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[30/1/02 -02] The LRIC model of UK mobile network costs, developed for Oftel by Analysys, September 2001 A Manual for the Oftel model Working paper for Oftel, 29 January 2001 2 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions Executive summary 3 Executive summary This working paper presents a comprehensive description of the long-run incremental cost (LRIC) model of UK mobile network costs, developed for the UK regulator, Oftel, by Analysys, during 2001 The model was made available by Oftel in conjunction with its statement on mobile termination in the UK, and can be downloaded from the Analysys Web site. Although this model is freely available, it is copyright of the UK Crown, and should not be used for any purpose other than the review into mobile termination in the UK this document does not contain details of the Excel-related mechanics of the model instead, it provides details of the theory that underlies the model, and details of the nature of calculations employed (but not their Excel implementation) 4 Executive summary Related documents The LRIC model of UK mobile network costs, developed for Oftel by Analysys download from www.analysys.com Oftel statements related to the review of mobile termination in the UK download from www.oftel.gov.uk 5 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 6 Introduction LRIC modelling is a method of calculating costs which employs a specific set of costing principles Long-run incremental cost modelling relates to: a consideration of costs over the economic lifetime of assets (long-run) the attribution of costs to specific services Estimates the economic costs of installing, maintaining and operating a mobile network Estimates the cost to a new entrant of providing the same service as the existing network operator Identifies the structure of costs – how they vary with the level of demand and range of service offerings Advantages are: a good predictor of volume/cost movements represents an economically rational approach to pricing cost-based services over time of increasing interest to regulators, especially for validation of interconnect arrangements, because cost-orientated of paramount interest to new entrants forward-looking Introduction 7 LRIC cost modelling is supported by major regulators and other organisations Supported by the FCC, EC and IRG (Independent Regulators Group) for costing mobile termination Applied by OFTEL in its current proposals for the regulation of mobile termination rates in the UK 8 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 9 Background Oftel was required to consider a range of issues when setting interconnect prices Prices Pricing method e.g. LRIC, LRIC+ Costs Other factors e.g. externalities Costing method e.g. forward-looking economic costs Data e.g. unit input costs Assumptions e.g. demand forecasts Background 10 The models developed for Oftel by Analysys only derived the costs of mobile termination, and enabled a number of mark-up regimes to be applied Illustration of alternatives not policy Prices Pricing method e.g. LRIC, LRIC+ Costs Other factors e.g. externalities Costing method e.g. forward-looking economic costs Data e.g. unit input costs Assumptions e.g. demand forecasts 11 Background Analysys constructed the 1998 and 2001 LRIC models for Oftel In 1998, Analysys constructed a bottom-up LRIC model for Oftel, to assist Oftel in its 1998 review of the price of calls to mobiles This model calculated the costs of : a reasonably efficient new entrant in a (hypothetically) fully contestable market with the demand parameters of either Vodafone (GSM 900) or Orange (GSM 1800) for (year average of) the financial year 98/99 In 2001, Analysys began the process of updating this model to reflect the needs of Oftel for the next review of the price of calls to mobiles (completed September 2001) 12 Background A number of areas of the model were highlighted for improvement Enable the model to calculate costs for the years 2000/01–2005/06 Improve specific areas of the model: update and refine data and assumptions in the model, with the co-operation of the UK operators review methodological issues, with input from operators, to improve the accuracy and suitability of the network deployment algorithms make the model algorithms and calculations more explicit Update the model to reflect the current and expected development of the mobile market: current: SMS, emerging HSCSD and GPRS services, increased expectations of the “quality of mobile network coverage” expected: increased take-up of data services (HSCSD, GPRS and latterly UMTS), eventual decline in SMS in favour of packet based messaging services, simultaneous operation of UMTS voice and data networks by the four UK operators 13 Background In order to calculate costs out to 2005/06, forecasts of the UK mobile market and associated network deployments were required It was important to establish consistent forecasts, calculations and model algorithms e.g. the allowance for growth assumed in deploying the network was consistent with the growth in market demand that the nature of the (hypothetical) competitive market was correctly and consistently represented Taking into account the (2000/01 real terms) model results, Oftel derived P2000/01, P2005/06 and X these parameters (P = price; X = percentage price decline) were important in setting the regulated price cap The UK mobile market was forecasted in terms of: Network deployment forecasts required time series for: subscribers minutes of use (incoming, outgoing, on-net) demand drivers (e.g. busy hour traffic proportions) data service take-up (subscribers, technologies, megabytes of use) network design parameters (e.g. traffic by cell type) equipment unit costs 14 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 15 The model The costs calculated by the model developed by Analysys represent a unique implementation of LRIC theory and regulatory policy … The model developed by Analysys in 1998 calculated the long run costs of: a reasonably efficient new entrant in a (hypothetically) fully contestable market* with the demand parameters of either Vodafone (GSM 900) or Orange (GSM 1800) for (year average of) the financial year 98/99 However, the model developed by Analysys in 2001 calculated the critically different long run costs of: a reasonably efficient operator that launched service in 1992/93 (corresponding with the launch of GSM in the UK)* in a market with the assumed level of contestability* with 25% share of the total mobile market from 1992/93 to 2002/03, declining to 20% share of the total mobile market by the end of 2009 (corresponding with the entry of the fifth player to the UK market) for the (year average) of financial years 2000/01 to 2005/06 * See later section on Economic Depreciation for definition of these terms and justification of approach adopted 16 The model … but the cost modelling is still based on sound techno-economic principles Bottom-up A ‘scorched-node’ approach was adopted, so that the network design reflects the actual number of base stations and switch sites currently deployed a scorched-node deployment is one that evolves over time and is constrained by the history of deployments conversely, a scorched-earth deployment is one which has no historic constraints, and can be deployed in an optimal fashion Modern technologies (for example, those currently being deployed) are used throughout (MEAs; modern equivalent assets) Sufficient capacity to meet present (coverage and demand) requirements is provided; plus an allowance for reasonable future growth, but no more Incorporating (a variant of) economic depreciation for calculating economic costs Deriving the long run average incremental costs: average costs are calculated rather than marginal 17 The model Scorched node approach Background to the scorched node approach Networks develop over time in response to changes in demand (or forecast demand) The location of network nodes is dictated to at least a degree by the availability of suitable sites on the ground As a result of this evolutionary development, networks are rarely truly optimal for current (or currently forecast) market conditions Such sites are rarely in the ideal location from a theoretical perspective – another reason for networks being less than optimal Radio network design is a complex process, involving a very large number factors and design parameters, not all of which are measurable in advance To accurately capture every nuance of these algorithms in a predictive cost model would be excessive (and almost certainly impossible given the reliance to some extent on information that can only be measured once the network is in place) 18 The model Scorched node approach The rationale for the scorched node approach The scorched node approach accepts that: these are real processes that increase the cost of providing services, and that it is impossible to accurately capture the impact of such highly complex processes as these in a purely predictive model. The scorched node approach therefore relies instead upon actual statistics about the design of operators’ networks as predictors of the aggregate impact that these effects would be likely to have on the network design of an operator, including that of a new entrant. NB Not because incumbents’ have to continue operating their existing networks: If the market were contestable (even if not fully contestable) then incumbents’ would have to set prices in line with those that a new entrant would charge; New entrants would not have to recreate the existing design of an incumbent’s network if that were less than fully efficient, but they could be expected to suffer the same problems as incumbents already have, when rolling out their networks. NB This does not mean that the modelled operator has to have exactly the same number and distribution of nodes as does a real operator, merely that the relationship between the drivers of node deployment and actual node placement, are similar in the model to those actually seen in the networks of real operators. 19 The model Scorched node approach Notes re implementation in the LRIC Model of UK Mobile Network Costs Information about the networks of the four UK mobile network operators was collected from a variety of sources – in particular the number of base stations, BSCs and MSCs Information about the coverage and traffic carried by each of the networks was also obtained or estimated The network design algorithms and parameters in the model were then fixed at reasonable values (based on general industry data) A specific parameter of the network design algorithms (the “scorched node utilisation”) was then adjusted for each network element until the number of units of that element predicted by the model was reasonably close, for all network operators, to the actual number of units of that element believed to be in use in the real networks The resulting value for the scorched node utilisation parameter simply describes how much lower (or higher) than expected (on the basis of the standard network design algorithms and parameters used in the model) the actual utilisation of network elements really is The model can then predict the number of nodes that a 25% market share operator would be likely to have, with a reasonable degree of accuracy, based on the actual number of nodes in use by the UK operators today 20 The model The scope and detail of the model is critical The model aims to capture: all relevant network elements and business activities all relevant expenditures: – capital investment – operating expenses – return on capital employed The level of detail in the model should be sufficient: for the network design to reflect actual industry practice rather than some hypothetical optimum or simplification to capture significant factors that influence the total cost of the network, yet should not be more complex than is absolutely necessary 21 The model Key inputs fall into five broad categories Service demand levels Network design rules and parameters Equipment unit costs (and price trends) Cost of capital Service routeing factors 22 The model The key outputs are a number of cost figures For each year, the model outputs: total common cost total incremental costs unitised, un-marked up incremental cost per service unitised marked-up cost per service, for a number of alternative mark-up regimes Unitised costs represent: total costs associated with an increment divided by number of demand units of that increment The model 23 Mark-ups Unmarked-up costs represent the raw incremental cost associated with each increment, without recovery of common costs Common costs may be recovered by marking-up some or all of the raw incremental costs of services – increasing prices of those services to ensure recovery of the costs common to some or all services A number of different mark-up regimes are possible – see later for details In all cases mark-ups are calculated and applied as a percentage increase on raw incremental costs The recovery of common costs from services is therefore done by reference to incremental costs (possibly more or less weighted according to the service) and not by reference to any common unit of demand or supply (which is typically how such costs would be allocated to services in a fully allocated cost model) 24 The model The model flow consists of six major building blocks; information flows from input, to calculation, to output … A Cost drivers, services and increments B Forecast of demand 2000–2006 C E Network design 1 3 Network element costing 2 D Economic cost 4 F 5 Service costing 25 The model … which are shown in brief in this section The following slides indicate the main data, assumptions, calculations and information flows associated with each of the: six building blocks identified five information flows Following this section, each section of the model is discussed in greater detail Legend Data or assumptions Information flow Calculations or Outputs Major elements 26 The model A. Cost drivers, services and increments Define what the drivers of cost are Define the associated services and increments Define how the increments will interact Cost drivers, services and increments 27 The model B. Forecast of demand 2000–2006 S-curve penetration Market shares Minutes per sub 2G/3G partition SMS penetration SMSs per user MByte user penetration MByte per sub 2/2.5/3G partition Mobile subscribers 2G incoming minutes 2G outgoing minutes Forecast of demand SMS volumes GPRS users GPRS MBytes HSCSD MBytes 28 The model 1. Cost drivers and demand forecasts to network design The drivers of cost Cost drivers, services and increments Year average mobile subscribers Year total incoming minutes Year total outgoing minutes Year total SMS messages Forecast of demand 2000–2006 Year average GPRS users Year total GPRS Mbytes Year total HSCSD Mbytes Select year: 00/01 01/02 02/03… Network design Select operator: GSM 900, GSM 1800 29 The model C. Network design Design parameters Selected year Coverage Selected operator Demand inputs Coverage network design Full network design Incremental network design 30 The model 2. Network design to economic cost Selected year Network design Selected operator Out-turn utilisation profiles Economic cost 31 The model D. Economic cost 00/01 MEA capex Selected year 00/01 MEA opex Economic lifetime Opex trends Annualisation percentage Selected operator Out-turn utilisation profiles * Calculation performed for each item Economic cost calculation Capex trends 32 The model 3. Network design to network element costing Coverage network deployment + Network design Incremental network deployment = Full network deployment Network element costing 33 The model 4. Economic cost to network element costing Economic cost Economic cost for each item Network element costing The model 34 E. Network element costing Economic cost for each item Coverage network deployment Coverage network cost + Incremental network deployment Incremental network cost = Full network deployment Full network cost 35 The model 5. Network element costing to service costing Average incremental cost of each network element per unit output Network element costing Service costing Common costs of coverage 36 The model F. Service costing Routeing factors Average incremental cost of each network element per unit output Unitised incremental cost per service Common costs of coverage Mark-ups to recover common costs 37 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 38 The model Define what the drivers of cost are Define the associated services and increments Cost drivers We assume four primary cost drivers Cost drivers, services and increments Define how the increments will interact In a mobile network, the primary drivers of cost are: the level of coverage required, either geographically, or in terms of quality (in-building penetration, etc.) the number of customers (subscribers) the amount of traffic that is carried on the network the quality of service (QoS) offered to the customers, in terms of blocking or dropping probabilities In addition, a range of secondary drivers of cost exist, for example: number of location updates number of call handovers 39 The model Cost drivers Coverage requirements are defined in terms of population and area coverage 100% 90% Coverage is often quoted in terms of percentage of population covered (as per licence obligations) More useful to a mobile network designer is the geographical area covered (disaggregated by type): Population We define a number of area types that effectively capture the broad range of radio environments in a country. In the UK, we used: Area 60% 100% Suburban Urban Rural Highway converting population coverage into area requirements usually requires detailed demographics urban, suburban, rural, highway For example 90% of the population can be covered in 60% of the land area, comprising all urban, all suburban, part rural and part highway coverage strictly speaking, no-one lives on a highway, and such deployments cover rural motorway-side towns and villages 40 The model Cost drivers Notes re implementation in the LRIC Model of UK Mobile Network Costs In-building penetration is not explicitly quantified in the model The scorched node approach ensures that the level of in-building coverage included in the model is comparable with that typically provided by UK operators Likewise, the effects of secondary cost drivers, such as the number of location updates and call handovers, are not explicitly quantified in the model The values of other network design parameters have been set conservatively to provide sufficient capacity to deal with these activities 41 The model Cost drivers Customer-driven costs are not significant ... Infrastructure related Mobile networks do not have substantial investments tied up in plant dedicated to individual customers However, some elements (such as the maintenance of a HLR about status of customers) are sensitive to customer volumes Handsets In addition, each customer requires a mobile handset in order to make or receive calls The cost/subsidy per handset is the only relevant cost component and in general considered separately from customer-driven network costs The amount of costs associated with handsets may however be taken into account in the markup regime Similarly, the (year average) number of subscribers is used to drive handset costs Hence, the model contains the (year average) number of subscribers as a driver 42 The model Cost drivers ... whereas traffic and quality of service are significant cost drivers Traffic Principal measures used when dimensioning network elements are: busy hour erlangs (busy hour minutes/60) busy hour call attempts Levels of cost drivers are calculated separately for each traffic-related service, based on the annual amount of traffic the use of appropriate annual traffic and busy hour averaging parameters ensures that the network is also driven by the year average load Traffic cost drivers (incoming, outgoing and onnet voice, SMS messages, GPRS and HSCSD data traffic) are assumed to be parallel (see next slide for explanation) and hence can be combined into a single increment called traffic Quality of service Quality of service is an important driver of cost However, inverting the relationship between quality of service and cost is a complex transformation, and does not result in a simple increment that is orthogonal or parallel to others Hence we do not define a service increment called quality of service, with X units: and cannot determine the cost per unit of quality (whatever unit that may be) However, the model contains blocking probabilities as inputs, so can be used to investigate the variance of other service unit costs with quality of service The base case values for these are: 2% blocking on the air interface 0.1% blocking in the core network 43 The model Cost drivers What is the significance of orthogonal and parallel services? For example, two drivers of cost, each with a corresponding service increment: If the services are orthogonal, then equipment that supports service 1 does not support service 2 and vice versa no common costs exist (other than the coverage network, if appropriate) HLR – for customers only TRX – for traffic only If the services are parallel, then equipment that supports service 1 partially or entirely supports service 2, and vice versa common costs exist between the services, according to the levels of demand and design algorithms TRX – for voice traffic TRX – for GPRS traffic dedicated costs also occur for each service, where appropriate GGSN – for GPRS only 44 The model Cost drivers Combining service into a single increment simplifies the calculation requirements Most services exhibit both parallel and orthogonal behaviour, depending on the particular equipment class which they are interacting with: Resolving the common and incremental costs associated with each increment absolutely is a complex algebraic calculation and a time consuming process: for example, HLRs are a dedicated resource for customers; however, the MSC processing requirement of location updates (a customer driven cost) is shared with the MSC processing requirements of incoming and outgoing call attempts such a calculation needs to resolve all combinations of common costs and incremental cost by considering all possible permutations of the increments Combining services into a single increment for all demand simplifies the model: orthogonal service costs are resolved without need for complex calculations parallel service costs are resolved on the basis that any common costs that may arise are automatically allocated on the basis of resource consumption 45 The model Cost drivers The Oftel model uses a single increment for all traffic demand, representing a single parallel increment for all traffic, plus an orthogonal increment for customers Busy hour total traffic load Customers Busy hour call attempts Number of location updates Peak SMS throughput Coverage Costs Incremental Traffic Coverage Services Total cost of the network is taken to be the sum of: the standalone cost of providing a specified level of coverage the incremental cost of expanding that network to carry a specified volume of traffic the incremental cost of expanding that network to serve a specified volume of customers 46 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 47 The model Define what the drivers of cost are Define the associated services and increments Cost drivers, services and increments Define how the increments will interact Services and increments At one stage the Oftel model contained eight separate services In general, services should relate to the fundamental services which the subscribers are purchasing Applications or value-added layered services are not considered: this simplification is influenced by the fact that the vast majority of current network traffic and costs are due to simple voice communication data transport is assumed to become more important in later years, however we use a Mbyte data transport service, rather than a range of uncertain data applications Handsets Customers Mobile originated off-net minutes Mobile originated on-net minutes Mobile terminated minutes SMS messages GPRS Mbytes HSCSD Mbytes The handset increment can be considered separately from (i.e. is orthogonal to) the other increments 48 The model Services and increments Considering all permutations of service demand requires a large number of calculations (16 calculations for 4 increments) Raw incremental costs Voice e.g. 80% GPRS HSCSD SMS 1,2 3 Voice + SMS Voice +… 4 5 6 Voice +… 7 8 9 10 11 GPRS + HSCSD … + GPRS .. + HSCSD SMS + GPRS SMS +… .. + HSCSD Voice + SMS + GPRS Common costs e.g. 5% SMS + GPRS + HSCSD Voice + SMS + … .. + HSCSD Voice +… … + GPRS + HSCSD Voice + SMS + GPRS + HSCSD Coverage cost Coverage e.g. 15% Areas are not to scale Voice represents customers and voice minutes Fully and separately resolving 8 increments would require 64 separate calculations Incremental costs using single traffic increment 49 The model Services and increments Even when the permutations have been calculated, the mark-up regime becomes horrendous Each common cost 1–11 needs to be marked-up across the services which it supports The order and nature in which costs are marked-up must be defined: Voice GPRS HSCSD SMS 1,2 3 Voice + SMS Voice +… 4 5 6 Voice +… 7 8 9 10 11 GPRS + HSCSD … + GPRS for example, equalproportionate? mark-up on mark-up? .. + HSCSD SMS + GPRS SMS +… .. + HSCSD The sum of all the common costs 1– 11 is small in comparison with the raw incremental costs of the major traffic increments (voice and latterly GPRS) The coverage cost (by far the largest common cost) must also be marked up in some fashion Voice + SMS + GPRS SMS + GPRS + HSCSD Voice + SMS + … .. + HSCSD Voice +… … + GPRS + HSCSD Voice + SMS + GPRS + HSCSD Coverage 50 The model Define what the drivers of cost are Define the associated services and increments Cost drivers, services and increments Services and increments Hence, after investigation, we implemented a single increment for traffic in the Oftel model Define how the increments will interact The model calculates incremental costs for the services using a single increment This increment resolves the allocation of costs using routeing factors: shared infrastructure on the basis of demand consumption: – equivalent voice equivalent erlangs, or other parameter dedicated infrastructure is still allocated directly to the appropriate service This model enables: understanding of the relevant increment calculations comparatively rapid calculation time simple (yet automatic) allocation of common costs between services simplified mark-up step And produces results for the voice LRICs that are very close (~1% difference) to those of a combinatorial multi-increment model 51 The model Services and increments In addition, the definition of the coverage network was altered … The coverage network is required to: Such a network, due to equipment divisibility, actually contains enough capacity to support many more voice calls at no additional cost support at least one incoming or outgoing voice call, anywhere within the coverage area of the network for example, one TRX has 8 channels The coverage network was investigated. It was determined that: a large proportion of the cost of the coverage network was actually equipment which directly supported traffic or customers only some equipment represented an absolute minimum requirement to provide coverage – for example, the acquisition and preparation of the 2000–3000 sites required to achieve minimum population coverage 52 The model Services and increments … to better reflect the relationship between capacity and cost Coverage network Macro-cell site and TRXs HLR Backhaul transmission BTS BSC–MSC transmission Inter-switch transmission The coverage network was broken into two parts: MSC VLR BSC – network management system (NMS) and points of presence (macro site acquisition, preparation and rental) NMS Minimum coverage presence Macro-cell site acquisition, preparation and rental NMS HLR Backhaul transmission BTS BSC–MSC transmission BSC the coverage capacity – equipment deployed in the coverage network providing more capacity than actually required to support just one voice minute Coverage capacity Macro-cell BTS and TRXs the minimum coverage presence Inter-switch transmission MSC VLR 53 The model Services and increments The two parts of the coverage network are dealt with separately The minimum coverage presence is used as the mark-up term The coverage capacity is added to the incremental network capacity: all capacity-providing elements deployed in the coverage network are considered as incremental to traffic or customers as appropriate the cost of these capacity elements is allocated according to routeing factors This definition reduces the amount of cost in the coverage network, and as a consequence, reduces importance of the choice of mark-up mechanism 54 The model Services and increments The Oftel model is a good representation of reality and significantly more manageable than possible alternatives Combinatorial multiple increment Single increment, MCP Voice GPRS HSCSD Voice SMS GPRS Voice + SMS Voice +… Voice +… GPRS + HSCSD … + GPRS .. + HSCSD SMS + GPRS SMS +… .. + HSCSD Voice + SMS + GPRS SMS + GPRS + HSCSD Voice + SMS + … .. + HSCSD Voice +… … + GPRS + HSCSD Voice + SMS + GPRS + HSCSD HSCSD SMS Coverage Minimum coverage presence Voice represents customers, incoming minutes, outgoing off-net and outgoing on-net minutes Diagrams not to scale. Total cost is the same in both cases 55 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 56 The model Demand forecasts Demand forecasts are required in order to calculate cost results to 2006 It is important that this forecast is consistent with the methodology used elsewhere in the model for determining the LRICs: We primarily require a set of reasonable forecasts which will enable the model to be run, investigated and produce reasonable information: for example, the allowance for reasonable growth which is factored into the LRIC approach should be consistent with the demand growth assumed in the forecasts the assumption set was tailored to provide the required fidelity in forecasting, yet small enough to be easy to use and modify The forecasts used in the model were intended to be operator non-biased, for example: all operators tend to the same market share all operators are subject to the same rates of long term traffic growth all operators have identical assumptions concerning HSCSD, GPRS and UMTS demand historic nature of an operator’s subscriber base persists in the forecast The model 57 Base case demand forecast: subscribers Demand forecasts The model 58 Demand forecasts Base case demand forecast: outgoing minutes per subscriber per quarter The model 59 Demand forecasts Base case demand forecast: incoming minutes per subscriber per quarter 60 The model Demand forecasts The forecasts contain a number of inputs, calculations and outputs Inputs take the form of: S-curves, for parameters which grow to a saturation point Simple percentages for time dependent shares or divisions Quarterly growth rates, for parameters which increase or decrease in a smooth fashion The following demand parameters are calculated: Mobile subscribers, by operator SMS messages Incoming and outgoing* voice minutes, on 2G and 3G networks HSCSD, GPRS and UMTS transport service users and Mbytes of traffic Demand parameters in future years, in order to calculate allowances for reasonable growth Outputs of the forecast are: Demand parameters in each year *outgoing voice minutes forecast includes outgoing on-net minutes 61 The model Demand forecasts S-curves are used for parameters which grow to a saturation point x(t) The inputs required for an s-curve are: saturation of x base year x(A) at time A x(B) at time B saturation of x x(B) x(A) t base A B Used for: mobile market penetration migration of voice traffic from 2G to 3G data transport service penetration 62 The model Demand forecasts Percentage inputs are used for time dependent shares or divisions 100% A simple percentage is used to distribute a parameter across different categories Used for: 80% market shares Mbytes across GPRS, HSCSD and UMTS 70% 60% 50% 40% 30% 20% 10% UMTS GPRS HSCSD Jul-09 Jul-08 Jul-07 Jul-06 Jul-05 Jul-04 Jul-03 Jul-02 Jul-01 0% Jul-00 Partition of Mbytes by technology 90% 63 The model Demand forecasts Quarterly growth rates are used for parameters which increase or decrease in a smooth fashion growth 3 growth 2 growth 1 x(t) Simple exponential growth (or decline) can be specified with a single percentage Annual growth rates are the compound of quarterly growths: t0 t1 t2 t3 t e.g. 2% per quarter constitutes 8.2% annually The input of quarterly growth rates are used to forecast: minutes per subscriber SMS per user Mbytes per user 64 The model Demand forecasts Various levels of dimensionality are contained in the Oftel model forecasts Mobile subscribers by year quarters by operator Incoming voice minutes by year quarters by operator by technology 2G/3G Outgoing voice minutes by year quarters by operator by technology 2G/3G SMS messages by year quarters by operator Data transport users by year quarters identical for each operator by technology HSCSD, GPRS, UMTS Data transport Mbytes by year quarters identical for each operator by technology HSCSD, GPRS, UMTS 65 The model Demand forecasts Our technology assumptions by their nature contain implicit consideration of the range of issues that will affect traffic on these networks For example, the partition of voice traffic across 2G and 3G networks implicitly makes assumptions on: numbers of subscribers on 2G or 3G plans operator strategies for 3G voice and data 3G coverage extent or black-spots high-use 3G early adopters and low-use price-sensitive 2G remaining subscribers The use of quarterly assumptions assist in defining accurately when services are assumed to be launched 66 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 67 The model Network design The Oftel model network design algorithms are based on a number of principles Reflect industry practice with regard to base station layout, checked against existing networks this checking is a combination of parameter calibration and application of industry experience Represent the use of modern technology Satisfy the requirements of coverage and demand Allow for reasonable growth (but no more) Contain the key differences between GSM 900 and GSM 1800 radio network deployment different cell radii and different radio layer spectral efficiency* The model contains around 60 different units of equipment, sufficient to capture the required fidelity in network design, yet small enough to be manageable * Spectral efficiencies vary between GSM 900 and GSM 1800 networks in the UK because the 900MHz spectrum allocation is more fragmented than the 1800MHz spectrum allocation 68 The model Network design Simplified network diagram Macro-cell site and TRXs HLR Backhaul transmission BTS Backhaul transmission BSC–MSC transmission Inter-switch transmission BSC MSC VLR PCU NMS Micro-cell or pico-cell site SGSN Dedicated GPRS infrastructure * For the purposes of inter-switch transmission, we assume BSC, SGSN and MSC are co-located GGSN Internet 69 The model Network design We define a number of area and cell types Four area types Six cell types Rural Urban Omni macrocell Microcell Suburban Bi-sectored macrocell Highway Tri-sectored macrocell Picocell Tri-sectored GSM 1800 dual spectrum overlay 70 The model Network design The area types are based on population densities It is assumed that population density is a proxy to radio planning area types. Hence the model utilises data from around 9000 postcode sectors to assist in the categorisation of area types in this fashion Definitions of the area types used are as follows: Urban – postcode sectors with a population density larger than 8178 Suburban – postcode sectors with a population density between 8175 and 721 per km2 Rural – postcode sectors with a population density less than 721 per km2 Highway – 50% (11 000 km) of the primary roads in the UK – this area type is actually “rural highways” since urban and suburban road are assumed to be within urban or suburban coverage 71 The model Network design The six cell types allow differences in network design by area type to be reflected The model contains a number of inputs for: the proportion of cells of each macro type, in each area type However, the inputs currently assigned in the model reflect a simplified situation: tri-sectored macro sites are deployed in urban and suburban areas bi-sectored macro sites are deployed in highway areas omni-sectored macro sites are deployed in rural areas These cell types are deployed in response to the greater of coverage or traffic requirements Micro and pico sites (defined as single sector, 2 and 1 TRX respectively) are deployed in response only to traffic requirements, and furthermore, only in urban and suburban areas: the amount of traffic that is carried on these cell layers is specified by a percentage (by area type) of total traffic in that area type In the UK, the GSM 900 operators also have GSM 1800 spectrum.. The model deploys a GSM 1800 layer upgrade to these operators’ urban macro sites, and expands this in response to the amount of traffic loaded onto this cell layer 72 The model Network design The use of a single increment for traffic requires service demand drivers to be added together In reality, the radio interface responds differently to voice circuit, GPRS packet and signalling traffic. However, constructing a complex radio engineering model which separately deals with these traffic types is not recommended in a LRIC costing exercise Rules are required to combine traffic from voice, SMS, HSCSD and GPRS in a suitable way The Oftel model contains voice equivalent erlangs: the amount of traffic equivalent to one voice erlang rules are defined for converting service demand (eg SMS messages, GPRS Mbytes) into voice equivalent erlangs Voice equivalent erlangs can then be added to normal voice erlangs, in order to drive the network design algorithms with the aggregate traffic load It is assumed that all services have a coincident busy hour (which may lead to some overstatement of costs), and highly complex effects (such as different link margins (i.e. cell radii) for GPRS traffic) are neglected 73 The model Network design SMS and HSCSD voice equivalent erlangs (VEErl) SMS messages 40 bytes per SMS HSCSD mbytes voice channel rate of 767 bit/s 80% of user demand in the downlink 1 minute 82 SMS 70% channel occupancy SMS messages are carried by signalling channels in the radio layer: the model assumes an average size for each SMS message, and a data rate for a channel the model assumes the use of SDCCH (synchronous data control channel) for SMS message transfer voice channel rate of 14.4 kbit/s 1 minute 0.135 HSCSD Mbyte User demand represents both up and downlink traffic HSCSD is a circuit switched dialup data service that enables users to open more than one channel in a particular direction, in order to obtain a higher rate of data transfer: it is very similar to a circuit switched voice service we need to assume a channel occupancy and data rate 74 The model Network design GPRS voice equivalent erlangs 80% of user demand in the downlink 100% channel occupancy voice channel rate of 9.05kbit/s (CS1) 12% additional IP overheads an allowance for packetised nature 1 minute 0.09 GPRS Mbyte User demand represents both up and downlink traffic GPRS is an IP packet switched service: hence the model assumes 100% channel occupancy, and 12% overheads for IP protocol GPRS has variable data rates: four data rates (CS1–CS4) are available with GPRS CS4 (around 22kbit/s per channel) represents transmission under idealised conditions, or when the network has a low level of loading CS1 represents the lowest data rate of transmission, and is the likely rate achieved in the network under busy conditions (from which the model is driven) An allowance has been made for the ability of the packetised GPRS service to utilise some of the gaps in traffic which occur as a direct result of using the erlang transformation to provision more channels than required. This assumed allowance is calculated to be small 75 The model Network design GPRS traffic can utilise (to an extent) gaps between voice conversations A certain amount of ‘under-utilised’ capacity exists as a result of applying the erlang blocking probability formula to the voice calls in a sector: a BTCellnet paper (obtained from its website) indicates that this spare capacity can in fact be used by GPRS: – some probability should be applied to this spare capacity, to work out its effective erlang capacity The model calculates the difference between the number of channels deployed and the number of erlangs supported: this number of channels is used to determine the relative loading of voice circuits and GPRS packet traffic: – this factor is calculated to be 95%. i.e. GPRS packet traffic only demands 95% of the capacity for the same amount of voice circuit switched traffic The model 76 Network design GPRS service demand interacts with a number of dedicated and traditional GSM network infrastructure SGSN100 Total GPRS BH kbit/s (+12% IP) GPRS subscribers GGSN100 IP transmission PCU Downstream GPRS BH kbit/s Dedicated GPRS infrastructure Downstream GPRS voice equivalent BHE Existing GSM infrastructure Air interface Backhaul BH = busy hour 77 The model Network design The HSCSD service places demands upon all traditional GSM infrastructure Radio and transmission HSCSD voice equivalent erlangs are added to voice circuit switched erlangs (using routeing weighting) and used to drive the deployment of traditional GSM infrastructure, including: base station sites and TRX backhaul BSC switching interswitch transmission switch ports MSC/VLR processing Voice calls require MSC/VLR processing to originate and terminate. This processing includes checking the validity of the subscriber, and locating the mobile handset in the network HSCSD calls also require processing when they are originated from a HSCSD enabled handset: we assume an average HSCSD session of 0.25Mbyte assume 1.1 session attempts per session assume the same MSC/VLR processing per session as an outgoing voice call attempt (20ms) 78 The model Network design Additional allowance for the distribution of traffic is made, over and above the use of area types The model currently contains four area types (urban, suburban, rural, highway) in order to distribute traffic load across the country in a sensible fashion However, within each area type, demand will be distributed non-homogeneously (both in time and space), and an allowance for this is included The requirement for half an additional unit of capacity at each point in the network was calculated by Analysys using a network simulation tool Area type Diagrams not to scale Area type Highway Suburban Urban Non-homogeneous reality erlangs per sector Highway Rural Suburban Urban erlangs per sector Simplified average situation Rural to account for this effect, an additional ½ TRX is deployed on each sector Additional capacity requirement over the average 79 The model Network design Equipment utilisation is an important input parameter to the network design algorithms A large number of network design calculations are based upon the following relationship: number of items required = demand / capacity per item * utilisation The utilisation parameter contained in the Oftel model is used to reflect the explicit combination of a number of different ‘under-utilisation’ effects: Design utilisation: most equipment has a (vendor designated) maximum utilisation parameter (for example, 90%). This utilisation parameter ensures that the equipment in the network is not overloaded by any transient spikes in demand Scorched node utilisation: the deployment of a scorched node network is captured explicitly by the use of additional utilisation parameters. These indicate the degree to which equipment is unable to reach the level of utilisation that would be achieved in a scorched earth deployment, as a direct result of adhering to the scorched node constraint Reasonable growth utilisation: in a real mobile network, equipment is deployed in advance of expected demand (weeks to years), depending on the equipment modularity and the time it takes to make all the necessary preparations to bring new equipment online. The model explicitly determines the level of under-utilisation in the network, as a function of equipment planning periods and expected demand. 80 The model Network design Reasonable growth utilisation parameters are calculated explicitly Explicit inputs relating to the provision of a reasonable allowance for future growth enable the effect on average equipment utilisation to be calculated This is done for a number of asset classes, by choosing: the key demand driver which is to be used in determining future growth in demand the point in the future at which demand should be considered – The future demand point for each asset class is taken to be half of one planning period in the future, based on the simple assumption that some sites will have only just been upgraded (and hence have sufficient capacity to meet demand anticipated one entire planning period into the future) whereas other sites will be about to be upgraded (and therefore are only able to meet current demand), with most sites lying somewhere in between these two extremes (and hence on average the effect is likely to be as if all sites have sufficient capacity to meet demand for about half of one planning period into the future) The model contains a forecast of demand over time, which is then used in the calculation of the reasonable growth utilisation 81 The model Network design Calculation method for reasonable growth utilisation Assign a key driver to each class of infrastructure, e.g. demand: define planning period (2p), and determine demand at time half planning period later: = xt / (capacity * normal utilisation) Number of elements deployed at time t+p, if no future growth: (demand at time t + p ) = xt+p Number of elements deployed at time t, if no future growth: (demand at time t) = xt Demand = xt+p / (capacity * normal utilisation) Hence actual utilisation of elements at time t, given forward looking deployment is: xt+p / (capacity * normal utilisation) = xt / (capacity * actual utilisation) hence: – actual utilisation = normal utilisation * (xt / xt+p) normal utilisation = design utilisation * scorched node utilisation allowance t t+p time 82 The model Network design An example of maximum utilisation Macrocell BTS: design utilisation input at 80% scorched node allowance input at 90% Due to the inefficiencies which arise as a result of scorched node (compared to scorched earth) BTSs are not able to reach their designed utilisation Reasonable growth driver set to “traffic” The main driver of the deployment of BTSs is traffic Look-ahead selected as 2 years ahead Traffic in two years time is 60% higher than today’s traffic, hence Vendor says “do not run a BTS at more than 80% peak capacity” reasonable growth allowance = 1/1.6 = 63% Calculated maximum utilisation of a macrocell BTS is thus: 80% * 90% * 63% = 45% BTSs (sites) have a long planning period 83 The model Network design For each asset class, the key demand driver and period of planning must be selected Asset classes TRX BTS – macro, micro and pico backhaul links Key demand drivers Look-ahead period Year average subs Current time Year total incoming minutes 2 weeks ahead Year total outgoing minutes 1 month ahead Year total SMS messages 1 quarter ahead Year total GPRS Mbytes 6 months ahead Year total HSCSD Mbytes 1 year ahead BSC BSC-MSC transmission MSC/VLR – CPU and ports HLR Inter-switch transmission Year average GPRS users 2 years ahead SMSCs Year total minutes 3 or more years ahead PCU Year total approx traffic GSNs – connections and peak throughput IP transmission 84 The model Network design The model also explicitly calculates the output utilisation profiles required for the economic depreciation calculations The economic depreciation calculations require equipment utilisation profiles (taken into account when calculating economic life and distributing the cost of an asset over its lifetime) These profiles are calculated for a number of classes of equipment in the model The reasonable growth utilisation factor is not taken into account in the determination of output utilisation since these assets are deployed in advance of the demand they will support 100% utilisation Design utilisation allowance Scorched node utilisation allowance 100% y Actual out-turn utilisation x(t) Output utilisation profile for economic depreciation is x(t) / y time 85 The model Network design flow diagrams The following slides provide details of the network design algorithms: flow diagrams explanatory sections relating to these flow diagrams Input parameter (data or assumption) Calculation Major equipment deployment output Network design 86 The model Network design Base station sites Maximum cell radii Spectrum Reuse TRX bandwidth Spectral capacity of a sector Area to cover Maximum cell area Non-uniform allowance (0.5 TRX/sector) BTS and TRX unit capacity Maximum achievable capacity of a sector Utilisation of TRX and BTS Effective capacity of a sector TRX Traffic (BHE) Sectors required for capacity Site type proportions Sites (by type) required for capacity Sites required for coverage Number of sites (by type) used in TRX calculations 87 The model Network design Base station sites (2) Maximum cell radii Spectrum Reuse TRX bandwidth Spectral capacity of a sector Spectrum, reuse and TRX bandwidth are Maximum cell Area towell cover reasonably area defined parameters Non-uniform allowance (0.5 TRX/sector) BTS and TRX unit capacity Maximum achievable capacity of a sector Utilisation of TRX and BTS Effective capacity of a sector The non-uniform allowance is the ½ unit TRX Traffic (BHE) of capacity per sector allowanceSectors for the required for capacity fact that traffic is not evenly distributed (in both time and space) across each area type Sites (by type) required for Site type proportions capacity Sites required for coverage Number of sites (by type) used in TRX calculations 88 The model Network design Base station sites (3) Spectrum Different cell radii are used for each area type, and for GSM 900 and GSM 1800. Reuse TRX traffic is the (routeing weighted*) sum of all the traffic types, allocated to each area The area to cover is again TRX bandwidth Spectral capacity a sector and cell type using percentage inputs by area type,ofand in terms of 2 km Site type proportions are simplified Maximum cell radii Area to cover Maximum cell area Non-uniform assumptions for: allowance (0.5 TRX/sector) • all urban and suburban as tri-sectored • all BTS highway bi-sectored and as TRX unit capacity • all rural as omni-sectored Maximum achievable capacity of a sector • micro and pico sites are defined as omni-sectored Utilisation of TRX and BTS Effective capacity of a sector TRX Traffic (BHE) Sectors required for capacity Site type proportions Sites (by type) required for capacity Sites required for coverage Number of sites (by type) * routeing weighted: for example, one on-net mobile-to-mobile minute has two used in TRX calculations contributions to TRX BHE 89 The model Network design Base station sites (4) Maximum cell radii Spectrum Reuse TRX bandwidth Spectral capacity of a sector Area to cover Maximum cell area Non-uniform allowance (0.5 TRX/sector) BTS and TRX unit capacity Utilisation of TRX and BTS TRX Traffic (BHE) Site type proportions Maximum achievable capacity of a sector The number of sites Effective a sector deployedcapacity (for eachofarea and cell type) is determined as the greater of those required for coverage or traffic Sectors required for capacity Sites (by type) required for capacity Sites required for coverage Number of sites (by type) used in TRX calculations The model 90 Typical results of Base station site calculations Network design 91 The model Network design TRXs Number of sites Sectors per site (by site type) Number of sectors TRX traffic (BHE) Traffic per sector (BHE) TRX unit capacity and utilisation TRXs per sector to meet traffic requirements from Sites calculations Non-uniform allowance (0.5 TRX per sector) Minimum TRXs per sector Number of TRXs per sector Number of TRXs (all sectors) used in Site–BSC transmission calculations used in BSC calculations 92 The model Network design TRXs (2) Number of sites Sectors per site (by site type) TRX traffic (BHE) TRX unit capacity and utilisation from Sites calculations Number of sectors These assumptions areTraffic the same per sector (BHE) as used in the BTS calculations TRXs per sector to meet traffic requirements Non-uniform allowance (0.5 TRX per sector) Minimum TRXs per sector The minimum TRX deployment Number of TRXs per sector is 1 TRX per sector Number of TRXs (all sectors) used in Site–BSC transmission calculations used in BSC calculations 93 The model Network design TRXs (3) Number of sites from Sites calculations Sectors per site (by site type) Number of sectors TRX Traffic (BHE) Traffic per sector (BHE) TRX unit capacity and utilisation TRXs per sector to meet traffic requirements The final number of TRXs is again calculated in response to coverage requirements (driven by the number of sites) and traffic requirements (driven by the amount of traffic per sector) Number of TRXs per sector Number of TRXs (all sectors) used in Site–BSC transmission calculations used in BSC calculations Non-uniform allowance (0.5 TRX per sector) Minimum TRXs per sector The model 94 Typical results of TRX calculations Network design 95 The model Network design Base station site – BSC transmission Number of TRXs per sector Required circuits per TRX Required circuits per sector Sectors per site (by site type) Required circuits per site Link capacity (by link rate) Links required per site (by link rate) Link utilisation Links required per site (at selected link rate) Link type proportions Leased lines (by link rate) from TRX calculations Microwave links (by link rate) used in BSC calculations Hops per link Microwave hops (by link rate) 96 The model Network design Base station site – BSC transmission (2) Number of TRXs per sector Required circuits per TRX Required circuits per sector Sectors per site (by site type) Required circuits per site Link capacity (by link rate) Links required per site (by link rate) Link utilisation Links required per site (at selected link rate) Link type proportions Leased lines (by link rate) from TRX calculations Microwave links (by link rate) used in BSC calculations The number of circuits per TRX is a well known network design parameter A calculation determines the number of links of each type (2, 8, 16, 32 Mbit/s) required to support the demand … … and then deploys no more Hops link than one link perper site, selecting the required link capacity Microwave hops (by link rate) 97 The model Network design Base station site – BSC transmission (3) Number of TRXs per sector Required circuits per TRX Required circuits per sector Sectors per site (by site type) Required circuits per site Link capacity (by link rate) For example, 80% microwave self provided and 20% leased lines, specified for macro, Link utilisation micro and pico sites in each area type Link type proportions from TRX calculations Links required per site (by link rate) Links required per site (at selected link rate) Leased lines (by link rate) Microwave links (by link rate) used in BSC calculations Again, specified for macro, micro and pico sites in each area type Hops per link Microwave hops (by link rate) 98 The model Network design BSCs from TRX calculations Number of TRXs (all sectors) Number of BSCs BSC capacity Utilisation from Site – BSC calculations from BSC – MSC calculations Leased lines (by link rate) Leased lines (by link rate) Microwave links (by link rate) Microwave links (by link rate) Number of BTS-facing ports Number of MSC-facing ports Ports per link (by link rate) Ports per link (by link rate) used in BSC – MSC transmission calculations used in MSC calculations 99 The model Network design BSCs (2) from TRX calculations Number of TRXs (all sectors) from Site–BSC calculations Leased lines (by link rate) Microwave links (by link rate) from BSC – MSC calculations Leased lines (by link rate) Microwave links (by link rate) BSC deployments are simply driven by the number of TRXs deployed in the radio network Number of BSCs BSC capacity Utilisation Number of BTS-facing ports The number of BSC ports does not drive the deployment of BSCs, but the number of MSCfacing ports is taken into account in the MSC Ports per link (by link rate) dimensioning used in BSC – MSC transmission calculations Number of MSC-facing ports Ports per link (by link rate) used in MSC calculations 100 The model Network design BSC – MSC transmission Number of BSCs BSC–MSC traffic (BHE) Traffic per BSC Link capacity (by link rate) Links required per BSC (by link rate) from BSC calculations Link utilisation Links required per BSC (at selected link rate) Link type proportions Leased lines (by link rate) Microwave links (by link rate) used in BSC calculations Hops per link Microwave hops 101 The model Network design BSC – MSC transmission (2) Number of BSCs BSC – MSC traffic (BHE) Traffic per BSC BSC – MSC is again a Linktraffic capacity (routeing (by weighted) sum of all link rate) traffic types passing from BSC to MSCs Link utilisation Links required per BSC (by link rate) from BSC calculations Links required per BSC (at selected link rate) Link type proportions Leased lines (by link rate) Microwave links (by link rate) used in BSC calculations Hops per link Microwave hops 102 The model Network design BSC – MSC transmission (3) BSC–MSC traffic (BHE) These calculations are similar Number ofbase BSCsstation to those used for site – BSC transmission, though involve different assumptions where appropriate Traffic per BSC Link capacity (by link rate) Links required per BSC (by link rate) from BSC calculations Link utilisation Links required per BSC (at selected link rate) Link type proportions Leased lines (by link rate) Microwave links (by link rate) used in BSC calculations to define number of MSC-facing ports required (but not the number of BSCs) Hops per link Microwave hops 103 The model Network design MSCs from BSC calculations Interconnect traffic (BHE) Number of MSC-facing ports Minimum interconnect ports MSC capacity (ports) Number of BSC-facing ports Switch port capacity Number of MSCs required to meet demand for ports Switch port utilisation Minimum MSCs Number of interconnect-facing ports CPU capacity (BHms) Total number of ports CPU utilisation Interswitch traffic (BHE) MSC capacity (CPUs) Number of interswitch ports Processing demand (BHms) Switch port capacity Switch port utilisation Number of MSC/VLRs used in MSC transmission calculations 104 The model Network design MSCs (2) Interconnect traffic (BHE) from BSC calculations Number of MSC-facing ports Minimum interconnect ports MSC capacity (ports) Number of BSC-facing ports Number of MSCs required to meet demand for ports Minimum MSCs CPU capacity (BHms) Switch port capacity Switch port utilisation MSC/VLRs are deployed in response to the Number of interconnect-facing CPU processing requirements of the network, ports generated by a number of services and processes, including: number of ports • subscriberTotal authentication CPU utilisation MSC capacity (CPUs) • incoming and outgoing circuit switched call set-ups • SMS message send and delivery Number of interswitch ports • subscriber location updating Processing demand (BHms) Interswitch traffic (BHE) Switch port capacity Switch port utilisation Number of MSC/VLRs used in MSC transmission calculations 105 The model Network design MSCs (3) Interconnect traffic (BHE) from BSC calculations Number of MSC-facing ports Minimum interconnect ports MSC capacity (ports) Number of BSC-facing ports Number of MSCs required to meet demand for ports Switch port capacity Switch port utilisation Minimum MSCs Number of interconnect-facing ports CPU capacity (BHms) Total number of ports CPU utilisation Interswitch traffic (BHE) In addition, the number of MSCs should also have sufficient capacity to support Number of demands. interswitch ports port MSC capacity (CPUs) Switch port capacity However, this link is not automatic in the model, and must be completed with a Switch port utilisation manual check. Processing demand (BHms) Number of MSC/VLRs used in MSC transmission calculations 106 The model Network design MSCs (4) from BSC calculations The number of ports are summed up from the three major types of ports MSC present incapacity the MSC(ports) Interconnect traffic (BHE) Number of MSC-facing ports Minimum interconnect ports Number of BSC-facing ports Switch port capacity • each MSC-facing port in a BSC Number requires a reciprocal port in of theMSCs MSC required to meet demand for ports • interconnect ports are driven by interconnect traffic (routeing weighted MSCs sum of Minimum all relevant traffic types), capacity and utilisation inputs • there may be a contractual CPU capacity (BHms) QoS minimum requirement for the number of interconnect ports CPU utilisation • interswitch ports are also driven by interswitch traffic (routeing weighted sum of allMSC relevant traffic types), capacity and capacity (CPUs) utilisation inputs Switch port utilisation Number of interconnect-facing ports Total number of ports Interswitch traffic (BHE) Number of interswitch ports Processing demand (BHms) Switch port capacity Switch port utilisation Number of MSC/VLRs used in MSC transmission calculations The model 107 Network design Interswitch transmission Number of interswitch ports Transmission utilisation Number of interswitch circuits from MSC calculations The model 108 Network design Interswitch transmission (2) Number of interswitch ports Transmission utilisation Number of interswitch circuits from MSC calculations The number of interswitch ports is simply driven by the number of interswitch ports (which was in itself driven by the amount of interswitch traffic) 109 The model Network design HLR capacity HLR capacity Minimum number of HLRs Number of HLRs Number of customers HLR utilisation Number of HLR upgrades HLR upgrade capacity 110 The model Network design HLR capacity (2) HLR capacity Minimum number of HLRs Number of HLRs Number of customers HLRs are again driven by a simple calculation involving capacity, demand and utilisation. However, at least two HLRs are required, at minimum, for redundancy HLR utilisation Number of HLR upgrades HLR upgrade capacity 111 The model Network design HLR capacity (3) HLR capacity Number of customers Minimum number of HLRs Capacity upgrades to the HLRs are deployed, however the full Number costofofHLRs a HLR is assumed in the base HLR, and hence HLR upgrades do not impact the cost results HLR utilisation Number of HLR upgrades HLR upgrade capacity 112 The model Network design Typical results of BSC, MSC and HLR calculations 140 120 100 80 BSCs MSCs HLRs 60 40 20 0 93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03 113 The model Network design SMS centres Minimum number of SMSCs SMS throughput demand SMSC throughput capacity Utilisation Number of SMSCs 114 The model Network design SMS centres (2) Minimum number of SMSCs SMS throughput demand SMSC throughput capacity Utilisation SMS throughput demand is again a routeing weighted sum of all SMS types: • Mobile originated (MO) off-net Number of SMSCs • MO on-net • MT • server originated (voicemail, info-service, etc) 115 The model Network design Dedicated GPRS equipment – PCU boards from BSC calculations Number of BSCs GPRS MB throughput demand PCU throughput capacity Number of PCUs by throughput Number of PCUs by 1 per BSC minimum Utilisation Number of PCUs 116 The model Network design PCU boards (2) GPRS MB throughput demand PCU throughput capacity The number of PCUs deployed (packet control unit upgrades to from BSC calculations BSCs) is calculated as the greater of capacity demands or Number of BSCs one per BSC Number of PCUs by throughput Number of PCUs by 1 per BSC minimum Utilisation Number of PCUs 117 The model Network design Dedicated GPRS equipment – GGSNs GPRS MB throughput demand Active GPRS PDP contexts GGSN throughput capacity GGSN PDP context capacity Throughput utilisation PDP context utilisation Number of GGSNs by throughput Minimum number of GGSNs Number of GGSNs by PDP contexts Number of GGSNs 118 The model Network design GGSNs (2) GPRS MB throughput demand GGSN throughput capacity The greatest of three requirements are taken into account when calculating the number of GGSNs deployed: • at least two for redundancy Active GPRS PDP contexts GGSN PDP context capacity • throughput traffic requirements Throughput utilisation • PDP context (IP address) requirements Number of GGSNs by throughput Minimum number of GGSNs PDP context utilisation Number of GGSNs by PDP contexts Number of GGSNs 119 The model Network design Dedicated GPRS equipment – SGSNs GPRS MB throughput demand Connected GPRS subscribers SGSN throughput capacity SGSN subscriber capacity Throughput utilisation Subscriber utilisation Number of SGSNs by throughput Minimum number of SGSNs Number of SGSNs by subscribers Number of SGSNs 120 The model Network design SGSNs (2) GPRS MB throughput demand SGSN throughput capacity The greatest of three requirements are also taken into account when calculating the number of SGSNs deployed: • at least two for redundancy Connected GPRS subscribers SGSN subscriber capacity • throughput traffic requirements Throughput utilisation • GPRS subscriber requirements Number of SGSNs by throughput Minimum number of SGSNs Subscriber utilisation Number of SGSNs by subscribers Number of SGSNs 121 The model Network design Dedicated GPRS equipment – IP transmission GPRS IP Mbit/s Number of IP transmission 2Mbit/s links Transmission utilisation 122 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 123 The model Economic Depreciation The problem How would an operator set its prices if it were operating in a (hypothetical) fully competitive and partially contestable market? So as to neither under- nor over-recover costs, since: – they would not enter if costs could not be fully recovered – they would be prevented from over-recovery of costs by competition Consistent with changes in the underlying costs of production and the contestability of the market, since: – they will set their prices in line with those that a new entrant into the market at each point in time would charge Traditional depreciation methods, such as straight-line or reducing balance depreciation, can achieve the first of these requirements, but not in general the second. Economic depreciation can achieve both. 124 The model Economic Depreciation Competitiveness vs Contestability Competitiveness describes the extent to which operators already in the market compete with each other (and thereby control each others behaviour): A fully competitive market is one in which there are at least two (non-collusive) players and no customer switching costs – customers can (and will) instantaneously switch from one provider to another if a better deal is on offer Contestability describes the ease with which operators can enter (and exit) the market (and thereby control the behaviour of those already in the market): A fully contestable market has no barriers to entry and exit – a new entrant can enter the market and capture all of an incumbent’s existing customers instantaneously if they offer a better deal A partially contestable market has barriers to entry and exit – new entrants into the market can only capture customers from the incumbent after some delay (for example the time necessary to roll out their network) and/or at some limited rate (for example because of the need to build up their reputation and brand image) 125 The model Economic Depreciation What difference does it make whether a market is fully or only partially contestable? In a fully contestable market, incumbents (players already in the market, irrespective of the date they entered, or their scale) can never set prices higher than what it would cost a new entrant to provide the same service, using the most efficient means, since: If they were to do so, new players would enter, set lower prices, and capture the entire market (NB This is true even if the incumbent is a monopoly!) In a less than fully contestable market, incumbents may be able to temporarily sustain prices that are higher than what it would cost a new entrant to provide the same service, using the most efficient means, to the same number of customers as the incumbent, since: It will take time for the new entrant to be ready to capture all of the incumbents’ customers And so in the mean time the new entrant’s cost per customer will be higher than it would be if they had instantaneously captured the entire market 126 The model Economic Depreciation Why then can’t incumbents in a less than fully contestable market over-recover their costs? They can if the market is less than fully competitive! But if the market is fully competitive (or assumed to be), competition between the incumbents will ensure that prices overall (over the lifetime of the product) are no higher than the costs of production, since if any one incumbent attempted to set a price, at any time, that was higher than the competitive level, they would instantaneously lose all of their customers to their competitors. In a fully competitive market it is therefore only the timing of the recovery of costs that differs between scenarios of full and partial contestability, not the total amount of cost recovered: If the market is fully contestable, operators have to recover costs in each year from the customers making use of the service in that year, which in theory would lead to very high prices in the early years of operation If the market is less than fully contestable then operators can keep prices at a reasonable level in the early years, albeit with a compensatory but small increase in prices in later years 127 The model Economic Depreciation Why model a less than fully contestable market? Mobile markets are in practice less than fully contestable: Significant up-front investment in network roll-out is required before any customers can be signed up It took time for mobile operators to build up the market for mobile services If the mobile operators had set prices commensurate with a fully contestable market in the early years those prices would have been very high, in which case the market would probably have never developed If mobile operators are now forced to set prices as if the market were fully contestable then they will never fully recover the costs of their initial investments (they will suffer a so-called “windfall loss”) 128 The model Economic Depreciation The economic depreciation problem restated What time-series of prices, consistent with trends in the underlying costs of production and the assumed contestability of the market, yield an expected NPV of zero over the period of interest? An NPV of zero ensures that the prices are cost-based, as they would have to be in a fully competitive market, neither under- nor over-recovering total costs over the lifetime of the project Consistency of prices with trends in the underlying costs of production and assumed contestability of the market ensure that those prices are reflective of those that a (hypothetical) new entrant into the market at each point in time would charge 129 The model Economic Depreciation The inputs Expenditure 1000 100% 800 80% 600 60% 400 40% Output (utilisation) Underlying cost trend (capital and opex combined) Capital investment 200 20% Operating expenses 0 0% 0 1 2 3 4 5 6 7 Year of life 8 9 10 11 12 130 The model Economic Depreciation First calculate the total expenditure… Expenditure (We will initially assume a lifetime of 10 years) 1800 1800 1600 1600 1400 1400 1200 1200 1000 1000 800 800 600 600 400 400 200 200 0 0 0 1 2 3 4 5 6 7 Year of life 8 9 10 11 12 Capital investment Operating expenses PV of total expenditure (up to year 10) 131 The model Economic Depreciation …then calculate the total relative output value (assuming the same lifetime of 10 years) 350% 350% 300% 300% 250% 250% Output (utilisation) 200% 200% Underlying cost trend (capital and opex combined) 150% 150% Relative output value 100% 100% PV of total relative output value (up to year 10) 50% 50% 0% 0% 0 1 2 3 4 5 6 7 Year of life 8 9 10 11 12 132 The model Economic Depreciation Divide one by the other to yield the unit price for a relative output value of 100% 334% 1644 492 PV of total expenditures PV of total relative output value Unit price at 100% output value 133 The model Economic Depreciation Multiply this by the relative output value in each year to yield annual revenues 500 90% 450 80% 400 70% 350 60% 300 50% Unit price at 100% output value Relative output value 250 40% 200 Revenue 30% 150 100 20% 50 10% 0 0% 0 1 2 3 4 5 6 7 Year of life 8 9 10 11 12 134 The model Economic Depreciation Economic depreciation is then the difference between revenues and operating expenses Economic lifetime = last year in which economic depreciation is positive 500 400 Check that this matches with earlier assumption 300 200 Revenue 100 Economic depreciation Operating expenses 0 -100 -200 0 1 2 3 4 5 6 7 Year of life 8 9 10 11 12 135 The model Economic Depreciation Check that everything is consistent! 1,800 1,600 1,400 1,200 1,000 800 600 400 200 0 PV of total revenues Revenues PV of total annualised costs Operating expenses Economic depreciation PV of total expenditures Capital investment 136 The model Economic Depreciation Notes re implementation in the LRIC Model of UK Mobile Network Costs [1] Model considers a period of interest longer than one asset lifetime: Includes investment necessary to replace assets at the end of their useful life Uses perpetuities to model the period beyond the finite horizon of the explicit calculations This is economically rational in a less than fully contestable market since operators invest for the long term, not merely to obtain customers for the lifetime of each individual asset 137 The model Economic Depreciation Notes re implementation in the LRIC Model of UK Mobile Network Costs [2] Model calculates “revenue required” separately for capital investment and operating expenses Simplifies modelling of separate underlying cost trends for capital costs (MEA prices) and operating expenses Operating expenses are assumed to vary both with time and age of asset 138 The model Economic Depreciation Notes re implementation in the LRIC Model of UK Mobile Network Costs [3] Model computes “revenue required” separately for each of three components of total cost: Long-run equilibrium costs – based on long-run equilibrium input prices and output Additional costs of lower output in earlier years Additional costs of higher input prices in earlier years Makes it easier to ensure that the “underlying cost trend” is consistent with the assumed evolution of the market 139 The model Economic Depreciation Notes re implementation in the LRIC Model of UK Mobile Network Costs [4] The “underlying cost trend” applied in each case is different reflecting the different forces at work in each case: Long-run costs = long-run input cost trend Costs of lower output = Extent to which later entrants achieve long-run output more quickly than do earlier ones Costs of higher input prices = Extent to which earlier entrants have to pay input prices higher than those implied by the long-run trend 140 The model Economic Depreciation Notes re implementation in the LRIC Model of UK Mobile Network Costs [5] Model tracks history of UK operators to date, together with a forecast of their likely future development Would be equally valid to model the future of a new entrant into the market today (or any other date), but: This would entirely disconnect the model from the reality of the incumbent operators (who are the ones whose charges are to be regulated) Makes the model and results entirely dependant upon forecasts Results ought to be the same anyway, since the objective of the approach is to identify that set of prices which an incumbent would charge which are consistent with those that new entrants would charge 141 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions The model 142 Network costing Network costing is the multiplication of economic cost per item and network deployment per item Economic cost for each item Coverage network deployment Coverage network cost + Incremental network deployment Incremental network cost = Full network deployment Full network cost 143 The model Network costing A number of business activities are included either directly or indirectly in the network costs Included explicitly as direct costs: equipment, site rentals, switch software, building preparation network management Included as indirect costs, per unit of infrastructure: maintenance accommodation, power, vehicles and IT 144 The model Network costing A number of similar calculations produce coverage, incremental and total costs Economic cost per item x Total Incremental Total Incremental MCP MCP Number of items deployed Total cost for each item = 1 1 1 2 2 2 3 3 3 … … … Total cost The simple multiplication of economic cost per item and equipment deployments produces the headline total costs: coverage network cost, defined as just the MCP incremental network cost (which includes the equipment designated as coverage capacity) total network cost 145 The average incremental cost per unit output of each network element is simply the incremental cost of each network element divided by its output Demand by service 1 2 3 … x Incrementalc ost of each network element 1 Routeing factors = Average incrementalc ost per unit output of each network element 2 1 3… 2 3… = Output of each network element 146 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 147 The model Service costing The matrix of routeing factors is key to the allocation of incremental costs to services Routeing factors* Average incremental cost per unit output of each network element Unitised incremental cost per service Common costs of coverage Mark-ups to recover common costs * Routeing factors defined below 148 The model Service costing Routeing factors are relative numerical weightings for the consumption of resources by services Routeing factors = Capacity of each network element required by each service (per unit of demand) 149 The model Service costing The axes of the routeing factor matrix are services and network elements OG on-net mins SMS messages 1 1 2 0.01 BSC 1 1 2 0.01 HLR MSC/VLR 1 1000 etc OG off-net mins 3-sector macro Assets Customers Incoming mins Services Each network cost must be allocated to one or more services, according to the consumption of resources The allocation of certain network costs to particular increments may be varied, provided there is a good reason for allocating such a cost to a different service increment than that used to drive the cost. For example: 50 20 70 etc * Illustrative routeing factors; OG = outgoing the costs of location updates could be allocated to customers or traffic, depending on whether location updates were seen as a feature applicable to subscribers or calls 150 The model Service costing The output of the service costing calculation is unitised incremental service costs Average incrementalc ost per unit output of each network element x Routeing factors = Unitised incremental cost per item, for service 1 1 1 2 2 3… 3… Total unitised incremental cost for service 1 Unitised Unitised Unitised incremental Unitised incremental Unitised incremental cost per incremental cost per incremental cost per item, for cost per item, for cost per item, for service 2 item, for service 2 2for item, service service 22 service 11 11 1 22 22 2 3… 3… 3… 3… 3… … … Unitised incremental cost per item, for service 8 1 2 3… Total unitised incremental cost for service 8 151 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions 152 The model Results The key outputs of the model are unitised and total costs For each year of calculation: customers incoming calls outgoing calls etc Total cost of Coverage MCP represents the unitised cost for one customer, number of boxes indicates the number of customers represents the unitised cost for one incoming minute, number of boxes indicates the annual number of minutes represents the unitised cost for one outgoing offnet minute, number of boxes indicates the annual number of minutes 153 The model Results The costs of the coverage network must be recovered (marked-up) from the services Equal proportionate LRIC Customers Mark-up Coverage MCP Traffic Outgoing Incoming SMS… Premium on mobility LRIC Coverage MCP Customers Mark-up Traffic Traffic Outgoing Incoming SMS… The economically optimal method of mark-up utilises Ramsey pricing economics: a larger mark-up is applied to services with a lower elasticity to price change this is complex and requires knowledge or assumptions about service elasticity A number of simpler approaches may be taken, for example: LRIC Customers Mark-up Coverage MCP Attributable to access Traffic Outgoing Incoming SMS… equal proportionate, as selected by Oftel: markup is applied to all the incremental costs (a proxy for simplified Ramsey pricing) ‘premium on mobility’: coverage costs are seen as attributable in equal proportionate terms to customers and outgoing call minutes attributable to access: coverage costs are seen as entirely attributable to customers NB In all cases the relevant mark-up is calculated and applied as a percentage increase on the raw incremental cost of some or all of the services 154 The model Results We discuss four key sensitivities A Modifying service routeing factors D Reducing the price of (modern equivalent) equipment Base model Increasing long term growth in demand Modifying network design parameters C B The model 155 Results Sensitivity – service routeing factors A Modifying service routeing factors Base model the economic cost of the equipment required to support demand is allocated to each service in proportion to the consumption of each resource – new routeing factors will redistribute costs across the relevant services, and impact the outcome of common cost mark-up The model 156 Results Sensitivity – long term demand Base model Increasing long term growth in demand B algorithms in the model deploying equipment in advance of future demand would bring forward deployments - reducing the average utilisation of equipment The model 157 Results Sensitivity – network design parameters network design algorithms would respond to new parameter values, ensuring appropriate deployments and, for example, impacting the economies of scale present in parts of the network – impacting the evolution of network utilisation as these economies of scale are exhausted Base model Modifying network design parameters C 158 The model Results Sensitivity – equipment prices D Reducing the price of (modern equivalent) equipment Base model economic depreciation algorithms take into account the expected prices of equipment in the future – will increase the recovery of costs in earlier years, as the price of equipment in future years is expected to be lower 159 Executive summary Introduction to LRIC modelling Background to the Oftel model The model: Cost drivers Services and increments Demand forecasts Network design Economic depreciation Network costing Service costing Model results Conclusions Conclusions 160 The 2001 Oftel model was developed over a long period of time The Oftel model contains a number of very specific features which have been tailored to meet the needs of the consultation process in the UK, including a specific variant of economic depreciation Iterative processes with Oftel and the industry working group meant that a large number of complex calculations have been added or refined in the model, often as a reactionary measure to the demands of the industry working group Conclusions 161 A number of lessons can be derived from our LRIC modelling experience Use of a single increment for all traffic is necessary if the model is to be manageable Understanding how new services will be reflected in the model (and potential corresponding regulation) should be defined early in the process Ensuring that the model contains enough fidelity to capture key areas in sufficient detail, yet is concise enough to be understandable and workable, is critical