA s mobile LRAIC model draft v3 cost model

Transcription

1 Model Documentation NITA s mobile LRAIC model draft v3 cost model 27 March 2008 Our ref: Analysys Consulting Limited St Giles Court, 24 Castle Street Cambridge, CB3 0AJ, UK Tel: +44 (0) Fax: +44 (0) consulting@analysys.com

2 NITA s mobile LRAIC model draft v3 cost model Model Documentation Contents 1 General introduction 1 2 Introduction to model documentation 2 3 Installing and running the model Model workbooks Running the model 5 4 Main inputs 5 5 Demand and network assumptions Market demand Market share Traffic volumes Demand drivers Radio network deployment Transmission and switching network deployment 5 6 Network design algorithms Radio network: site coverage requirement Radio network: site capacity requirement (GSM and UMTS) Radio network: TRX requirements Backhaul transmission BSC deployment G NodeB deployment G channel kit and carriers deployment 5

3 Model Documentation 6.8 3G backhaul deployment G RNC deployment G MSC deployment Calculation of length of backbone links Transit layer deployment G MSS and MGW deployment Deployment of other network elements 5 7 Expenditure calculations Purchasing, replacement, and capex planning periods Retirement algorithm Equipment unit prices 5 8 Annualisation of expenditure The rationale for using economic depreciation Implementation of economic depreciation principles Implementation details 5 9 Service cost calculations 5 10 Glossary of abbreviations used 5 Confidential annexes (provided as separate files) A: Draft v3 cost model for TDC B: Draft v3 cost model for Sonofon C: Draft v3 cost model for Telia D: Draft v3 cost model for Hi3G Public annexes E: Cost of capital F: Model updates G: Optimisation H: Decisions applied in the draft v3 model

4 1 General introduction NITA plans to finish its long-run average incremental costing (LRAIC) model for mobile termination at the end of May At that time, NITA will make its final decision on the LRAIC-based termination prices that will come into force from 1 January According to the Executive order no from 31 October 2006, NITA is obliged to use the efficiently incurred costs of the highest-cost company as the basis for setting LRAIC prices. As such, the LRAIC model includes the network operators TDC, Sonofon, Telia and Hi3G. During the process, NITA has also considered how to treat the MVNOs, Tele2 and Barablu, in the LRAIC model. Tele2 has been acquired by Telenor, which is also the owner of Sonofon. At this point NITA believes that Tele2 and Telenor (including and hereafter Sonofon) should be considered as one economic entity, and NITA s decision to treat Sonofon and Tele2 as one economic entity also applies in the context of calculating LRAIC-based costs. With regard to the MVNO operator Barablu, NITA is currently as a part of its investigation of the competition on mobile termination markets (Market 16) in the process of performing a market analysis for Barablu. If this analysis subsequently should conclude that Barablu has SMP and should be subject to price regulation, NITA will then consider the configuration of this price regulation. Should it be decided to price regulate Barablu according to the LRAIC method, this could be based on the following options: the mobile termination rate of its host operator the MVNO s own cost of termination plus its commercially agreed access charge the MVNO s own cost of termination plus a calculation of the access charge on an LRAIC basis. It is the view of NITA, that the second and third of these approaches would be consistent with the legislation. Because of the highest cost principle, however, the second approach could give rise to incentives for the host operators to increase the commercially agreed access charge. Therefore, NITA believes that the results of the third approach should be used as a ceiling for the results from the second approach.

5 NITA s mobile LRAIC model draft v3 cost model 2 2 Introduction to model documentation This document accompanies the draft v3 reconciled bottom-up demand, network and cost model for long-run average incremental costing (LRAIC), distributed to Danish industry parties on 31 March The draft v3 bottom-up model specifies in detail the demand, network and unit cost parts of each individual operator. A roadmap of the model is shown in Exhibit 1 below.

6 NITA s mobile LRAIC model draft v3 cost model 3 Collating market demand - voice Operator data on historic voice usage Collating market demand - data Operator data on historic nonvoice usage Market scenario subs_evolving Historic and forecast subscribers by operator NwDes.Operators Network design parameters by operator Market scenario select Historic and forecast voice and data traffic by operator NwDes.Selected Network design parameters for selected operator Operator select Demand data for selected operator Cov&Dem.In Outdoor coverage and demand calculations - normalisation of traffic by geotype DemCalc Busy hour demand calculations Untilisation.In Utilisation inputs for operators' assets Costscenario.basecase Basecase unit cost inputs CostTrends Capex and opex unit cost trends NwDes Network design algorithm Unit Capex Unit capex over time Unit Opex Unit opex over time FullNw Output of network elements required by demand NwDeploy Network deployment schedule, retirement and purchasing algorithms RouFacs Network routing factors Lifetime.In Accounting and economic asset lifetime data TotCapex Total capex incurred over time TotOpex Total opex incurred over time Dem.In Transposed service demand array NwEle.Out Network element output (routed demand volumes) EconDep Economic Depreciation algorithm Com.incr Common and incremental cost calculations Results Exhibit 1: Model schematic [Source: Analysys]

7 NITA s mobile LRAIC model draft v3 cost model 4 In this draft v3 model, the demand and network aspects have been updated in response to the operators hearing submissions and new information provided since 15 December The costing module has been populated with a realistic set of values for costs, price trends and the weighted average cost of capital (WACC). The bottom-up model has also been reconciled with the top-down information submitted by each mobile operator. This documentation covers the whole model: Section2 introduces the model documentation Section 3 explains how to install and run the model. Section 4 provides a quick reference to the main inputs of the draft model. Section 5 describes the assumptions and structure of the demand module. Section 6 details the network design algorithms of the network module. Section 7 describes the expenditure calculations. Section 8 explains the cost annualisation calculations. Section 9 details the service costing calculations Section 10 provides a glossary of terms. This document also provides annexes for: Annex A: Demand and network model for TDC Annex B: Demand and network model for Sonofon Annex C: Demand and network model for Telia Annex D: Demand and network model for Hi3G Annex E: Cost of capital Annex F: Model updates. Annex G: Optimisation Annex H: Decisions applied in the draft v3 model.

8 NITA s mobile LRAIC model draft v3 cost model 5 3 Installing and running the model This section presents the basic operation of the model. 3.1 Model workbooks The model is presented in an Excel workbook, called LRIC_model_NITA_draft_v3.xls, which can be stored in a local directory and opened as a single file. There are no external links and no macros. The model has been developed using Microsoft Excel 2000, though it should be compatible with later versions of Excel. The structure of the Excel workbook is detailed in Exhibit 2 below. Exhibit 2: Sheet-by-sheet description of the model [Source: NITA draft demand network and demand model, Analysys] Sheet name Input summary Roadmap Con V.H Style Lists Categorisation table Control.Panel Collating market demand-voice Collating market demand-data Market_scenario_ subs_evolving Description and details of spreadsheet calculations Summary of model inputs by operator Flow diagram of model calculations with hyperlinks Contents description Version history Style guide Definition of lists commonly used in the model Operator asset, capex and opex categories Selection of operator and scenarios Collation and processing of voice demand for each operator Collation and processing of data demand for each operator Subscriber history and indicative forecast of evolution of market share Rows 7-20: mobile penetration Rows 23-40: market share and subscribers by operator Rows 41-79: 2G and 3G subscribers Rows 81-95: non-personal SIMs Rows : GPRS subscribers Rows : Summary for output

9 NITA s mobile LRAIC model draft v3 cost model 6 Sheet name Market_ scenario_ select Operator_ select Lifetime_In Cov&Dem_In DemCalc UtilisationIn NwDes.Operators Description and details of spreadsheet calculations Market and demand scenario subscribers and traffic for the selected market scenario, plus forecasts for usage per subscriber by operator Rows 6-265: historic parameters from collated actual data plus forecasts of usage per subscriber Rows : calculation of volumes by service. Demand parameters for the selected operator, including: Rows 55-94: table of demand sensitivity inputs set to 0% from 2023 onwards to remove service demand thereafter Rows : table of 0s and 1s to multiply into later arrays to zero out unit costs when there are no service volumes. Asset lifetime inputs and planning period inputs Calculation of coverage area and demand per geotype Rows 4-8: Urbanisation distribution Rows 11-52: distribution of 2G demand by geotype over time Rows 54-89: distribution of 3G demand by geotype over time. Conversion of service demand into cost drivers Rows 7-56: demand volumes linked in Rows 59-99: call duration volumes linked in Rows : calculation of successful calls per year Rows : calculation of busy hour load by service including ringing time to be added per conveyed minute Rows : input of service routeing factors Rows : calculation of busy hour load for each part of the network Maximum equipment utilisation, including scorched node calibration factors Network design parameters, including spectrum allocation and asset capacities for all of the mobile operators Rows 5-9: geotype definition Rows 10-71: spectrum Rows : cell radii and scorched-node outdoor coverage coefficients Rows : blocking probabilities Rows : area coverage Rows : coverage and capacity deployment factors Rows : traffic parameters Rows : network design parameters. Rows : 3G Licence payment sequence Rows : National roaming payments

10 NITA s mobile LRAIC model draft v3 cost model 7 Sheet name NwDes.Selected NwDes Full_Nw Description and details of spreadsheet calculations Network design parameters, including spectrum allocation and assets capacity for the selected mobile operator Network design calculation Rows 6-510: 2G coverage and capacity sites Rows : 2G transceivers Rows : 2G backhaul Rows : BSC layer. Rows : 3G coverage and capacity sites Rows : 3G channel kit Rows : 3G backhaul Rows : RNC layer Rows : 2G main switching layer and transmission Rows : 3G main switching layer and transmission Rows : other network elements. Network requirements in each year NwDeploy Purchasing and retirement algorithms expenditure schedule as a function of network requirements Dem_In Transposes service demand RouFac Routeing factors for network elements for average incremental cost allocation NwEle_Out Element output routed service demand DiscFacs Costscenario. basecase CostTrends UnitCapex TotCapex UnitOpex TotOpex WACC and discount factors for present value (PV) calculations Unit capex and opex cost inputs Real-terms cost trends and output weighted by cost trends Unit capex over time Total capital expenditures Unit opex over time Total operating expenditures EconDep Cost annualisation economic depreciation algorithm Com_incr Rows 7-158: Capex cost per unit output Rows : Opex cost per unit output Rows : Total cost per unit output Rows : Fully allocated economic cost per service unit (not used elsewhere in the model) Rows : Total economic cost recovery. Input of common assets by category and the incremental and common costing calculation Rows 3-309: Total and per-unit economic costs Rows : Input and calculation of proportion of network elements that are common

11 NITA s mobile LRAIC model draft v3 cost model 8 Sheet name Results Real.to.nominal Description and details of spreadsheet calculations Rows : Calculation of common and incremental costs by network element Rows : Calculation of incremental costs per service unit and common cost mark-ups Rows : Check of total cost recovery post-mark-up. Marked- up costs per unit of service demand Conversion of investment and expenditure from real into nominal terms, as required for Historic Cost Accounting (HCA) costing HCA Cost annualisation HCA algorithm HCA.nom.to.real HCA.service_cost Tilted_annity Erlang.table Summary table Conversion of HCA result from nominal into real terms Calculation of HCA costs per service unit Calculation of 2006 tilted annuity based costs per network element. Reference table: for a given a number of TRXs or channels in a sector and a blocking probability, this table provides the capacity of the sector in Erlangs Summary of operator inputs in model 3.2 Running the model In order to run the model, simply press the F9 (re-calculate) key. On some versions of Excel, a full recalculation (CTRL + ALT + F9) may be required. The model has run and calculated when calculate is no longer displayed in the Excel status bar. The model may take around ten seconds to fully calculate, particularly if run on an older computer.

12 NITA s mobile LRAIC model draft v3 cost model 9 4 Main inputs The model uses a number of input parameters, and is designed so that these can easily be changed. The table below provides a brief description of the main inputs and their location in the workbook. Exhibit 3: Input parameters and their location in the model [Source: Source: NITA draft Input parameter Control panel Subscriber traffic forecasts Market share of subscribers demand network and demand model, Analysys] Location in the model and brief description of the input Selection of options or scenarios to be applied to the model Location: Market_scenario_select The forecast per year-average subscriber of voice and data traffic volumes per month Location: Market_scenario_subs_evolving worksheet The evolution of subscribers and market share from 1 January Network roll out Location: NwDes.Operators worksheet, rows Network design parameters This controls the proportion of area covered by the coverage network in each year. Location: NwDes.Operators worksheet These parameters control all the operator specific aspects of the network design, and most of them can be modified by the user as required: spectrum allocation blocking probabilities cell radii coverage inputs traffic assumptions (call durations, busy hour, call attempts, traffic by geotype) maximum frequency reuse pattern site sectorisation site type deployment (own, third party sites) BTS capacity repeater/tunnel deployments backhaul: split between microwave and leased lines BSC capacities and remote percentage RNC capacities and remote percentage BSC-MSC link capacity MSC capacities

13 NITA s mobile LRAIC model draft v3 cost model 10 Input parameter Asset lifetimes Demand driver parameters Equipment costs Equipment price trends Cost of capital Location in the model and brief description of the input proportions of traffic traversing the backbone network HLR, SMSC, PCU and GSN capacities and minimum deployments. Location: Lifetime_in Input of asset lifetimes, planning and retirement periods. Location: DemCalc This sheet contains further inputs which are require to convert demand volumes into network drivers: SMS channel parameters GPRS traffic parameters UMTS channel parameters Ringing time per call Subscriber and PDP context registration in GSNs Routeing factors for Radio and Transmission parts of the network MSC processor, SMSC and GSN loading parameters. Location: UnitCapex and UnitOpex Capital and operating cost per unit of equipment, expressed in real 2006 DKK. Location: CostTrends Annual real-terms price trend for capital and operating cost components. Location: DiscFacs Real, pre-tax WACC and inflation.

14 NITA s mobile LRAIC model draft v3 cost model 11 5 Demand and network assumptions 5.1 Market demand Market demand is modelled for each mobile operator for historical years, based on data provided by NITA s statistics and information provided by the mobile operators in response to the data request. For future years, a forecast for market subscribers and traffic is presented. Subscribers The number of active subscribers in the market is calculated, with a projection of future population and assumed level of penetration of digital mobile services. The penetration is assumed to reach 120% by the end of the period, following a saturation formula (see Exhibit 4). This forecast explicitly excludes the new MVNO Barablu, which currently has a very small share of the market and traffic. Forecast volumes and subscribers of Barablu are therefore considered to be additional to the forecasts presented in the model. 140% 120% 100% 80% 60% 40% 20% 0% Active SIM penetration Exhibit 4: Modelled mobile penetration, in terms of active SIMs [Source: Analysys]

15 NITA s mobile LRAIC model draft v3 cost model 12 Traffic Information on historical traffic levels, up to 2007, is sourced from operator data. The forecast traffic demand for each mobile operator is determined by a projection of traffic per subscriber, multiplied by projected subscriber numbers. Traffic per subscriber is projected for each operator, specified in the traffic scenario sheet (Sheet Market_scenario_select, Rows 40-50, 52-62, etc). The following traffic services have been modelled, split according to the information supplied by each operator: Voice (incoming, outgoing off-net and on-net). SMS (incoming, outgoing off-net and on-net). 2G PS data traffic. 3G PS data traffic (Release 99). Incoming to VMS deposit. On-net to VMS deposit. On-net to VMS retrieval. Technical SMS. 3G Video minutes (split by incoming, outgoing off-net and on-net). ON 2G NR incoming, outgoing (applicable to TDC and Sonofon). OFF 2G NR incoming, outgoing (applicable to Telia and MVNOs). ON 3G NR incoming, outgoing (applicable to Sonofon). OFF 3G NR incoming, outgoing (applicable to Hi3G and MVNOs). OFF 2G MVNO SMS outgoing (applicable to MVNOs). OFF 3G MVNO SMS outgoing (applicable to MVNOs). These services are then divided into 2G and 3G network volumes as follows: Voice services: according to the voice migration profile SMS services: according to the subscriber migration profile 2G PS data: assumed all on the 2G network 3G PS data and 3G video: assumed all on the 3G network. The table below indicates how the various services interact with the network:

16 NITA s mobile LRAIC model draft v3 cost model 13 Radio Transmission Switch processing Service TRX or BSC or Inter- Inter- to VMS MSC SMSC SGSN HLR CK RNC to connect switch and core GGSN Voice traffic SMS traffic (1) Voice to/from VMS (2) Packet switched traffic (3) Video traffic Subscriber numbers NR on network NR off network (4) Notes: (1): SMS traffic is assumed to be carried in signalling channel reservation (2): calls which are deposited on the voic system do not utilise the radio network for call conveyance, although an allocation for ringing time is included (3): 2G PS traffic is assumed to be carried in data channel reservation; 3G packet switched data is added to the voice Erlang load (4): NR off the network is counted as NR on network for the corresponding other operator Exhibit 5: Indicative interactions between network elements [Source: Analysys] 5.2 Market share The market share of each operator is projected in the Market_scenario_subs_evolving worksheet. This scenario reflects NITA s position on the evolution of the market and represents the definitive basis on which costs will be calculated. The draft model presents an evolution to equality of market share between the established GSM players in the medium term, and the four network operators in the long term (according to the introduction, Tele2 is included with Sonofon for this purpose).

17 NITA s mobile LRAIC model draft v3 cost model 14 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Market share of subscribers TDC Sonofon Telia Hi3G Exhibit 6: Market shares in a slow evolution scenario [Source: Analysys] 5.3 Traffic volumes The forecast of usage per subscriber is projected in the Market_scenario_selected worksheet. In the draft v3 model, the forecast reflects NITA s position on the evolution of the market and represents the definitive basis on which costs will be calculated. 5.4 Demand drivers The total service volumes for the selected operator are converted into the main demand drivers which are used to dimension the various network elements. Voice services The number of voice minutes is converted into a year-average busy-hour Erlang (BHE) load (Sheet DemCalc, Rows ) using the following inputs: Proportion of annual traffic during 250 normal weekdays. Proportion of weekday traffic occurring in the normal busy hour.

18 NITA s mobile LRAIC model draft v3 cost model 15 The number of voice BHE is converted into a further measure, the number of busy hour call attempts (BHCA) (Sheet DemCalc, Rows ) using inputs of: Average call duration. Number of call attempts per successful call (e.g. due to unanswered calls). BHE annualtraffic Pd B d Pw 60 Where P d = Proportion of daily traffic in the busy hour P w = Proportion of annual traffic in the busy week days B d = Number of busy (week) days BHCA BHE D ave C Where C = call attempts per successful call D ave = average duration of a successful call. Ringing time Voice services explicitly include the additional Erlang load presented by the ringing time associated with calling. Ringing time occurs for calls to a B-subscriber where there is network occupancy until the call is answered, diverted or not answered. An estimated ringing time of 10 seconds for calls to an end user, and 5 seconds for calls to/from the VMS, is applied to the various call types. An estimate of 5 seconds is applied to VMS calls because some diversions are a result of a mobile ringing but not being answered, and some diversions are immediate. For each service, the model calculates: RingingMinutesPerConveyedMinute RingingTime CallAttemptsPerSuccessfulCall AverageSuccessfulCallDuration This ringing time per minute is added to the per-minute routeing factors for radio and transmission elements in the DemCalc routeing factor table.

19 NITA s mobile LRAIC model draft v3 cost model 16 SMS services The volume of SMS messages carried in the year is converted into a messages-per-busyhour rate using similar inputs as the voice calculation. A throughput in messages per second is also calculated this is equal to messages per hour divided by A conversion factor between SMS messages and equivalent voice minutes is also calculated, using estimates of the average SMS length (40 bytes) and the channel rate that SMS is carried by (assumed to be 8 SDCCH per TCH) (Sheet DemCalc, Rows ). Packet data services Demand for data services is converted into a Mbit/s demand driver and an equivalent voice Erlang load using assumptions of: The proportion of traffic occurring in the downlink vs. uplink direction. The amount of additional IP overheads to user data that is required. The channel rate at which the data is carried (13.4kbit/s CS2 for GPRS and 16kbit/s for UMTS). The model also calculates the number of connected and active packet data users (to dimension the SGSN and GGSN network elements which service the packet data demand) using estimates of the proportions of GPRS and UMTS subscriptions which are active/connected (Sheet DemCalc, Rows ). Video services A relatively small volume of video traffic is included in the model. This is converted into BHE and BHCA in exactly the same way as voice traffic, although the model assumes that 4 channels are required per Erlang when video is included in the dimensioning of radio network elements (Sheet DemCalc, Rows ). Routeing factors An input table of routeing factors determines the factor applied to each service volume when calculating the load on the various parts of the network (Sheet DemCalc, Rows , ).

20 NITA s mobile LRAIC model draft v3 cost model Radio network deployment The main assumptions and choices about network design are documented below. Geotypes The model considers four geotypes: dense urban, urban, suburban and rural. These geotypes have been defined using the data submitted by the mobile operators. The rural geotype can be matched closely to the various rural geotypes defined by the operators (e.g. open, woodland, etc.). However, the definitions of non-rural areas differed between the operators. As a result, operator-specific assumptions have been made when transforming information such as traffic proportions from the operator-defined geotypes into the modelled non-rural geotypes. The proportion of area within each of the defined geotypes is shown below in Exhibit 7: Geotype Proportion of area Cumulative proportion Dense urban 0.08% 0.08% Urban 0.83% 0.91% Suburban 3.34% 4.25% Rural 95.75% 100% Exhibit 7: Split of area between geotypes [Source: Analysys] In order to better understand the distribution of the geotypes across Denmark, a MapInfo dataset of Danish postcode areas has been used to assign each postcode to a geotype. This was done by sorting postcode areas in descending order by population density and allocating them to geotypes based on the cumulative proportion of area in the sorted list. The geotypes are distributed across Denmark as shown in Exhibit 8.

21 NITA s mobile LRAIC model draft v3 cost model 18 Exhibit 8: Denmark geotypes by postcode areas for the purpose of the LRAIC model [Source: Analysys] Dense urban Urban Suburban Rural Each operator has supplied data for traffic split by geotype, with is used to populate the relevant traffic distribution percentage input in the model. The definition of the geotypes can be found on the NwDes_operators worksheet (for geographical parameters) and Cov&Dem_In (for traffic distribution calculations). Coverage The coverage networks for each technology (primary GSM, secondary GSM and UMTS) are calculated separately within the model. In order to inform this coverage profile, NITA s mast database was used. This database provides information about the number of active GSM/UMTS BTSs installed in the radio networks of each operator over time. It includes information on: Technology of the BTS (GSM900, GSM1800, or UMTS).

22 NITA s mobile LRAIC model draft v3 cost model 19 Location of the BTS, specified in Danish co-ordinates. Activation date of the site that houses the BTS. The location coordinates allow each BTS to be assigned to a geotype. At any one time, the database can only provide a snapshot of the deployment at the time: it cannot be used to accurately build up a time series, since the activation dates refer to the site, rather than the BTS on that site. The two dates will only coincide when a BTS is deployed on a new site. BTSs using more recent technologies are often deployed on existing sites, so their associated dates in the database will be earlier than the actual date of installation of the BTS. For example, 2G/3G operators have many UMTS BTSs with dates in the database preceding 2000, since they were deployed on sites originally built for GSM and/or NMT. The limitations in the database for each operator and technology are displayed below in Exhibit 9. Operator GSM900 GSM1800 UMTS TDC Sonofon Telia Limitations: overlays of all three technologies on NMT sites, UMTS overlays on GSM sites, GSM1800 overlays on GSM900 sites Can assume no limitations: primary spectrum Limitations: secondary spectrum many overlays on pre-existing sites Limitations: secondary spectrum many overlays on pre-existing sites Can assume no limitations: primary spectrum Limitations: UMTS overlays on GSM sites Limitations: UMTS overlays on GSM sites Hi3G n/a n/a Can assume no limitations: primary spectrum Exhibit 9: Limitations of the mast database in calculating BTS deployments over time [Source: Analysys] NITA was able to provide several versions of the mast database, providing snapshots at various points in the years Consistency checks were carried out on these data sets, and a number of additions and removals of data were made where appropriate, to ensure that Forecasted (but not yet built) BTSs were removed. BTSs with severe information gaps (such as technology and location) were removed if the missing information could not be provided using other versions of the database.

23 NITA s mobile LRAIC model draft v3 cost model 20 BTSs in earlier versions of the data persisted through to the later versions in a consistent way (sometimes BTSs would appear in the data intermittently). After establishing a reasonable level of consistency, a detailed treatment of the BTS deployments for the period was undertaken. Specifically, the number of BTSs was calculated for the mid-year and year-end, broken down by operator, technology and geotype. For the cases where no limitations in the data sets can be assumed (as described in Exhibit 9), an understanding of deployments back to 1992 has also been possible. For the remaining cases, using the date point in the database would result in an over-estimation of the number of BTSs over time. Some operators provided additional databases of their BTSs, which have allowed better historical understanding of their BTS deployments over time. The mast database information was combined with operator-supplied data in order to define the BTS locations by geotype over time. This was in turn combined with cell radii estimates to calculate the coverage profiles over time for each operator. These profiles were checked against operator-supplied coverage estimates. The databases also contained partial information on site identification, allowing BTSs to be grouped together by their site. Where this information was unavailable, the co-ordinates of the BTS was used to ascertain whether the BTS was an overlay or not. Two or more BTSs (from the same operator) are assumed to be co-sited if their coordinates are within 15m of each other. This buffer zone is used to account for Small discrepancies in the BTS location data across the various databases. The fact that BTSs may be listed with slightly different locations, given that they are likely to be separately positioned on the site. For the period covered by the databases ( ), the number of sites by operator, technology and geotype has been calculated for the following categories: GSM900 only. GSM1800 only. GSM900 shared with GSM1800. UMTS only. UMTS shared with GSM900. UMTS shared with GSM1800.

24 NITA s mobile LRAIC model draft v3 cost model 21 UMTS shared with both GSM900 and GSM1800. The definition of coverage by geotype can be found on the NwDes_operators worksheet for each spectrum band. The same sheet also contains the definition of cell radii, as described below. Cell radii Two different types of cell radii are used within the model: theoretical cell radii and effective cell radii. Effective radii are derived from theoretical radii using the process described below. Theoretical cell radii These radii apply to the hexagonal coverage area that it is estimated a BTS of a particular type, considered in isolation, would have. Operators were able to provide some information on the values that these cell radii would take. The model uses a set of theoretical cell radii values which vary by geotype and technology, but not by operator this is because theoretical cell radii differences are considered to be due to differences in radio frequency and geotype (clutter). These were derived by an iterative process, shown below in Exhibit 10.

25 NITA s mobile LRAIC model draft v3 cost model 22 Cell radii data from operators Cell radii estimations (technology, geotype) BTS locations by operator BTS locations (operator, time) Exhibit 10: Process for calibrating the cell radii and deriving area coverage over time [Source: refinement Area coverage data from operators (operator, time) Area coverage (operator, time) comparison Geotype areas Analysys] Calibrated cell radii (technology, geotype) Area coverage (operator, geotype, technology, time) Each operator was able to provide several values for its total geographic coverage for a particular technology at a particular point in time. Using the databases described above, the location of all BTSs for that particular network at that point in time was identified. In order to derive the total geographic coverage of the network, MapInfo was used to construct hexagonal zones of the relevant cell radius (depending on the technology of the BTS and the geotype that it was located in) around each BTS in the network at that time. These hexagonal zones were then grouped together and the total area of this shape was calculated using MapInfo. Importantly, areas of overlap between hexagonal cells were only counted once. An example of such a coverage map is given below in Exhibit 11, with areas of network coverage shown in red.

26 NITA s mobile LRAIC model draft v3 cost model 23 Exhibit 11: Example of a network coverage map generated by MapInfo for a single network at a particular point in time [Source: Analysys] This process was repeated until a set of cell radii were found that gave the closest values for geographic coverage compared with the data provided by the mobile operators. MapInfo was then used again as the central calculation engine to derive the geographic coverage of each network by geotype and over time. Effective cell radii When calculating the number of BTSs required, the LRAIC model does not know the exact location of each BTS across the geotypes. Assuming that BTSs have hexagonal coverage areas means that they can in theory tessellate perfectly (fit together with no overlaps). However, in reality some BTSs are not located optimally with the result that there may be considerable overlap between their individual coverage areas. This concept is demonstrated below in Exhibit 12.

27 NITA s mobile LRAIC model draft v3 cost model 24 Exhibit 12: Illustration of optimal versus suboptimal BTS locations [Source: Analysys] Optimal locations of BTS Sub-optimal locations of BTS occurring in reality The reasons for being unable to locate BTS optimally include: obstructions (woodland, rivers, buildings), a lack of permissible sites to house BTSs in the vicinity, and the site already being occupied by another operator. As a result, once a network has reached coverage in a certain geotype, the cell radii derived using the method described above will be larger than they would be in a real-world network. This can be seen in Exhibit 12, since sites that are sub-optimally located (on the right of the diagram) have less total coverage than would be assumed by a more simplistic model (on the left). In order to explicitly account for this overlapping effect, the model weights the theoretical cell radii by a percentage factor to give effective cell radii. In other words, the model assumes a sub-optimal but realistic placing of BTSs. The factor that is applied is a consequence of the scorched-node methodology used in the model, and is therefore referred to as a scorched-node outdoor coverage coefficient (SNOCC). The value of this coefficient can vary by operator, technology and geotype, but is always less than 1. Effective coverage per site = SNOCC Theoretical coverage per site 2.6 R 2 2 e = SNOCC 2.6 R t Where 2.6 is the hexagonal radius. for a hexagon, R e = effective hexagonal radius, and R t = theoretical

28 NITA s mobile LRAIC model draft v3 cost model 25 The variation of this factor by operator is particularly important, since earlier market entrants usually get first choice of the sites, and later entrants often have to use site locations that are less optimal for their network (e.g. because it is at a different frequency). Operators may also choose the degree to which they fill-in any gaps in outdoor coverage and achieve a more contiguous coverage network. Variation by geotype is also of relevance, since the effect of sub-optimality can be expected to be greater in more urban areas, where BTSs need to be more concentrated due to the smaller cell radii, the higher density of buildings can create greater obstructions, support structures (buildings, chimneys and rooftops) cannot be moved, and the demand for sites is higher. In order to estimate values for the scorched-node coverage coefficient, the model uses the calculations shown in Exhibit 13. Year of interest (operator, geotype, technology) Exhibit 13: Derivation of scorched-node BTS locations (operator, geotype, technology, time) Geographic coverage (operator, geotype, technology, time) Theoretical cell radii (geotype, technology) coverage coefficient [Source: Analysys] Geographic coverage in year of interest (operator, geotype, technology) Number of BTSs (operator, geotype, technology, time) Effective cell radii (operator, geotype, technology) Ratio of effective radius to theoretical radius (operator, geotype, technology) In order to calculate the effective cell radii, the principles that have been used are that: a geotype can only be covered by a BTS lying within that geotype,

29 NITA s mobile LRAIC model draft v3 cost model 26 the year of interest is determined on the basis that if a network has achieved full coverage of a geotype: then the year of interest is taken to be the earliest year in which coverage is achieved, not achieved full coverage of a geotype, but has reached a steady maximal value: then the year of interest is taken to be the first year where that value is reached. This situation could occur because an operator may not fully deploy to a geotype with a particular frequency (especially secondary spectrum), neither achieved full coverage of a geotype nor reached a steady maximal value: then the latest year (2006) is used. Special sites The model considers two types of special sites: indoor sites and tunnel repeaters. Data on these site numbers has been supplied by each operator, and they are modelled on a logical deployment basis. A small proportion of total traffic is assumed to be carried by these sites. These roll-outs are defined in the NwDes.Operators worksheet. Sectorisation and overlay of sites with secondary GSM spectrum Mobile operators in Denmark are subject to coverage requirements for both the GSM900MHz and DCS1800MHz spectrum. However, when determining site numbers, the secondary spectrum may be overlaid upon the primary spectrum site. The proportion of secondary spectrum BTSs which are overlaid upon primary spectrum sites is calculated from operator information in the mast database (see the Coverage subsection above). Macro site types Operators utilise a mix of owned and third-party sites for deploying macro site BTSs and NodeB equipment. Data from the operators indicates that these can be broadly grouped into the following categories: Owned tower sites. Owned monopole sites. Third-party tower sites.

30 NITA s mobile LRAIC model draft v3 cost model 27 Third-party roof-top or other sites. The model considers the proportion of these four types of site deployment in order to capture the different costs associated with site acquisition, civil works and ancillary equipment. These site types are shown in Exhibit 14. Own tower site Own monopole site Third party tower site Third party roof-top site (blue shading denotes own equipment; grey shading denotes third-party assets) Exhibit 14: Site types [Source: Analysys] The proportions of sites falling into these different categories can be found in the NwDes.Operators worksheet. 5.6 Transmission and switching network deployment 2G and 3G backhaul configuration The backhaul configuration is modelled on the basis of the percentage of sites in each geotype which use microwave backhaul (8Mbit/s links which can be filled with up to four 2Mbit/s E1s) or leased-line backhaul (2Mbit/s E1 links). This backhaul configuration is shown in Exhibit 15:

31 NITA s mobile LRAIC model draft v3 cost model 28 Exhibit 15: Backhaul configuration 8Mbit/s microwave (n E1 part filled) n x E1 E1 E1 AN Up to n BTS per AN (AN = access node) [Source: Analysys] E1 n E1 leased lines per site on average BSC Indoor/Tunnel sites 1 x E1 Fibre backbone In addition to the last mile transmission to sites by microwave or leased links, a proportion of sites are connected to access points on the operator s national transmission network. The proportion of sites that are also connected by an access node is estimated from operator data. Access nodes are dimensioned according to a ratio of 24 E1s per node. These assumptions can be found on the NwDes.Selected worksheet. In order to capture the specifics of the Danish networks, a series of fibre transmission rings are modelled across the three main parts of Denmark (Zealand, Funen and Jutland). These fibre rings, illustrated in Exhibit 16 below, carry: Backhaul traffic from the access nodes to the BSC/RNC traffic from remotely sited BSC/RNCs to the main switching sites (MSC/MGW) inter-switch traffic between the main switching sites.

32 NITA s mobile LRAIC model draft v3 cost model 29 Exhibit 16: Diagram of fibre ring deployment in Jutland fibre ring Denmark [Source: Jutland fibre ring Analysys] The red rings indicate the location of the fibre Sealand fibre ring rings Sjaelland fibre ring Fyn fibre ring Fyn fibre ring BSC deployment The number of BSCs is driven by the number of transceivers (TRXs) in the network, using a BSC capacity as supplied by each operator. The inputs associated with this deployment can be found in the NwDes.Operators worksheet. Remote BSCs and associated BSC MSC links The model includes a certain proportion of BSCs that are deployed remotely from an MSC. This proportion is based on operator data. The traffic transiting through these BSCs is backhauled to the MSC using E1 links provisioned over the fibre network. RNC deployment The number of RNCs is driven by the number of NodeBs or the total traffic which is handled by the network. The model is based upon data for RNC capacity as supplied by

33 NITA s mobile LRAIC model draft v3 cost model 30 each operator, in terms of number of NodeBs and traffic capacity. The inputs associated with this deployment can be found in the NwDes.Operators worksheet. MSC/VLR deployment 2G MSCs are dimensioned on the basis of the processing load handled. This load is assessed based on the number of calls, SMSs and location updates of each type that need to be switched. This determines the number of MSC CPUs required. See Section 6.10 for further details. A reference table based on the Danish mobile network structures is used to determine the number of main switching sites (MSC locations) and TSCs based on the number of MSCs deployed in a particular operator s network. The number of MSC locations determines the number of logical and physical links required in the network for inter-switch transmission. Transmission requirements determine the number of E1 port cards required to support transmission to and from the MSCs. Four types of MSC ports are calculated, based on the associated busy hour Erlang loads carried on the respective parts of the network: BSC-facing ports. Interconnection ports. Inter-switch ports. Voic server ports. 3G MSCs are modelled as two units an MSC Server (MSS), and a Media Gateway Switch (MGW). The MSS is dimensioned on the basis of the processing load handled, and this is assessed based on the number of calls, SMSs and location updates of each type that need to be switched. The MGW is dimensioned on the basis of port demand, which is calculated using a similar methodology to the calculation of 2G MSC port numbers. See Section 6.10 for further details. Transit layer The number of required transit switches (TSCs) is calculated on the basis of the MSC reference table. Transit switches are assumed to be required (efficient) once the diversity of

34 NITA s mobile LRAIC model draft v3 cost model 31 the switching network reaches the point that fully-meshing seven MSCs across six MSC sites becomes overly complicated. See Section 6.10 for further details. Backbone network As discussed in the subsection on 2G and 3G backhaul, a configuration of three fibre backbone rings is modelled. These rings are dimensioned according to the inter-switch traffic plus the additional traffic associated with the radio sites and remote BSC/MSCs that are connected directly to the fibre ring. The backbone links are assumed to be deployed in STM-1 increments, based on the number of E1 subunits required by the various transmission types. The length of the rings is estimated on the basis of the Danish geography. Other network elements Also included is an explicit calculation of the remaining significant network element deployments: HLR, network management systems, various IN servers, billing system, VMS, GPRS and SMS infrastructure. Non-network elements The model has been populated with elements representing the major non-network activities of wholesale support services, business overhead services and licence fees.

35 NITA s mobile LRAIC model draft v3 cost model 32 6 Network design algorithms This section details the algorithms used to build up the network. 6.1 Radio network: site coverage requirement The coverage networks for each technology (primary GSM, secondary GSM and UMTS) are calculated separately within the model. The model also calculates the sharing of sites between GSM and UMTS networks, and any new standalone 3G sites required. GSM In Denmark, both 900MHz and 1800MHz spectrum are used for coverage purposes by the GSM operators (TDC, Sonofon and Telia). To satisfy the coverage requirements, the number of macro sites deployed has to be able to provide coverage for a certain area defined for each geotype, which has been calculated for the period using the data provided by the mobile operators. The inputs to the coverage site calculations, based on the chosen GSM operator, are as follows: primary and secondary spectrum total area covered by the mobile operator by technology, geotype and time cell radii for coverage, by geotype and technology scorched node coefficients by geotype and technology, to convert between theoretical and effective cell radii proportion of primary spectrum sites available for overlay, by geotype. The model allows for additional future coverage to be modelled. Exhibit 17 below outlines the model algorithm for the calculation of GSM macro sites deployed.

36 NITA s mobile LRAIC model draft v3 cost model 33 Primary spectrum coverage cell radius (G) % area to be covered by primary spectrum (G, t) Land area km 2 (G) Scorched-node outdoor coverage coefficient (G) Primary spectrum effective coverage cell radius (G) Coverage area km 2 (G, t) Sectors per BTS (G) Hexagonal factor Coverage BTS area km 2 (G) Number of primary BTS for coverage (G, t) Number of primary sectors for coverage (G, t) Number of primary sites for coverage (G, t) Secondary spectrum coverage cell radius (G) % area to be covered by secondary spectrum (G, t) Land area km2 (G) Total coverage sites Scorched-node outdoor coverage coefficient (G) Secondary spectrum effective coverage cell radius (G) Coverage area km 2 (G, t) % of secondary spectrum BTS deployed on primary site (G) Number of primary sites available for overlay (G, t) (G, t) Hexagonal factor Coverage BTS area km2 (G) Number of secondary BTS for coverage (G, t) Number of separate secondary sites required (G, t) Sectors per BTS (G) Number of secondary sectors for coverage (G, t) Tunnel sites (t) Indoor sites (t) (G) = by geotype. (t) = by time Exhibit 17: GSM coverage algorithm for the selected operator [Source: Analysys]

37 NITA s mobile LRAIC model draft v3 cost model 34 The coverage sites for the primary spectrum are calculated first (Sheet NwDes, Rows 9-37). The area covered by a BTS in a particular geotype is calculated using the effective BTS radius. The total area covered in the geotype is divided by this BTS area to determine the number of primary coverage BTSs required (and therefore sites) (Sheet NwDes, Rows 19-29). The number of secondary coverage BTSs are calculated in the same manner as for the primary spectrum (Sheet NwDes, Rows 39-60), but the calculation of the number of sites includes an assumption regarding the proportion of secondary BTSs that are overlaid on the primary sites (Sheet NwDes, Rows 62-86). The remaining secondary BTS require new sites (Sheet NwDes, Rows 76-80). The total numbers of indoor BTSs and tunnel BTSs are modelled as explicit inputs using operator data (Sheet NwDes, Rows ). All sites are assumed to be tri-sectored, except primary spectrum 900MHz coverage sites in some geotypes which are assumed to be (on average) bi-sectored. UMTS The same methodology is used to derive the initial number of coverage NodeBs required for UMTS (Sheet NwDes, Rows , ). This is shown below in Exhibit 18. All UMTS coverage NodeBs are assumed to be tri-sectored. Coverage cell radius for (G) % area to be covered (G, t) Land area km 2 (G) Scorched-node outdoor coverage coefficient (G) Effective coverage cell radius (G) Hexagonal factor Coverage area km 2 (G, t) Sectors per NodeB (G) Coverage NodeB area km 2 (G) Number of NodeB for coverage (G, t) Number of sectors for coverage (G, t) Number of sites for coverage (G, t) (G) = by geotype. (t) = by time Exhibit 18: UMTS coverage NodeB dimensioning [Source: Analysys] Within the UMTS network, however, the effect of cell breathing has been included. Cell breathing takes places in a UMTS network in the situation where traffic loads increase and

38 NITA s mobile LRAIC model draft v3 cost model 35 the subsequent rise in the signal-to-noise ratio acts to curtail the range of the cell usually anticipated to be limited by the uplink communication. The coverage cell radii inputs to the model are estimated (using operator data and a number of link-budget calculations) to be applicable for an uplink load of up to 50% on the cells in the network. Beyond a 50% cell load, the cell radius is estimated to decline using a polynomial approximation, as shown in Exhibit 19 below. Relative cell radius y = x x Exhibit 19: Estimated cell breathing effect [Source: Analysys] % 20% 40% 60% 80% 100% Cell load Radius Max (100%) load Poly. (Radius) The cell load is calculated (by geotype) in the model according to the average number of utilised carriers per sector (Sheet NwDes, Rows ), which is then applied to the polynomial approximation to give the relative cell radius factor. Since the cells are shrinking at the edges, and the uncovered area cannot be uniquely covered by single additional sites in each locality, the relative cell radius factor is squared once, to reflect the area per site, and then squared again to reflect the degree of infill coverage required to cover the hexagonal mesh of uncovered areas (Sheet NwDes, Rows ). In order to avoid a complicated circularity in the model, the cell radius post-cell-breathing is applied to the following year s coverage roll-out calculation (Sheet NwDes, Rows ).

39 NITA s mobile LRAIC model draft v3 cost model 36 Shared or standalone macro sites For 2G network operators, as their 3G network is rolled out 3G macro NodeBs may be added to existing GSM macro sites if the site is suitable (e.g. suitably located with sufficient room/tower space). The proportion of sites which are available for 3G upgrade is specified by an input for each operator. This percentage is multiplied by the number of 2G sites to determine the number of sites available for upgrade (Sheet NwDes, Rows ). 3G sites are then deployed preferentially on these sites first, and thereafter on new, standalone 3G sites (Sheet NwDes, Rows ). Standalone 3G sites are considered as dedicated 3G network costs, whereas sites used by both 2G and 3G radio infrastructure are considered to be shared and therefore recovered from both 2G and 3G volumes. 6.2 Radio network: site capacity requirement (GSM and UMTS) The capacity requirements for each technology (primary GSM, secondary GSM and UMTS) are calculated separately within the model. In all cases, two steps are required, which involve calculating The capacity provided by the coverage sites (Sheet NwDes, Rows , ). The number of additional sites (including secondary spectrum overlays, if available) required to fulfil capacity requirements (Sheet NwDes, Rows , ). However, the differences between GSM and UMTS technologies means that the methodologies require slightly different inputs, as explained below. GSM capacity requirements Step 1: Capacity provided by the sectorised coverage sites Denmark has coverage requirements for both its GSM900 and GSM1800 licences. Section 6.1 explains how the number of coverage BTSs has been derived for the three 2G operators, by geotype, technology and over time. The calculation of the busy-hour Erlang (BHE) capacity provided by the sites deployed for coverage purposes is shown in Exhibit 20.

40 NITA s mobile LRAIC model draft v3 cost model 37 Spectrum MHz (t, 900MHz, 1800MHz) Spectrum channels(t, 900MHz, 1800MHz) MHz per channel (900MHz,1800MHz) Radio blocking probability (t, 900MHz, 1800MHz) Spectral sector capacity (TRX) (t, 900MHz, 1800MHz) Maximum sector re-use (900MHz,1800MHz) Actual sector capacity (TRX) (G, t, 900MHz, 1800MHz) Physical capacity of BTS in TRX (G) Actual sector capacity (Erlang) (G, t, 900MHz, 1800MHz) Erlangs required for a given number of channels (G) Sectors required for coverage (G, 900MHz, 1800MHz) Coverage sector capacity (BHE) (G, t, 900MHz, 1800MHz) Total coverage capacity (BHE) (G, t) Peak TRX utilisation Peak macro BTS utilisation (900MHz,1800MHz) Inputs are broken down by geotype (G), by time (t), or by frequency band Exhibit 20: Calculation of the BHE capacity provided by the coverage network [Source: Analysys] For each GSM operator, the coverage capacity for each technology is calculated separately. For a given technology, before the capacity requirements of the network are calculated, the Erlang capacity for the allocated spectrum is determined. The inputs to this calculation are: Availability of spectrum, spectrum re-use factor, blocking probability, and BTS capacity, in terms of TRXs.

41 NITA s mobile LRAIC model draft v3 cost model 38 The spectral capacity per sector is the number of transceivers that can be deployed per sector given a certain maximum spectrum re-use factor. The lesser of the physical capacity and the spectral capacity of a sector is the applied capacity (Sheet NwDes, Rows ). The sector capacity in Erlangs is obtained using the Erlang B conversion table channel reservations for signalling and GPRS are made in the Erlang B table according to the information provided by the operators. In calculating the effective capacity of each sector in the coverage network, allowance is made for the fact that BTSs and TRXs will in fact be underutilised: Underutilisation of BTSs occurs because it is not possible to deploy the full physical TRX complement in every BTS, since BHE demand does not occur uniformly at a small number of sites. Alternatively, an operator may specifically choose to provide capacity using additional sites rather than additional TRXs. Underutilisation of TRXs occurs because the peak loading of each cell at its busy hour is greater than the network average busy hour. To take this into account, an average-topeak BHE-loading factor of 150% is used in the calculation of TRX utilisation, accounting for the fact that the cell busy hour is 50% greater than the network busy hour. Also, BHE demand does not uniformly occur in a certain number of sectors. This sector capacity (in Erlangs) is then multiplied by the total number of sectors in the coverage network to arrive at the total capacity of the network. Step 2: Calculation of the number of additional sites required to fulfil capacity requirements It is assumed that all the GSM operators only deploy capacity BTSs on new sites, rather than overlaying existing sites. This is based on comparison of the versions of the mast database for the period , which indicate that almost all of the incremental GSM BTSs deployed were on completely new sites, either as single-technology sites or dual sites. The reason for this is likely to be that (respectively): TDC and Sonofon will not overlay on existing coverage sites because their 1800MHz coverage is inside their 900MHz coverage, so they will already have overlaid those sites for 1800MHz coverage reasons in the high-population areas where the new traffic loads will be located.

42 NITA s mobile LRAIC model draft v3 cost model 39 Telia accommodates increasing capacity with 1800MHz and uses 900MHz to extend rural coverage. For this reason, increasing demand is occurring in places (i.e. population centres) where the operator already has 1800MHz sites. Therefore, the additional sites required are calculated to fulfil capacity requirements after the calculation of the capacity of the coverage networks, as shown below in Exhibit 21. Total coverage capacity (BHE) (G, t) Radio BHE (G,t) BHE carried over coverage network (BHE) (G, t) BHE requiring additional radio site capacity (G, t) Peak macro BTS utilisation Additional sites required (G, t) Total capacity BTS (G, t) Actual spectrum capacity (Erlang) (G, t) TRX utilisation Total effective capacity of fully overlaid site (G, t) Average capacity per additional site (G, t) Sectors per BTS (3 for full sectorisation) Proportion of additional sites (G) (G) = by geotype. (t) = by time Exhibit 21: Calculation of the additional sites required to fulfil capacity requirements [Source: Analysys] Three types of GSM site are dimensioned according to the spectrum employed: Primary-only sites. Secondary-only sites. Dual sites. The total BHE demand is aggregated by element and then re-partitioned by geotype. GPRS traffic is currently excluded, on the assumption that it is carried in a channel reservation. Knowing the total capacity of the coverage network allows the determination of the BHE demand that cannot be carried by the coverage network, broken down by geotype Rows ). (Sheet NwDes,

43 NITA s mobile LRAIC model draft v3 cost model 40 Assuming that all new sites are fully sectorised and that both BTSs and TRXs are not fully utilised, the total effective capacity of a fully sectorised BTS for both primary and secondary spectrum is calculated (Sheet NwDes, Rows ). Then, for a selected operator, it is assumed that new GSM sites will be deployed in specific proportions by site type (Sheet NwDes, Rows ). These parameters are used with the effective BTS capacities to calculate the weighted average capacity per additional site by geotype. The total BHE demand not accommodated by the coverage networks is then used, along with this weighted average capacity and the split of new sites by site type, to calculate the number of additional sites by site type and geotype required to accommodate this residual BHE (Sheet NwDes, Rows ). UMTS capacity requirements Step 1: Capacity provided by the sectorised coverage sites Exhibit 22 below demonstrates the methodology used to derive the capacity of the UMTS network.

44 NITA s mobile LRAIC model draft v3 cost model channel elements per channel kit 5 channel kit per carrier per sector, 3 sectors per NodeB Percentage of channels reserved for signalling/soft-handovers Available channel elements per sector (t) Channel elements required per sector (G) Channels available per sector to carry voice/data (G, t) Voice and guaranteed data (BHE) Radio network blocking probability (1%) Erlang B Table Erlang channels available per sector to carry voice/data (G, t) Weighted average BHE channel load (t) BHE traffic split (G) Voice BHE traffic (Erlangs) (G, t) NodeB utilisation Channel kit utilisation BHE traffic supported by coverage network (G, t) Capacity on coverage network (G, t) UMTS coverage BTS (G, t) BHE traffic not supported by coverage network (G, t) (G) = by geotype. (t) = by time Exhibit 22: Calculation of the BHE capacity provided by the UMTS coverage network [Source: Analysys] The following assumptions about specific 3G modelling inputs have been made: 3 sectors per NodeB. 5MHz per UMTS carrier. A maximum physical capacity of 5 channel kit per carrier per sector, across all geotypes- Channel elements are pooled at the NodeB. 16 channel elements per channel kit. 1 channel element required to carry a voice call; 4 to carry a video call. 30% of channel elements are reserved for signalling/soft-handover purposes.

45 NITA s mobile LRAIC model draft v3 cost model 42 The model ensures that all offered traffic voice, data and video is carried with a guarantee of available bandwidth. This represents the situation where delivery of besteffort data traffic is undertaken without compromise to the user s experience of the service during the busy hour. The degree to which operators may allow degradation in packet data service during the busy hour is highly uncertain at the current time, and HSDPA services may be available to deliver down-link traffic more efficiently. However, since it can be anticipated that end users will not accept a significant degradation of the quality of the packet data service in the busy hour, the model assumes that in the network busy hour 3G packet data is carried without a restriction to the offered load. The sector capacity (in Erlangs) is then obtained using the Erlang B conversion table and, using the 3G demand data in BHE calculated by the model, the average BHE channel load is obtained. Operator data has also allowed the model to estimate 3G BHE split by geotype (with indoor traffic calculated separately). The number of UMTS coverage sites calculated earlier in the model is multiplied by the average BHE channel load to derive the capacity in the coverage network by geotype (Sheet NwDes, Rows ). However, as when modelling GSM capacity requirements, allowance is made for the fact that NodeB and channel kit capacity is less than 100% utilised: Underutilisation of NodeBs occurs because it is not possible to deploy the full physical complement of channel kit in every NodeB, since BHE demand does not uniformly exist at a small number of sites. Alternatively, an operator may choose to satisfy capacity load with additional NodeBs rather than additional channel kit for each existing carrier. Underutilisation of channel kit occurs because the peak loading of each cell in its busy hour is greater than the network average busy hour. To take this into account, the same average-to-peak BHE-loading factor of 150% is used in the calculation of the channel kit utilisation, i.e. the cell busy hour is assumed to be 50% greater than the network busy hour. Also, BHE demand does not uniformly occur in a certain number of NodeB sectors.

46 NITA s mobile LRAIC model draft v3 cost model 43 Step 2: Calculation of the number of additional sites required to fulfil capacity requirements Having calculated both the 3G BHE and the capacity of the coverage network by geotype, the BHE that cannot be accommodated by the coverage network by geotype is derived (Sheet NwDes, Rows ), and the number of additional sites calculated, as shown below in Exhibit 23. Capacity on coverage network (G, t) BHE traffic supported by coverage network (G, t) BHE traffic not supported by coverage network (G, t) Capacity on single-carrier coverage network (G, t) BHE traffic that can be supported by additional carrier on coverage sites (G, t) BHE traffic that cannot be supported by an additional carrier on coverage sites (G, t) NodeB utilisation Coverage sites which are overlaid (G, t) Number of additional sites required (G, t) Channel kit utilisation Weighted average BHE channel load (t) Effective capacity of a site with a full overlay (t) (G) = by geotype. (t) = by time Exhibit 23: Calculation of the additional sites required to fulfil capacity requirements [Source: Analysys] This calculation essentially uses a three-stage algorithm: Stage 1: If the 3G BHE in a geotype can be accommodated by the coverage network for that geotype, then no further carriers or sites are added to the network. Stage 2: If the 3G BHE in a geotype cannot be accommodated by the coverage network for that geotype, then another carrier is added to the BTS in that geotype so that the residual 3G BHE can be accommodated.

47 NITA s mobile LRAIC model draft v3 cost model 44 Stage 3: If the proportion in Stage 2 reaches 100% (so every 3G coverage BTS in that geotype has been overlaid with additional carriers) and there is still more 3G BHE in that geotype, then the number of additional sites required in that geotype to accommodate the residual BHE from Stage 1 and Stage 2 is calculated. These additional sites are assumed to be deployed fully overlaid (with 2 carriers used) (Sheet NwDes, Rows ). 6.3 Radio network: TRX requirements To calculate the total number of transceivers required, the inputs required are: BHE traffic. Number of GSM sectors, split between 900MHz and 1800MHz. Transceiver utilisation. Minimum number of TRXs per sector, which is assumed to be 2 in the urban geotypes 1 in the rural geotype 1 or 2 for special sites (indoor and tunnel sites) depending on operator-stated data Blocking probability for the radio network. Exhibit 24 below gives a flow diagram describing the calculation of transceivers required. Total sectors (G, t, 1800MHz, 900MHz) BHE traffic (G, t, 1800MHz, 900MHz) Maximum utilisation of TRX erlang capacity Average BHE traffic per sector (G, t, 1800MHz, 900MHz) Minimum TRX per sector (G, 1800MHz, 900MHz) TRX per sector to meet traffic requirements (G, t, 1800MHz, 900MHz) Radio network blocking probability Total number of TRXs required (G, t, 1800MHz, 900MHz) (G) = by geotype. (t) = by time Exhibit 24: Transceiver deployment [Source: Analysys]

48 NITA s mobile LRAIC model draft v3 cost model 45 The number of TRXs required in each sector to meet the demand is calculated taking into consideration the TRX utilisation, and converting the Erlang demand per sector into a channel requirement using the Erlang B table and the assumed blocking probability. The TRXs for each sector are then calculated (being at least the minimum amount specified above), and then the total number of TRXs required is obtained by multiplying the number of sectors and the number of TRXs per sector (Sheet NwDes, Rows ). 6.4 Backhaul transmission The calculation of the number of backhaul links and the corresponding number of E1 ports required is set out in Exhibit 25 below. Circuits (G,t) E1 utilisation Proportion of sites using microwave (G) E1s per site (G, t) Number of microwave links (2Mbit/s) (G, t) Number of E1s occupied (G, t) Total number of macro sites (G, t) Proportion of sites using leased lines (G) Number of sites using E1 links (G, t) Total number of E1links (G, t) Proportion of sites directly linked to the fibre ring (G) E1s per site (G, t) Number of E1 links connected into Fibre to BSC links Special sites (t) 1 leased E1 per Special site Total number of E1 links required for special sites (t) (G) = by geotype. (t) = by time Exhibit 25: Backhaul calculation [Source: Analysys]

49 NITA s mobile LRAIC model draft v3 cost model 46 Step 1: Capacity requirements The number of E1s required per macro site is calculated to fulfil the capacity requirements for a backhaul link. There are eight channels per transceiver, which translates into eight circuits in the backhaul since the backhaul is dimensioned to support all the TRX channels. If an operator has deployed EDGE in its radio network, the relevant number of reserved TRX channels are multiplied by a factor of four (representing the approximate 4x coding gain achieved with EDGE). Taking into consideration the co-location of primary and secondary BTSs on the same site, the number of channels per site is calculated on the basis of the number of channels per TRX multiplied by the number of 900MHz and 1800MHz TRXs. Given the maximum capacity of an E1 link and considering the link utilisation, the effective capacity per E1 link is calculated. The number of E1 links required per site is then obtained by simply dividing the circuits per site by the actual capacity per E1 link (Sheet NwDes, Rows ). Step 2: Backhaul network design algorithms There are two types of backhaul to be considered in the network: microwave (2Mbit/s links) and leased line backhaul. The percentage of sites which have microwave backhaul is an input into the model. The number of microwave backhaul links (capacity of 8Mbit/s or four E1 equivalents) is set to be a minimum of one per site. The model allows for more than one 2Mbit/s link to be deployed in the microwave link (Sheet NwDes, Rows ). The number of sites using leased lines is calculated as the difference between the total sites and the number of sites using microwaves. The number of E1 leased lines required is obtained by multiplying the total number of macro sites using leased lines by the average number of E1s required per site (from Step 1) (Sheet NwDes, Rows ). A defined proportion of sites are linked to the BSC via the fibre ring network. The capacity of these links is dimensioned according to the average number of E1s per site (by geotype) (Sheet NwDes, Rows ). Special sites (indoor and tunnel sites) are assumed to use only E1 leased-line backhaul and hence are added to the leased-line requirement of the macro layer (Sheet NwDes, Rows ).

50 NITA s mobile LRAIC model draft v3 cost model BSC deployment The structure of the BSC deployment algorithm is set out below in Exhibit 26. Maximum utilisation TRX (G,t) Exhibit 26: BSC deployment BSC capacity in TRX Number of BSC required (G,t) Total number of BSC (G,t) [Source: Analysys] BSC-MSC BHE (G,t) MSC-facing E1 ports per BSC (G,t) Total number of MSCfacing BSC E1 ports (t) (G) = by geotype. (t) = by time Calculation of BSC units The number of BSC units deployed is dependent on the capacity of a BSC, its utilisation and the total number of TRXs required. The number of BSC units deployed must be able to accommodate the number of TRXs deployed (see Section 6.3). Given a maximum capacity of the BSC in terms of TRXs, adjusted for maximum utilisation, the number of BSCs required is calculated (Sheet NwDes, Rows ).

51 NITA s mobile LRAIC model draft v3 cost model 48 Calculation of BSC MSC links Remote BSCs (G,t) Exhibit 27: BSC MSC remote BSC-MSC BHE (G,t) BSC-MSC BHE per remote BSC (G,t) transmission [Source: Analysys] E1 capacity and utilisation Number of E1 links (G,t) (G) = by geotype. (t) = by time A proportion of BSCs are designated remote (i.e. not co-located with an MSC), and therefore require physical links to the MSC. The traffic transiting through these BSCs is backhauled to the MSC using E1 leased lines (on the fibre ring network). The total traffic handled by each remote BSC can be calculated using the total BHE transceiver traffic. The average BHE traffic handled by each remote BSC is converted into a channel requirement using the Erlang table. The number of E1 links is then calculated by dividing this channel requirement by the capacity of an E1 link, adjusted for maximum utilisation. It should be noted that the capacity of the BSC MSC transmission depends on where the transcoder equipment is located. For remote BSCs, the transcoder is assumed to be located in the MSC, and so, according to the GSM standard, has a capacity of 120 circuits. (Sheet NwDes, Rows , ) The number of E1 BSC MSC ports is determined on the basis of the number of BSC MSC E1 links (Sheet NwDes, Row 765). Total outgoing ports for co-located BSCs Given the total number of co-located BSCs and BHE transceiver traffic, the total number of outgoing ports for co-located BSCs is calculated (Sheet NwDes, Rows ). The flow of

52 NITA s mobile LRAIC model draft v3 cost model 49 calculation for co-located BSC ports is similar to that shown in Exhibit 27, except that the transcoder is assumed to be in the BSC (and therefore the E1 capacity is 30 channels) and the co-located links are not modelled (because this is part of the in-building cat-5 or similar wiring). Incoming and outgoing ports The incoming ports to the BSC are ports facing the BTS while the outgoing ports are ports facing the MSC. The diagram below shows the constituents of the incoming and outgoing ports. Incoming ports Outgoing ports Number of occupied E1 units of 8Mbit/s backhaul Number of leased line E1 links Number of E1 for remote BSC-MSC links Number of E1 for colocated BSC-MSC links Total E1 incoming ports Total E1 outgoing ports Exhibit 28: Total incoming and outgoing ports for BSC [Source: Analysys] The total number of E1 incoming ports into a BSC is the sum of the microwave and leased line backhaul links, while the total outgoing ports is the sum of the total number of E1s for both remote and co-located BSCs (Sheet NwDes, Rows ) G NodeB deployment The 3G NodeB deployment algorithm is outlined in Section 6.2.

53 NITA s mobile LRAIC model draft v3 cost model G channel kit and carriers deployment The dimensioning of 3G channel kit is done in a similar manner to the calculation of 2G TRXs (Sheet NwDes, Rows ), with the exception that an allowance is made for soft handover: Total number of UMTS sites (G, t) UMTS BHE traffic per geotype (G, t) Maximum utilisation of CE erlang capacity Average BHE traffic per site (G, t) Minimum CK per site (G) Channel Elements per Channel Kit CK per site to meet traffic requirements including a softhandover allowance (G, t) Radio network blocking probability (1%) Soft-handover allowance Total number of UMTS sites (G, t) Total number of CK required (G, t) CK per site to meet traffic requirements including a softhandover allowance (G, t) CK per carrier per Node B Number of carriers required per Node B Minimum number of carriers per Node B (G) = by geotype. (t) = by time Exhibit 29: 3G channel kit and carrier dimensioning [Source: Analysys]

54 NITA s mobile LRAIC model draft v3 cost model G backhaul deployment 3G backhaul is dimensioned in the same way as 2G backhaul (Sheet NwDes, Rows ). 3G backhaul is assumed to be logically and physically separate from 2G backhaul from the site to the switch G RNC deployment RNCs are dimensioned on the basis of the number of NodeBs per RNC, and the total traffic in the radio network. RNC traffic capacity Traffic BHE RNCs required for CS traffic Utilisation factor Maximum utilisation Number of RNC required to support NodeBs (G,t) Total number of RNC (G,t) RNC capacity in NodeBs NodeBs (G,t) Minimum number of RNC (G) = by geotype. (t) = by time Exhibit 30: RNC dimensioning [Source: Analysys] A minimum number of RNC units are modelled this minimum deployment of 1 or 2 RNCs is based on operator data (Sheet NwDes, Rows ). The number of E1 ports into and out of RNCs is modelled in the same way as for BSC switches (Sheet NwDes, Rows ).

55 NITA s mobile LRAIC model draft v3 cost model G MSC deployment Calculation of number of MSC units to support processing demand To support processing demand, the number of MSC units required is calculated from the CPU capacity, processor utilisation and the demand for MSC processor time. The flow diagram below shows the sequence of the calculation. MSC CPU Capacity MSC Processor Utilisation Total BHms Demand for MSC (t) Required number of processors for BHms demand (t) MSC Processor Capacity MSC Units required to support processor BHms demand (t) (t) = by time Exhibit 31: Calculation of MSC units to support processing demand [Source: Analysys] Taking into account the MSC processor utilisation, the total number of processors required to meet the demand can be calculated as the total number of busy-hour milliseconds (BHms) divided by the effective MSC capacity (Sheet NwDes, Rows ). Calculation of TSCs, MSC locations, logical links and physical links TSCs, MSC locations, logical links and physical links are all calculated by means of a reference table based on the number of MSCs deployed in an operator s network. This reference table shown in Exhibit 32 below is based directly on operator s submitted data, and is specific to the Danish network topology (Sheet NwDes, Rows ). The number of MSC locations is obtained by averaging the deployment for all operators. A transit layer of 2 TSC switches is assumed to be required when the number of MSCs reaches 7 in order to reduce the complexity of the logical transmission layout.

56 NITA s mobile LRAIC model draft v3 cost model 53 # MSC # MSC locations # TSC # Logical E1 routes # Physical routes # Rings Physical routes by ring Sjealland Fyn Jutland Distribution of E1 per ring Sjealland 0% 0% 0% 0% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% 50% Fyn 0% 0% 100% 50% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% Jutland 0% 0% 0% 50% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% 25% Ring length (km) Sjealland 50 Fyn 600 Jutland 400 Exhibit 32: Core network reference table [Source: Analysys]

57 NITA s mobile LRAIC model draft v3 cost model 54 The calculation of the number of logical links that are required is based on the fully-meshed formula n(n-1)/2 where n is the number of MSC locations. This is shown in Exhibit Exhibit 33: Logical route dimensioning of the 0 logical routes 2 6 logical routes backbone [Source: Analysys] logical routes 10 logical routes logical routes When dimensioning physical routes, a topology of three linking fibre rings is used, with rings deployed on each of the three main parts of Denmark (see Exhibit 16 on page 5 above). The topology modelled is based on information sourced from each operator. The model always deploys the three fibre rings, although there may be zero or one MSC MSC route in which case the fibre rings serve the sole purpose of backhauling site and BSC/RNC traffic back to the main switching centre(s). Based on this three-ring architecture, the number of physical links can be determined, as shown in Exhibit 34 below.

58 NITA s mobile LRAIC model draft v3 cost model 55 Exhibit Physical route dimensioning of the 0 physical routes 2 6 physical routes 4 backbone [Source: Analysys] physical routes 2 7 physical routes physical routes physical routes 7 Given that Copenhagen is on Zealand, the model assumes that a higher proportion of the E1 inter-switch links are located on the Zealand fibre ring. The remaining E1 links are divided equally between the Funen and Jutland fibre rings. This is shown in Exhibit 32 above. Calculation of BSC-facing, interconnect-facing, VMS-facing and core-facing ports Exhibit 35 below shows how the number of incoming and outgoing ports is obtained.

59 NITA s mobile LRAIC model draft v3 cost model 56 Incoming ports Interconnect infrastructure VMS ports Total number of outgoing E1 ports from BSCs (t) Interconnection BHE traffic (t) Voic BHE traffic (t) MSC locations (t) Interconnection traffic per MSC location Erlang table channel calculation Voic traffic (channels) (t) Total number of incoming E1 ports from BSCs (t) Erlang table channel calculation Interconnection traffic per MSC location (channels) (t) Port utilisation VMS ports (E1s) (t) Interconnection port utilisation E1 capacity (circuits) Interconnection ports per location (E1s) (t) E1 capacity (circuits) MSC locations (t) Number of interconnection- facing E1 ports required (t) (t) = by time Exhibit 35: Calculation of BSC-facing, interconnect-facing and VMS-facing ports [Source: Analysys] The total number of incoming ports in the MSC is simply taken as the total number of E1 outgoing ports from the BSC (Sheet NwDes, Rows ). The total number of outgoing ports comprises the number of interconnect-facing ports required, the number of VMS-facing ports required (both shown conceptually in Exhibit 35 above), plus the number of inter-switch ports required. For the interconnection infrastructure, the total number of interconnect-facing ports required to meet demand is obtained by dividing the interconnection BHE traffic at each MSC location (as a channel requirement) by the actual E1 capacity of the port Rows ). (Sheet NwDes, Inter-switch links are dimensioned on the basis of the BHE inter-switch traffic per logical route (the number of which is determined according to the MSC reference table) Rows ). (Sheet NwDes,

60 NITA s mobile LRAIC model draft v3 cost model Calculation of length of backbone links The length of the backbone ring network is determined on the basis of the inter-switch physical routes refer to Exhibit 34 for the dimensioning of these routes on the basis of MSC locations. As discussed previously, the model assumes that a higher proportion of the E1 inter-switch links are on the Zealand fibre ring, with the remainder divided between the Funen and Jutland fibre rings on the basis of the number of physical links dimensioned. The backbone is dimensioned in terms of STM-1 links, where one STM-1 link contains 63 E1 links, subject to a maximum utilisation factor. An average route length per physical route is calculated in order to determine the backbone link length required and the number of links (Sheet NwDes, Rows ) Transit layer deployment The deployment of a transit layer is determined according to the MSC reference table outlined in Exhibit 32. Two TSC units are deployed when at least 7 MSCs (deployed in 6 MSC locations) are deployed in the network. By deploying a transit layer, the number of logical links that are required is reduced compared to a fully-meshed network, e.g. the network is split into two sets of fully-meshed linkages (linked through the TSCs). This is shown in Exhibit 36 for the case of MSCs in seven locations with two TSCs. MSC location TSC Exhibit 36: Two-mesh linking for transit layer [Source: Analysys] 7 locations mesh 1 mesh 2 6 logical routes 10 logical routes

61 NITA s mobile LRAIC model draft v3 cost model G MSS and MGW deployment The 3G MSC is modelled as being composed of two separate components: the MSS, which is dimensioned on the processing load, and the MGW, which is dimensioned on the basis of ports. These separate calculations are built up in the same way as for the 2G MSC (Sheet NwDes, Rows ) Deployment of other network elements HLR HLR units are deployed based on registered subscribers. The diagram below shows the calculations used to obtain the number of HLR units required. HLR Utilisation Exhibit 37: HLR units calculation [Source: Analysys] HLR Capacity Actual HLR Capacity Registered subs (t) HLR required to support registered subscribers (t) Minimum HLR required Number of HLR units required (t) (t) = by time A minimum number of HLR units are deployed from the start of operations. HLR units have an associated capacity as provided by each operator and a maximum utilisation (Sheet NwDes, Rows ).

62 NITA s mobile LRAIC model draft v3 cost model 59 SMSC The SMSC deployment is driven by SMS throughput demand. The diagram below shows the calculation flow. SMSC Utilisation Exhibit 38: Calculation of SMSC SMSC Throughput Capacity Actual SMSC Capacity units [Source: Analysys] SMS Throughput Demand (t) SMSCs required to support thoughput demand (t) Minimum SMSC units Number of SMSC units required (t) (t) = by time Dividing the SMS throughput demand by the actual SMSC capacity gives the number of SMSCs required to support this throughput demand. The number of SMSC units deployed is the higher of either the SMSCs required to support demand or the minimum SMSC units (Sheet NwDes, Rows ). GPRS/EDGE/UMTS packet data infrastructure There are three packet data infrastructures deployed, namely PCU, SGSN and GGSN. PCU units are added to the GSM BSCs to groom packet data to/from the radio transmission. A certain number of PCUs are deployed per BSC. It is assumed that the UMTS RNC intrinsically contains PCU functionality (Sheet NwDes, Rows 1441:1469). The exhibit below shows the calculations for SGSN and GGSN deployment, supporting connective and active packet data subscribers of both 2G and 3G networks.

63 NITA s mobile LRAIC model draft v3 cost model 60 SGSN/GGSN Utilisation Exhibit 39: SGSN and GGSN SGSN/GGSN Capacity Actual SGSN/GGSN Capacity units calculation [Source: Analysys] Connected subscribers/active PDP contexts in the busy hour (t) SGSNs/GGSNs required to support BH connected subs/pdp contexts (t) Minimum SGSN/GGSN units Number of SGSN/GGSN units required (t) (t) = by time The calculations for both SGSN and GGSN deployment are similar. SGSN deployment is driven by the number of simultaneously connected subscribers in the busy hour (Sheet NwDes, Rows 1457), while GGSN deployment is driven by active PDP contexts made in the busy hour (Sheet NwDes, Rows 1468). A minimum number of SGSNs and GGSNs must be deployed (one or two, depending on operator data). Network management centre The network management centre is deployed at the start of operations (Sheet NwDes, Rows 1477). Voic system, IN and billing system These network elements are modelled as a single functional unit deployed at the commencement of operations (Sheet NwDes, Rows 1479:1484). Non-network elements Major categories of non-network activities are also modelled: Wholesale The costs relating to the support of wholesale services is modelled on the basis of the number of wholesale events carried by the

64 NITA s mobile LRAIC model draft v3 cost model 61 overheads network. Wholesale events are considered to be the sum of: incoming minutes from other networks outgoing minutes from other networks incoming SMS messages from other networks outgoing SMS messages from other networks national roaming minutes carried by own, or other networks. Wholesale overheads are assumed to be operating expenditures only. Business overhead activities Business overhead activities include the head office, IT, personnel, administrative support and executive management functions of the business. These activities may incur both capital and operating expenditures, though the approach of each operator in capitalising or expensing its business overhead expenditures varies according to how the operator has chosen to deploy its mobile function in Denmark. As such, the model allows for the following business overhead expenditures: one-off capital expenditure required to establish the head office buildings and basic facilities ongoing capital expenditure required to maintain and expand the head office facilities, fixtures and fittings; modelled approximately according to the number of subscribers supported by the business fixed annual operating expenditure of the fixed business overhead functions of building rental and running costs, business overhead staff salaries and executive management costs increasing annual operating expenditure of the expanding business overhead support functions (facilities and salary related costs); modelled approximately according to the number of subscribers supported by the business.

65 NITA s mobile LRAIC model draft v3 cost model 62 2G licence fees 3G licence fees Some operators specify 2G licence fees (annual operating expenditures), which are modelled as a fixed annual expenditure. The model includes the capital asset of the 3G licence fee. The expenditure profile of this licence fee is modelled as follows: 25% in year of purchase 7.5% per year for the following 10 years. The operators actual licence fees are applied in the model: DKK950 million in 2001 for TDC, Telia and Hi3G, inflated to DKK1042 million expressed in 2006 currency terms DKK533 million in 2006 for Sonofon.

66 NITA s mobile LRAIC model draft v3 cost model 63 7 Expenditure calculations Once the requirement for network assets over time has been calculated over time (Sheet NwDeploy, Rows 9+), the model must compute the purchasing, replacement, retirement and expenditures associated with these network elements. 7.1 Purchasing, replacement, and capex planning periods The network design algorithms compute the network elements that are required to support a given demand in each year (assessed at the year-average point). The network deployment scheduled is smoothed with respect to demand up to the peak asset deployment number, to remove any transient dips in the profile of assets needed over time (Sheet NwDeploy, Rows 315+). In order for network elements to be operational when needed, they need to be purchased in advance (Sheet NwDeploy, Rows 785+), in order to allow provisioning, installation, configuration and testing before they are activated. This is modelled for each asset by inputting a planning period of between zero (no planning required) and 24 months. This concept of a look-ahead period is illustrated in Exhibit 40. Deployment Demand requirement (t) subject to max utilisation Look-ahead period Time Ordering Purchasing Deployment Testing Activation Purchase requirement subject to look-ahead Exhibit 40: Look-ahead period for asset purchase [Source: Analysys] In order to calculate the number of assets to be purchased in each year, the model computes the number of additional assets that need to be installed to provide incremental capacity,

67 NITA s mobile LRAIC model draft v3 cost model 64 and also includes the amount of equipment that has reached the end of its lifetime and needs to be replaced (Sheet NwDeploy, Rows 630+). The average accounting lifetime of network elements has been calculated by taking into consideration the information submitted by the mobile operators on the depreciation periods applied to their network elements. In addition, an economic asset lifetime has been estimated by Analysys and NITA, taking into account the expectations of asset replacement under economic rather than accounting circumstances. 7.2 Retirement algorithm When the demand for an asset is reduced, it can either be removed from the network, or retained. An algorithm is used to model how particular assets are to be retired (Sheet NwDeploy, Rows 469+). There will be a period of delay between the point at which the demand reduction occurs, and the point at which the asset is decommissioned. This delay can vary from zero (the asset is retired in the same year that the demand reduction occurs) up to 100 years (the asset remains in the network until the end of the network s lifetime), as shown in the following exhibits. Retirement delay period (yr) Explanation 0 Asset numbers reduce directly in the year that demand reduction occurs 1 Asset reduction lags demand reduction by 1 year 2 Asset reduction lags demand reduction by 2 year 100 Assets are maintained in the network until the end of the network Exhibit 41: Values used for the retirement delay period [Source: Analysys]

68 NITA s mobile LRAIC model draft v3 cost model 65 Deployment t=1 t=2 t=100 Exhibit 42: Retirement algorithm options [Source: Analysys] Actual requirement according to demand Time The retirement algorithm is built into the model because there are various reasons why assets may not be removed perfectly from the network with reducing demand such as uncertainty over migrating volumes, or requirements to maintain network quality for remaining subscribers. 7.3 Equipment unit prices The model includes a schedule of capital and operating expenditures for each network element (Sheet CostScenario.Basecase), along with a price trend which reflects the price of modern equivalent assets over time (Sheet CostTrends). This price evolution also provides an important input into the economic depreciation calculation, as explained in Section 8. Capital and operating expenditures relevant to each network element in the model are derived from the input of unit price (in real 2006 DKK) and the price trend applying from 1992 onwards. The input of unit price consists of a number of components, which can generally be considered to be broadly similar (though not identical) for each network operator. Some distinct inputs exist, for example, where detailed operator data is unavailable or there are specific differences in the operators network architecture: Direct capital expenditure The direct capital expenditure for a network element reflects the list price to purchase and install one unit of equipment. These inputs have been estimated from two main sources:

69 NITA s mobile LRAIC model draft v3 cost model 66 bottom-up price lists provided by a number of the mobile operators (e.g. from internal budget planning, vendor estimates or other internal bottom-up operator data) Analysys estimates. In addition, a small number of bottom-up equipment prices have been estimated by direct comparisons with top-down data. Indirect capital expenditure The indirect capital expenditure for each network element represents the share of other capitalised costs associated with network deployment: installation capital, tools, testing, vehicles, network facilities, etc. The additional indirect capital expenditure associated with each network element category is identified by observing the discrepancies (if any) between actual top-down expenditures and the sum of bottom-up direct capital expenditures. The indirect capital expenditure allowance is added as a percentage to the direct expenditure. Operating expenditures for certain (direct) network elements The operating expenditures associated with the direct costs of certain network facilities are modelled as an input in DKK terms. The specific network facilities considered in this manner are: radio site rental backhaul leased E1 transmission links backbone leased/self-managed STM1 transmission kilometres wholesale overhead cost per wholesale event annual and per-subscriber business overhead expenditure 2G licence fees. However, the majority of these direct cost inputs are derived from the actual top-down operating expenditures of each network operator.

70 NITA s mobile LRAIC model draft v3 cost model 67 Operating expenditures as a percentage of capital expenditure for various (indirect) assets The remainder of the network element operating expenditures are estimated from top-down data on the basis of a percentage of capital expenditure per unit. This opex input is specified according to the 1992 capex values, although in subsequent years operating expenditure per unit is calculated according to the opex price trend.

71 NITA s mobile LRAIC model draft v3 cost model 68 8 Annualisation of expenditure This section describes the implementation of the economical depreciation algorithm used in NITA s mobile cost model. It details both the economic rationale for using this algorithm and the calculation steps. Further discussion of the appropriate mark-up mechanism can be found in the model principles document. 8.1 The rationale for using economic depreciation Economic depreciation is a method for determining a cost recovery that is economically rational, in that it: Reflects the underlying costs of production, and reflects the output of network elements over their lifetime. The first factor relates the cost recovery to that of a new entrant to the market, which would be able to offer the services based on the current costs of production. The second factor relates the cost recovery to the lifetime of a mobile business in that investments and other expenditures are in reality made throughout the life of the business (especially large, up-front investments) on the basis of being able to recover them from all demand occurring in the lifetime of the business. New entrants to the market would also be required to make these large upfront investments, and recover costs over the lifetime in a similar fashion to the existing operators. (This is based on the realistic assumption that new entrants to the market face the same systemic barriers to entry as were faced by the existing operators, and would not be able to instantaneously capture the entire market of an operator, i.e. the market is less than fully contestable). These two factors are not reflected in accounting-based depreciation, which simply considers when an asset was bought, and over what period the investment costs of the asset should be depreciated. Fundamentally, the implementation of economic depreciation utilised in the model is based on the principle that all (efficiently) incurred costs should be fully recovered, in an economically rational way. An allowance for capital return earned over the lifetime of the

72 NITA s mobile LRAIC model draft v3 cost model 69 business, specified by the weighted average cost of capital (WACC), is also included in the resulting costs. 8.2 Implementation of economic depreciation principles The economic depreciation algorithm recovers all efficiently incurred costs in an economically rational way by ensuring that the total of the revenues generated across the lifetime of the business are equal to the efficiently incurred costs, including cost of capital, in PV terms. More specifically, for every asset class, in every year, the algorithm recovers the proportion of total cost (incurred across the lifetime of the business) that is equal to the revenue generated in that year as a proportion of the total revenue generated (across the lifetime of the business) in PV terms. PV calculation The calculation of the cost recovered through revenues generated needs to reflect the value associated with the opportunity cost of deferring expenditure or revenue to a later period. This is accounted for by the application of a discount factor on future cash flow, which is equal to the WACC of the modelled operator. The business is assumed to be operating in perpetuity, and investment decisions are made on this basis. This means that it is not necessary to recover investments within a particular time horizon, for example the lifetime of a particular asset, but rather throughout the lifetime of the business. In the model, this situation is approximated by explicitly modelling a period of 50 years. At the discount rate applied, the PV of one DKK in the last year of the model is fractional and thus any perpetuity value beyond 50 years is regarded as immaterial to the final result. Cost recovery profile The costs incurred over the lifetime of the network are recovered in line with the revenues generated by the business. The revenues generated by an asset class are the product of the demand (or output) supported by that asset class, and the price per unit demand.

73 NITA s mobile LRAIC model draft v3 cost model 70 In the modelled environment of a competitive market, the price that will be charged per unit demand is a function of the lowest cost of supporting that unit of demand, and thus the price will change in accordance with the costs of the factors of production. Put another way, if a low-cost asset could support a particular service, then the price charged for the same service supported by a more expensive asset would be reflective of the costs of the lower-cost asset if not, a competitor would supply the service using the lower-cost asset in order to capture the associated supernormal profits. The shape of the revenue line (or cost recovery profile) for each asset class is thus the product of the demand supported (or output) of the asset, and the profile of replacement cost (or modern equivalent asset price trend) for that asset class. Capital and operating expenditure The efficient expenditure of the operator comprises all the efficient cash outflows over the lifetime of the business, meaning that capital and operating expenditures are not differentiated for the purposes of cost recovery. As stated previously, the model considers that the costs incurred across the lifetime of the business are recovered by revenues across the same period. Applying this principle to capital and operating expenditure leads to the conclusion that they should both be treated in the same way since they both contribute to supporting the revenues generated across the lifetime of the operator. Price trends for capital and operating components are likely to vary, however. Technology-specific assets versus those with shared technology A number of network assets are identified as specific to GSM or UMTS, and are assumed to be incompatible with the network services provided using the other technology. For example, TRXs cannot support W-CDMA radio signals. The total costs of this type of assets are recovered from an output profile, which considers only the specific GSM or UMTS network volumes. Assets which are not technology-specific are assumed to serve the same purpose in the GSM and UMTS networks such as a switching site or backbone transmission. The total costs of this type of assets, including all ongoing replacements, are recovered from a

74 NITA s mobile LRAIC model draft v3 cost model 71 profile of demand which sums up GSM and UMTS volumes according to the various routeing factors applicable to each service. 8.3 Implementation details The economic depreciation algorithm appears in the worksheet EconDep. The depreciation method implemented in the model (Sheet EconDep, Rows 8+) has the following characteristics: It explicitly calculates the recovery of all costs incurred across the specified time horizon (50 years), in PV terms (Sheet EconDep, Row 3). The cost recovery schedule is computed for each asset along the output profile of the asset. Cost recovery is computed separately for capital (Sheet Com.Incr, Rows 8+) and operating expenditures (Sheet Com.Incr, Rows 162+) (allowing for potentially different MEA price trends of capex and opex). Costs are calculated with reference to network element output the annual sum of service demand produced by the network element (weighted according to the routeing factor) (Sheet NwEle.Out).

75 NITA s mobile LRAIC model draft v3 cost model 72 9 Service cost calculations The model takes the total economic costs for each network asset, and applies a common cost proportion to that asset class. The proportion of each asset class (cost) that is common is calculated from the input of the number of common assets (Sheet Com.Incr, Rows 468+). Common costs are summed across assets to calculate a total common cost amount (Sheet Com.Incr, Rows 775+ and Rows ). Residual incremental costs per unit output are calculated for each asset class (Sheet Com.Incr, Rows 930+). Network common costs are defined as follows, representing the minimum radio network deployment in the absence of traffic. 1 Core switching deployments are considered costs that are overall incremental to the traffic volume carried: primary 2G spectrum outdoor coverage macro sites plus additional macro sites for 3G outdoor voice coverage. Special/tunnel sites a primary spectrum BTS for each outdoor coverage site a NodeB for each 3G outdoor voice coverage site one TRX per sector for primary spectrum coverage sites one CK per NodeB a backhaul link for each of these sites the network management system 2G and 3G licence fees. The assets are defined as being either 2G assets, 3G assets or shared assets; with common and incremental components calculated for each (Sheet Com.Incr, Rows ). Routeing factors determine the amount of each element s output required to provide each service. In order to calculate incremental service costs, incremental unit output costs are therefore multiplied by the routeing factors according to the following equation: Cost( Servicek ) cost _ per _ unit _ output( asseti) RouteingFactor( asseti, servicek ) assets 1 Indoor coverage is consequently treated as incremental to traffic

76 NITA s mobile LRAIC model draft v3 cost model 73 The routeing factors are defined as average traffic routeing factors: the incremental costs of traffic are shared between all traffic services using a measure of average traffic utilisation per unit of service demand. This method allocates incremental costs between voice and data services on the basis of a measure of traffic equivalence. The most significant categories of network costs are radio site, BTS and backhaul transmission costs (together approximately 75% of network costs). These cost items are allocated using traffic equivalent routeing factors representing the occupancy of channels by each unit of the various services 2, as follows: Service Incoming and outgoing minutes On-net minutes SMS messages GPRS Mbytes (total user data conveyed) Incoming to VMS deposit On-net to VMS deposit, on-net to VMS retrieval Incoming and outgoing 3G video minutes On-net 3G video minutes 3G packet data (Release 99) ON national roaming minutes LRAIC loading equivalent to 1 minute of traffic in the radio layer 1+ringing time per minute 2+2 ringing time per minute 1150 SMS messages equivalent to 1 minute of voice 123kB equivalent to 1 minute of voice ringing time per minute 1+ ringing time per minute 4 per minute 8 per minute 150kB equivalent to 1 minute 1+ ringing time per minute Exhibit 43: LRAIC equivalent loading for network channels [Source: Analysys] This disaggregation of total economic costs is show in Exhibit 44 below. 2 The costs of these network elements are not according to any dedicated channel reservations. This is because we do not consider channel reservation cost allocation consistent with the LRAIC methodology, which we instead interpret as the average usage of the (traffic incremental) network by each unit of demand.

77 NITA s mobile LRAIC model draft v3 cost model 74 Dedicated 2G assets Incremental Applicable to 2G only services Dedicated 2G assets - common Shared assets Incremental Dedicated 3G assets Incremental Applicable to 3G only services Dedicated 3G assets - common Applicable to 2G and 3G services Shared assets - common Retail incremental and common costs Exhibit 44: Economic cost structure [Source: Analysys] Business overhead common costs This cost structure gives rise to four equi-proportional mark-up calculations, applied sequentially as shown in Exhibit 45 (Sheet Com.Incr, Rows 1222 to 1391). Exhibit 45: Mark-up sequence [Source: Analysys] 2G 3G shared overheads The addition of the mark-ups results in a total cost per unit of demand, for each service (Sheet Com.Incr, Rows 1357+). The Results sheet of the model includes checks of the PV of cost recovered (rows 7-13) to ensure that all incurred expenditures are flowing through to the marked-up service costs. The mark-up for business overheads between network and retail activities is estimated outside of the model to be 50% for network and 50% for retail rather than encoding all the various retail costs in the model in order to endogenously calculate the percentage allocation outcome.

78 NITA s mobile LRAIC model draft v3 cost model Glossary of abbreviations used 2G 3G AN BHCA BHE BSC BTS CK CPU E1 GGSN GMSC GPRS GSM GSN HCA HLR IN IP LRAIC MGW MSC NMS NR PDP PCU PV RNC SDCCH SGSN SIM SMS SMSC SNOCC STM-1 TCH second generation of mobile telephony third generation of mobile telephony access node busy hour call attempts busy hour Erlangs base station controller base transmitter station or base station channel kit central processing unit 2Mbit/s unit of capacity gateway GPRS serving node GPRS MSC general packet radio system global system for mobile communications gateway serving node historic cost accounting home location register intelligent network Internet protocol long-run average incremental costing media gateway switch mobile switching centre network management system national roaming packet data protocol packet control unit present value radio network controller stand-alone dedicated control channel subscriber GPRS serving node subscriber interface module short message service SMS centre scorched-node outdoor coverage coefficient 155Mbit/s synchronous transport module traffic channel

79 NITA s mobile LRAIC model draft v3 cost model 76 TRX TSC UMTS VMS WACC transceiver unit transit switch universal mobile telecommunications systems voic system weighted average cost of capital

80 Annex A: Draft v3 cost model for TDC See separate file

81 Annex B: Draft v3 cost model for Sonofon See separate file

82 Annex C: Draft v3 cost model for Telia See separate file

83 Annex D: Draft v3 cost model for Hi3G See separate file

84 Annex E: Cost of capital As described in the conceptual approach to the LRAIC model development, the CAPM and WACC methods are used for the calculation of the cost of capital for the mobile operators. The cost of capital is to be calculated under two different situations: the cost of capital for an efficient supplier of mobile services in Denmark the cost of capital for each actual operator in Denmark reflecting any differing characteristics from the first calculation. In this annex, the parameters used in the calculation of the WACC are described. E.1 Calculation The cost model will require a cost of capital (WACC) to be specified. Pre-tax weighted average cost of capital is calculated as follows: WACC C d D D E C e E D E Where: C is the cost of debt d C is the pre-tax cost of equity e D is the value of the operator s debt E is the value of the operator s equity Since these parameters, or estimates of them, are most readily available in nominal form, we calculate the nominal pre-tax WACC and convert it to real 3 pre-tax WACC, as follows: Real pre - tax WACC Nominal pre - tax WACC (1 CPI ) 3 We have found it more transparent to construct real-terms bottom-up mobile LRIC models. Either method requires a CPI to be specified (either within the price trends, or the WACC).

85 Annex E: Cost of capital E-2 In the calculation shown above, CPI is the rate of inflation as measured by the Consumer Price Index. In the following sub-sections we discuss the assumptions behind each of the parameters in this calculation. E.1.1 Cost of debt C d ( 1 T ) ( R f RD ) is the cost of debt, where R f is the risk-free rate, R D is the company s debt premium and T is the corporate tax rate. The corporate tax rate is the rate that is applicable to the forward-looking business of the mobile operators in Denmark. The debt premium that must be offered by a company specifies the rate above the risk-free rate which debt providers of the company are offered in return for debt funding. Typically, the debt premium varies with the gearing of the company for a higher proportion of debt funding, a greater debt premium must be offered. This higher premium accounts for the greater financial risk borne by debt providers and the requirement to fund interest payments out of cashflows. E.1.2 Cost of equity We calculate the cost of equity using the capital asset pricing model (CAPM) as follows: C e R f R e Where: R is risk-free rate of return f R e is the equity risk premium is a measure of how risky a particular company or sector is relative to the national economy as a whole. Each of these parameters is now discussed in turn.

86 Annex E: Cost of capital E-3 Risk-free rate of return, R f The risk-free rate of return is usually taken as that of a long-term government bond. In NITA s prior work on WACC, a ten-year government bond has been used. Equity risk premium, R e Equity risk premium is the increase over the risk-free rate of return that investors demand from equity. Usually, companies listed on the national stock market are taken as the sample over which this average is calculated. Beta for mobile operators, An accurate empirical determination of requires very large amounts of historical data. It is therefore an area of considerable subjectivity. Only in the US, and perhaps in a few other countries with very large stock markets and long histories, have estimates of been practicable. However, given that represents the risk of a particular industry or company relative to the market as a whole, one would expect the of a particular type of company in this case a mobile phone company to be similar across different countries. Comparing in this manner requires an un-levered (asset) rather than a levered (equity) : asset = equity / (1+D/E) The ERG report on WACC 4 provides a European selection of asset ranging from 0.80 to E.1.3 Debt/equity (D/E) ratio Finally, it is necessary to define a funding structure for the market player, based upon an estimate of the (optimal) proportion of debt and equity in the business. NITA aims to establish a target gearing for this part of the calculation. 4

87 Annex E: Cost of capital E-4 E.2 Sensitivity of the cost of capital to varying the input parameters In constructing a WACC calculation it is necessary to specify the gearing of the company (its proportion of debt compared to equity funding) in order to weight the relative costs of debt and equity. The gearing of the company then also influences the calculation of the equity, which specifies the rate return required on the equity side, and the debt premium, which specifies the rate of return on the debt side. Equity returns are provided post-tax and debt returns are provided pre-tax, therefore in calculating the pre-tax weighted average cost of capital of a typical mobile operator it can be shown that the cost of capital is broadly insensitive to the gearing input: With a higher gearing, a greater proportion of the cost of capital is due to debt returns at a lower rate than equity returns. However, with a higher gearing the debt premium and equity also increases. These increases broadly counteract the benefit of sourcing a greater proportion of funding from (lower cost) debt, and this is otherwise known as the Miller-Modiglani hypothesis. As such, the level of the cost of capital is most strongly affected by the input of asset. E.3 Application to Denmark Risk-free rate of return, R f The effective interest rate on a government bond with duration of ten years has been used as an estimate for the forward-looking nominal risk-free interest. The effective interest rate for the bond is estimated as the average of the nominal rate of return for a ten-year government bond for the 24 month period March 2006 to February 2008 of 4.11%. 5 Equity risk premium, R e As it is more risky to invest in stocks (equity) than invest in the risk-free government bonds, investors demand a risk premium when investing in stocks. In 2002, NITA used an 5 Source: Statistics Denmark, series: DNRENTM, Bond Yields, Central Government (bullet issues) 10 years

88 Annex E: Cost of capital E-5 equity risk premium of 3.75%. 6 This choice was made by evaluating seven different studies of the Danish risk premium using forward-looking as well as historical approaches that applied arithmetical as well as geometrical averages based on time periods of years. The ERG report on WACC 7 shows that European regulators use an equity risk premium that is between 3.75% and 7.20%. The most recent study 8 of investment returns over the 101 years from shows that the equity risk premium for Denmark is 2.0% (geometric mean) and 3.3% (arithmetic mean), and for the world it is 4.6% (geometric mean) and 5.6% (arithmetic mean). Furthermore, the study estimates that the forwardlooking risk premium for the world is 3% (geometric mean) and a little below 4% (arithmetic mean). Furthermore, NITA has noted that, in 2005, the Danish Energy Regulatory Authority (DERA) found it to be true and fair to use a premium of 3.75% as part of the regulation of the gas transmission and distribution networks. 9 NITA therefore considers it to be appropriate that the equity risk premium should remain at 3.75%. Tax rate, T The Danish corporate tax rate of 25% should be applied in the cost of capital calculation Source: NITA, Report on the Hybrid Model, August Dimson, Marsh and Staunton (2002): Triumph of the optimists: 101 years of investment returns, Princeton University Press, Princeton, New Jersey and Oxford. DERA s decission from 29 August 2005: Indtægtsrammeregulering af naturgasdistributionsselskaberne fastsættelsen af forrentningssatser for 2005 samt udmelding af indtægtsrammer for 2005,

89 Annex E: Cost of capital E-6 Gearing, D D E The gearing denotes loan capital as a proportion of the total financing needs of a company. Generally, the demand for return on equity will be higher than the demand for return on loan capital. An increasing gearing will lead to an increasing debt risk premium as creditors demand a higher interest rate if there is less certainty in getting repaid. Therefore, in financial theory it is assumed that an optimal financing structure, that minimises the cost of capital, actually exists. This is called target gearing. In practice, this optimal gearing is very difficult to determine and it will vary according to the type and form of the company. The debt proportion of mobile companies typically varies from 0% to around 30%. Mobile operators generally have a lower reliance on debt than fixed operators because of the greater variability in costs and returns compared with incumbent fixed line operations. However, as discussed above, the final result is generally insensitive to this input. Often, a cost of capital is estimated for a range of gearing rates (e.g. NITA s 2002 and 2005 reports on the fixed network LRAIC modelling; PTS s assessment of the cost of capital for its mobile LRIC model, 4 July 2004). Debt premium, R D The debt premium for a mobile operator increases with the rate of gearing. At 10% gearing, the debt premium is approximately 1 2%. The debt premium increases to around 2 3% at a gearing of 30%. These premium rates are consistent with NITA s previous cost of capital determinations in the fixed network. In fixed networks, where costs are less variable, debt funding generally represents a higher proportion with debt premiums for a given gearing. They are 1 2% lower than in the mobile situation, where costs are generally more variable. Asset beta, asset When an agent invests in any given stock, two types of risks are assumed to exist a systematic and an unsystematic risk. The unsystematic risk is caused by the risk connected to the specific stock. The investor may avoid this risk by spreading (diversifying) the

90 Annex E: Cost of capital E-7 investment on a number of different assets. Obviously, a collection of assets (a portfolio) will always exist, eliminating the unsystematic risk. The systematic risk, related to the investment, is due to the fact that it is generally risky to invest in the stock market. This risk is denoted by and is measured as the covariance between the return of the specific stock and the return of the market portfolio in relation to the variance of the return on the market portfolio. For the investor, it is not possible to avoid the systematic risk, which is why a risk premium will be demanded. The magnitude of this will vary with the covariance of the specific stock and the overall market fluctuations. It is possible to estimate asset through a comparison of the fluctuations in a company s stock relative to a broad market portfolio over a number of years. However, such measurements will always be uncertain and will produce a wide range of values depending on the methodology. Again, under such circumstances, regulators often have to estimate the cost of capital for a broad range of asset values. However, by reviewing the range of measurements carried out by third parties, it is possible to provide some consistency to this range. Indeed, as noted above, the ERG provides its own range to this relevant parameter. We find the following conclusions for the reasonable range of asset: for integrated Scandinavian fixed and mobile telecoms providers such as TDC, Telenor or TeliaSonera, which may be disaggregated into separate asset for the fixed and mobile parts for mobile operators, depending on their degree of investment risk. 10 Therefore, NITA estimates that the asset applicable to the funding of the mobile operators in Denmark varies quite widely, ranging from depending on the operator. 10 Investment risk is characterised by the degree of operator maturity, market share, date of entry and technology prospects.

91 Annex E: Cost of capital E-8 E.4 Results NITA considers that the cost of capital is generally insensitive to the debt proportion applied to the weighting calculation, though it is likely that the Danish mobile operators fall into two types of company from a funding risk perspective. Based on this NITA considers the differences between these two groups to be uncertain and therefore finds it most appropriate to choose a beta value of 1.1 for all companies. The WACCs calculated with 0% gearing and an un-geared asset beta are as follows: <--Range for TDC, Sonofon, Telia ---> < Range for Hi3G > Efficient operator Low Beta Lower mid High mid High Beta Beta Beta Risk-free rate, nominal 4.11% 4.11% 4.11% 4.11% 4.11% Equity risk premium 3.75% 3.75% 3.75% 3.75% 3.75% Asset beta Tax rate 25% 25% 25% 25% 25% Pre-tax cost of equity, nominal 10.0% 10.5% 11.5% 13.0% 11.0% Inflation % 2.2% 2.2% 2.2% 2.2% Pre-tax cost of capital, real 7.6% 8.1% 9.1% 10.5% 8.6% Exhibit E.1: Cost of capital [Source: Analysys] For comparison, the WACC calculated at a 10% gearing with a 2% debt premium, and the WACC at a 30% gearing with a 2.5% debt premium, are also shown below. As can be seen, the level of WACC is not materially affected by the debt assumptions. Pre-tax cost of capital, real Low Beta Lower mid Beta High mid Beta High Beta Efficient operator 0% debt, 100% equity, 7.6% 8.1% 9.1% 10.5% 8.6% 10% debt, 2% debt premium 7.6% 8.0% 9.0% 10.4% 8.5% 30% debt, 2.5% debt premium 7.6% 8.1% 9.0% 10.3% 8.5% Exhibit E.2: Effect of debt assumptions [Source: Analysys] 11 Average of inflation for the next ten years, Source: EIU.

92 Annex F: Model updates This annex summarises the updates made to the model in producing versions 1 3 of the draft cost model. The table added to the model files (sheet: Change Summary) lists the specific application of model updates to each mobile operator. Exhibit F.1: Draft v1 model updates [Source: Analysys] Updates for draft v1 model PS data proportion Soft-handover allowance Notes Set to 75% based on NITA information Set to 30% based on Analysys estimates Exhibit F.2: Draft v2 model updates [Source: Analysys] Updates for draft v2 model Deployment of MMSC Deployment of content platform Notes Commences with packet data services Commences with packet data services Routeing factor for 3G interconnect infrastructure Routeing factor added for national roaming incoming traffic Inputs and calculations for Tele2 and Barablu Calculation of "BHCA per minute" for use in the cost allocation matrix New services added to complete the set of national roaming services for 3G Added calculation of book value of fully depreciated assets BTS, BSC and MSC utilisation input changed to a time series Reconciliation files created for each operator Categorisation of capital and operating expenditures for each operator Ringing time added to the radio routeing factors of each voice conveyance service Various changes to data inputs as listed in hearing note Model expanded to accommodate MVNOs Calculation adjusted to be based on 2007 demand parameters because when based on 2006 services, some zeros for non-launched 3G services flow through to give zero cost allocation to 3G services Model expanded to accommodate more services, though not all operators utilise/carry 3G national roaming Only used for one operator's reconciliation To improve calibration aspects of historic evolution To show reconciliation comparisons Operator-specific categorisation of costs set up to assist in reconciliation comparisons In response to operator comments Various see hearing notes

93 Annex F: Model updates F-2 Updates for draft v2 model Signalling channels per TRX Maximum utilisation of a BTS Erlang table functions Cell breathing quadratic approximation added Price trend inputs populated from operator information and estimates Unit equipment prices added A matrix of 0s and 1s has been applied to the unit cost result matrices Revised TSC series of MSC look-up table Switching site retirement period set to two years Revised GSN active PDP and connected subscriber percentages Refined scenario where "no migration to 3G" is selected Added cost elements for overhead elements Added cost elements for licence fees Set licence and business overhead elements to be 100% common, therefore flow through EMPU Added input for proportion of business overhead costs recovered from network OFF NR calls: outgoing calls are completed by the operator carrying the national roaming traffic, rather than handed back to the donor operator Calculation of data service load for GPRS corrected to include downlink proportion Calculation of data service load for 3G packet data corrected to include downlink proportion Revised topology of BTS-Fibre links connecting through the access node network element Revised topology of BTS-Fibre links connecting through the access node network elementaccess node capacity Notes Extended to be operator-specific input Revised algorithm so that maximum utilisation applies to the physical capacity of the BTS, rather than both the physical and spectral capacity. This is because the reasons for underutilising the capacity of BTSs on average relate to the physical domain (i.e. to cause deployment of more sites for "quality") rather than the specific constraint which may arise in the situation of (very) limited spectrum Revised formula to look one row further (see TDC hearing response) See Public Annex D Same underlying trends applied to all operators Operator-specific inputs based on bottom-up unit prices and top-down reconciliation To not show unit costs when services do not exist To improve TSC calibration Since these are particularly large and (slowreacting) network elements To achieve more accurate calibration of GSN deployments So that no 3G assets are deployed at all n/a n/a n/a n/a Though national roaming does not apply to all operators Added downlink percentage to calculation Added downlink percentage to calculation Operator-specific input Operator-specific input

94 Annex F: Model updates F-3 Updates for draft v2 model Fixed the formula for calculating capex unit price of equipment over time from the 1992 input Fixed the formula for calculating opex unit price of equipment over time from the 1992 input Added switch for applying the uplink data traffic to the 3G packet data radio dimensioning calculation Added scenario for WACC inputs Notes n/a n/a In case that the uplink is the limiting CE calculation then the required CE can be calculated on the uplink data n/a Exhibit F.3: Draft v3 model updates [Source: Analysys] Updates for draft v3 model Inclusion of 2007 market data Rationalisation of the scenarios contained on the Control.Panel worksheet Deletion of the Market_scenario_subs_static and Market_scenario_subs_converged subscriber scenarios Removal of the Market voice and data scenario worksheets Revised accounting lifetimes Included national roaming payment schedule Adjusted the model inputs so that the business overhead expenditures inputted to the model are directly equal to the amount to be recovered from network services Revised the estimates of the percentage of traffic carried on the inter-switch network Adjusted the calculation of 2G capacity sites so that the network design algorithm does not assume they are removed Revised the input for the percentage of traffic in the downlink for 3G data to 80% Revised the input price trends for transmission network elements Notes Re-calibration of the model has been performed NITA has finalised a number of scenario decisions, resulting in the removal of their control in the Control.Panel worksheet NITA has decided upon an evolving market scenario NITA has decided upon the specific voice and data forecasts to be used in the model. These are now inputted directly in the Market_scenario_select worksheet Analysys has revisited the calculation of average accounting lifetime for the network assets. Relevant only to Hi3G and Telia. These expenditures are modelled as a network opex to be recovered from all traffic. Previously, the model inputs were of total business overhead expenditures, to which a 50% multiplier was then applied to specify the network share. Analysys considered its estimates to be too low for some operators. This is necessary so that the calculation of sites shared with the 3G network reflects the fact that 2G sites persist in the network. Based on latest (2007) information n/a

95 Annex F: Model updates F-4 Network common cost assets calculated Calculation of the network common costs is located on the Com.incr worksheet (Rows 467: 617). As a result a number of new named ranges have been defined. Furthermore, in order to calculate the 3G common costs, additional calculations are performed on the 3G.Coverage.Calc worksheet

96 Annex G: Optimisation NITA must be satisfied that the results of the cost model are efficient and optimal for the Danish mobile market. Having developed a comprehensive model of each network provider and its associated costs, the model enables NITA to conduct comparisons between operators with relative ease. We have divided the issue of optimisation into two parts: is the network deployed in an efficient manner? are the level of expenditures being incurred reflective of efficient purchasing and operational practices? G.1 Network optimisation There are a large number of differences between the networks of the mobile providers. These network differences arise across a wide variety of network aspects. It would be possible to equalise or average across many of these network design inputs and construct a hypothetical average operator. However, we consider that this would diverge from the principle of actual operator costing, unless there are cases where material inefficiencies can be identified. Based on our comparison of the four mobile operators, we see no evidence of significant and avoidable network inefficiency in any of the networks. G.2 Cost optimisation The model calculates total capital and operating expenditures according to the schedule of asset purchase/operation and per-network-element input unit prices. These input unit prices have been set according to the bottom-up and top-down data submitted by the mobile operators, aiming for a consistent application of equipment unit prices where possible. The network share of business overhead expenditures is also captured using fixed and variable (per-subscriber) input unit prices. Input prices are contained in the Costscenario.basecase sheet, in which a number of similarities and differences exist between the three established operators, and also with Hi3G. Business overhead capex and opex inputs also vary for each operator.

97 Annex G: optimisation G-2 Whilst there are a number of differences between operator inputs for equipment prices, we consider the majority of these differences to be small in overall impact. Differences arise because operators take a different approach to the policies of capitalisation, expensing and categorisation of costs in their businesses. Again, it would be possible to equalise or average across many of these cost inputs and construct a hypothetical average expenditure operator. Again, we consider that this would diverge from the principle of actual operator costing unless there are cases where material inefficiencies can be identified. Based on our comparison of the four operators, we have identified one area of material inefficiency, and consider it appropriate to optimise the level of mobile network expenditures which one party is undertaking in respect of this aspect of its mobile network.

98 Annex H: Decisions applied in the draft v3 model The draft v3 model presents NITA s draft final view of the costs of the four mobile network operators applicable to its pricing decision. In developing the draft v3 model, NITA has carefully considered the submissions of mobile parties, third-party information, and the views of NITA and Analysys. These viewpoints have been used to develop a cost model which NITA considers is reasonable for the purposes of reflecting the operators efficiently incurred costs, and carefully balanced in its consideration of the issues and risks relating to regulatory policy, interconnecting parties and the mobile operators. This has required NITA to take a number of decisions in setting up the draft v3 model. These decisions are documented in this annex. Mobile penetration forecast Based on the latest 2007 market information, Analysys has forecasted a long-term mobile penetration for the four existing network operators amounting to a total of 120%. This penetration figure includes Tele2 (considered part of Sonofon) but excludes the additional subscribers and demand volumes which may be due to new MVNOs such as Barablu. Market share by operator A forecast of market share for the four operators in the Danish market is necessary to calculate the long-run costs of each operator. Analysys has received the latest 2007 market information from NITA and has also reviewed the forecasts provided by a number of thirdparty analysts. These forecasts do not cover the long term that is necessary for the long-run cost model, however they do project that in the medium term (to approximately 2010): Hi3G will increase its market share steadily TDC and Sonofon will steadily decrease their market shares. A forecast of market share has been developed for the model which NITA considers balances the uncertainties in market share forecast for each player, whilst defining a situation in which smaller market players are expected to become larger over time. NITA

99 Annex H: Decisions applied in the draft v3 cost model H-2 does not consider it appropriate to set wholesale mobile termination charges on the basis of highest cost in the situation where small operators remain small (and therefore have lower economies of scale). Voice usage per subscriber The forecast of incoming and outgoing voice usage per mobile subscriber has been projected by Analysys. This projection is considered to reflect medium growth in voice usage, consistent with the observed growth in mobile usage in recent years, and the deployment of higher-capacity 3G mobile networks. As shown in the Exhibits below, this medium growth projection steadily stabilises in the long-term, and during the period , each of the mobile networks evolves towards this average level of usage. NITA considers a medium-growth scenario to be a reasonable basis on which to calculate costs applicable for regulating wholesale termination charges. Originated minutes per average subscriber per month Exhibit H.1: Originated minutes per average subscriber [Source: Operator data, Analysys]

100 Annex H: Decisions applied in the draft v3 cost model H-3 Incoming minutes per average subscriber per month Exhibit H.2: Incoming minutes from other networks, per average subscriber [Source: Operator data, Analysys] SMS usage per subscriber The forecast of SMS usage per total mobile subscriber has been projected by Analysys. This projection is considered to reflect growth in usage that is consistent with the observed rapidly declining growth in SMS usage in recent years. As shown in Exhibit H.3 below, this growth projection steadily stabilises in the long-term, and during the period , each individual mobile network evolves towards this average level of usage. NITA considers this growth scenario to be a reasonable basis on which to calculate costs applicable for regulating wholesale termination charges.

101 Annex H: Decisions applied in the draft v3 cost model H-4 Total SMS messages per subscriber per month (in + out + onnet + technical) Exhibit H.3: Total SMS usage per average subscriber [Source: Operator data, Analysys] Data usage per subscriber The forecast of data usage per 2G and 3G mobile subscriber has been projected by Analysys. This projection is considered to reflect a reasonable yet conservative growth in usage, given the recently observed growths in data services. As can be seen in the following Exhibits, this projection steadily stabilises in the long-term. In the case of 3G Release-99 data (see Exhibit H.5), the forecast can be considered reasonably conservative due to the level of usage dilution experienced as early-adopters are joined by latermigrators on the 3G network. During the period , each of the mobile networks evolves towards this average level of usage. The projection of data traffic for Hi3G includes an additional megabyte traffic load per subscriber, related to the fact that as of the end of 2007, Hi3G was carrying a measurable volume of HSDPA traffic. Hi3G s HSDPA volume is converted to an equivalent amount of R99 data traffic by dividing by four (this being estimated by Analysys as the approximate coding rate gain achieved using HSDPA over R99) which is then included in Hi3G s forecast of projected usage per subscriber. NITA considers these usage projections to be a reasonable basis on which to calculate costs applicable for regulating wholesale termination charges.

102 Annex H: Decisions applied in the draft v3 cost model H GPRS MB per average subscriber per month 2012 Exhibit H.4: GPRS usage per average GSM subscriber [Source: Operator data, Analysys] Release-99 MB per average subscriber per month Exhibit H.5: UMTS Release-99 usage per average UMTS subscriber. Note: higher Hi3G volumes for HSDPA are not shown in this average usage [Source: Operator data, Analysys]

103 Annex H: Decisions applied in the draft v3 cost model H-6 Migration from 2G to 3G The migration from 2G to 3G can be considered a key uncertainty in the projection of mobile operator costs. It is influenced by many factors: the availability of spectrum, possible extension of existing 2G licences, growth in the level of usage per subscriber, and operator strategy. NITA considers it appropriate to set a 2G-to-3G migration scenario for TDC, Sonofon and Telia based on the following principles: All mobile operators have now launched 3G networks for voice and data services. By the end of 2012, full migration from 2G to 3G should be completed for all subscribers, voice and data services. This is consistent with the situation where existing operators vacate or do not reacquire their existing GSM spectrum. Subscriber migration matches each operator s actual subscriber migration profile at the end of 2007, and follows a similar (but not identical) migration curve for each operator. Voice traffic migration matches each operator s actual traffic migration profile at the end of 2007, and follows a similar (but not identical) migration curve for each operator. This voice traffic migration profile is slower than the subscriber migration, reflecting the fact that 3G subscribers can continue to generate both 2G and 3G network traffic, due to roaming back onto the 2G network whilst the 3G network is being completed. SMS usage is carried on the network applicable to the subscriber type (i.e. it follows the subscriber migration profile). GPRS and UMTS R99 packet data usage is applied according to the subscriber type. The migration profiles for each operator are provided separately to each operator in order to preserve confidentiality of their current migration regime. Migration from 2G to 3G is not applicable to Hi3G. Migration from 3G The long-term evolution and utilisation of 3G networks is uncertain. Rather than attempt to predict the 3G licence situation or network evolution post-2022, NITA considers it reasonable to assume in the model that the 3G networks should be fully operated and fully utilised until at least the end of Therefore, no migration off 3G technology is forecast within the first licence cycle of this technology, and all the expenditures of this first licence

104 Annex H: Decisions applied in the draft v3 cost model H-7 cycle are fully recovered within the period to The conservative position of no terminal value at the end of 2022 is also assumed. NITA considers this situation to be unbiased and reasonable from the perspective of the expenditures which are recovered through wholesale termination charges. This decision is applied identically to all four 3G networks. Quality of coverage in the 3G networks As Analysys has detailed to the mobile operators during the model development period, there are a number of possible options for the quality of coverage deployed in the modelled 3G networks. These options are: voice service, outdoor availability voice service, urban indoor availability minimum 64kbit/s data uplink service, urban indoor availability minimum 64kbit/s data uplink service, nationwide indoor availability. The GSM networks in Denmark currently provide good urban indoor availability, and we understand that all Danish mobile operators are deploying a 3G network with at least urban indoor availability for voice service, and in some areas also sufficient quality for a data uplink service (necessary to deliver HSDPA services). NITA considers it reasonable to reflect a voice service with urban indoor availability in the 3G network model. This is because the current mobile market volumes are to a material extent reliant on the presence of some indoor coverage, and because this reasonably closely reflects the deployments which the mobile operators are actually commencing. NITA does not consider it appropriate to model the additional costs required to deliver a minimum 64kbit/s uplink data service and recover some of those costs from wholesale voice termination charges, or to model a nationwide indoor network deployed using 2100MHz. Extent of 2G and 3G coverage All three 2G mobile operators are assumed by the model to achieve the same total coverage by the middle of 2007, at 100% dense urban and urban coverage, 99% suburban coverage

105 Annex H: Decisions applied in the draft v3 cost model H-8 and 98% rural coverage (deployed according to the 2G voice outdoor coverage cell radii and SNOCC). Consistent with the assumption of complete migration from 2G to 3G by the end of 2012 and the closedown of the 2G networks, it is necessary for the 3G networks in the model to have rolled out to cover the same geographic area as the existing 2G networks. Therefore, all four 3G networks are forecast to cover the same extent of coverage as the 2G networks by the middle of 2012, using the coverage quality cell radii defined. This is to ensure underlying network consistency in the modelled volume of traffic in moving completely from 2G to 3G technology. Spectrum used to provide coverage The deployment of the modelled 3G networks is assumed to be at 2100MHz in order to ensure consistency with the over-arching network situation being modelled. NITA considers it possible though not guaranteed that after 2012 some or all mobile operators may have access to 900MHz frequencies with which to further improve the coverage of their 3G networks, and therefore due to the spectrum uncertainty, this outcome is not modelled. Definition of network common costs The draft v3 model defines a proportion of network costs as common to traffic and subscriber services. This definition is provided in Section 9 of the main report. The costs associated with the network common costs (separated into 2G, 3G and shared network components) are aggregated and treated with an equi-proportional mark-up to the residual incremental costs. Asset lifetimes Analysys and NITA have examined the accounting lifetimes supplied by the GSM mobile operators. These lifetimes are, on an averaged basis, applied to the modelling of replacement capital expenditures occurring in the period to end 2006 in each operator s model: through the process of reconciliation, Analysys has set each operator s model to

106 Annex H: Decisions applied in the draft v3 cost model H-9 reflect the actual capital expenditures incurred, including modelled replacements, up to end However, the accounting lifetimes applied in the historical part of the cost model are shorter than the estimated economic lifetime of assets that Analysys has applied in similar mobile LRIC models (e.g. for PTS and Ofcom). Therefore, it has been necessary to consider whether the accounting lifetimes presented by the mobile operators should also be applied to 3G assets and assets with a potentially long lifetime over the long-run period of cost calculation. Analysys considers that the shorter (accounting) lifetimes applicable in the historical period of the mobile networks operations have been due to factors including: continually increasing quality of coverage rapid growth in service volumes (from 2% penetration to 100% penetration) introduction of new services (e.g. prepaid) and data technologies (SMS, GPRS, EDGE). In the 3G network model, rapid growth in service volumes (medium/conservative growth scenarios are modelled) and the introduction of new services (e.g. HSUPA, LTE, etc.) are not modelled. Therefore, from the perspective of setting wholesale mobile termination rates, NITA considers it reasonable to apply the longer, economic lifetimes to the 3G network elements. It is also considered reasonable to apply an estimate of the economic lifetime for long-lived assets such as radio and switching sites, since it is expected that over the period to 2022 such deployments will be more durable than the accounting lifetime would suggest. This decision also sets a reasonable benchmark for network operation over the long run from the perspective of the costs which must be borne by interconnecting operators and their customers. Retirement of assets from the 2G networks As traffic is migrated off the 2G networks, certain elements of 2G network capacity will become unnecessary: this issue has been discussed in some detail with the mobile operators. Given the full migration by 2012 being modelled and the operation of 2G and 3G networks in parallel until the end of 2012, it is reasonable to consider that it is unlikely that operators will be able to remove significant parts of their 2G networks prior to the end of This is because until mid-2012, 3G coverage will not have been completed, and

107 Annex H: Decisions applied in the draft v3 cost model H-10 therefore the old 2G networks may still be accessed by a large proportion of the customer base (e.g. as fall-back national roaming). Therefore, Analysys and NITA consider it reasonable to model 2G operators as retaining a considerable part of their 2G networks until the end of 2012: all GSM900 and DCS1800 BTS microwave and leased line backhaul links backhaul fibre access points 2G MSCs and 2G MSC/network software transit switches (if deployed) remote and main switching sites national STM1 transmission network. The following items are assumed to be removed from the 2G networks two years after becoming redundant: BSC switches including PCU The following items are assumed to be removed from the 2G networks one year after becoming redundant: TRX BSC and MSC port infrastructure variable costs such as wholesale and business overhead expenditures (if in decline). Whilst it is difficult to precisely predict the closedown process that an operator would carry out, we consider this specification to be a reasonable model of the expenditures being incurred for remaining assets combined with the expenditures being saved for removed assets during a 2 3 year period when an operator is simultaneously rolling out its 3G network and (where possible) closing down its 2G network. Retirement of assets from the 3G network Since the 3G networks is being modelled as fully operational until the end of 2022, retirement or removal of any 3G network assets are considered to fall outside of the cost calculation.

108 Annex H: Decisions applied in the draft v3 cost model H-11 Cost of working capital The model includes a cost of maintaining a working capital balance equal to one month s supply of operating expenditures. This cost is added as an uplift to all opex included in the model, calculated as 30/365 multiplied by the cost of capital. NITA considers this a reasonable allowance for working capital included in regulated wholesale mobile termination charges in Denmark. 3G licence fees NITA has considered the value of 3G licence payments (if any) to be included in the model and therefore to be partly recovered through mobile termination charges and other network services. NITA finds the actual licence fees and their specified payment schedule over the first ten years of the licence to be reasonable and efficient in the long run. Therefore operators actual fees are applied in each model, inflated where applicable to 2006 realterms currency.