[30/1/02 -02] the lric model of uk mobile network costs, developed for oftel by analysys, september...
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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
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
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)
Executive summary
4
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
Executive summary
5
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
6
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
Introduction
8
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
9
Oftel was required to consider a range of issues when setting interconnect prices
Prices
Pricing methode.g. LRIC, LRIC+ Costs
Other factorse.g. externalities
Costing methode.g. forward-looking
economic costs
Datae.g. unit
input costs
Assumptionse.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
Prices
Pricing methode.g. LRIC, LRIC+ Costs
Other factorse.g. externalities
Costing methode.g. forward-looking
economic costs
Datae.g. unit
input costs
Assumptionse.g. demand
forecasts
Illustration ofalternativesnot policy
Background
11
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)
Background
12
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
Background
13
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:
subscribers
minutes of use (incoming, outgoing, on-net)
data service take-up (subscribers, technologies, megabytes of use)
Network deployment forecasts required time series for:
demand drivers (e.g. busy hour traffic proportions)
network design parameters (e.g. traffic by cell type)
equipment unit costs
Background
14
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
15
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
The model
* See later section on Economic Depreciation for definition of these terms and justification of approach adopted
16
… 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
The model
17
Background to the scorched node approach
Networks develop over time in response to changes in demand (or forecast demand)
As a result of this evolutionary development, networks are rarely truly optimal for current (or currently forecast) market conditions
The location of network nodes is dictated to at least a degree by the availability of suitable sites on the ground
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)
The model Scorched node approach
18
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.
The model Scorched node approach
19
Notes re implementation in theLRIC 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
The model Scorched node approach
20
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
The model
21
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
The model
22
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)
The model
24
The model flow consists of six major building blocks; information flows from input, to calculation, to output …
Economic cost
Network design
Network element costing
Service costing
5
2
4
Forecast of demand
2000–2006
B
C E F
D
3
Cost drivers, services and increments
A
1
The model
25
… 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
Information flowData or
assumptionsCalculationsor Outputs
Major elements
Legend
The model
26
A. Cost drivers, services and increments
Define how the increments will interact
Define what the drivers of cost are
Define the associated services
and increments
Cost drivers, services and increments
The model
27
B. Forecast of demand 2000–2006
S-curvepenetration
Minutes per sub
MByte user penetration
2G/3G partition
2/2.5/3G partition
MByte per sub
SMS penetrationSMSs per
user
2G incomingminutes
2G outgoingminutes
SMS volumesGPRS users
HSCSD MBytes
GPRS MBytes
Market shares
Mobile subscribers
Forecast of demand
The model
28
1. Cost drivers and demand forecasts to network design
Year average mobile subscribers
Year total incoming minutes
Year total outgoing minutes
Year total SMS messages
Year average GPRS users
Year total GPRS Mbytes
Year total HSCSD Mbytes
Network design
Select year:00/0101/02
02/03…
Select operator:GSM 900,GSM 1800
Forecast of demand
2000–2006
Cost drivers, services and increments
The drivers of cost
The model
29
C. Network design
Coveragenetworkdesign
Fullnetworkdesign
Incrementalnetworkdesign
Demand inputs
Selected year
Design parameters
Coverage
Selected operator
The model
30
2. Network design to economic cost
Network design
Selected year
Economic costSelected operator
Out-turn utilisation profiles
The model
31
D. Economic cost
Economic lifetime
Annualisationpercentage
Selected year
Selected operator
Out-turn utilisation profiles
* Calculation performed for each item
Economic cost
calculation
00/01 MEA capex
Opex trends
00/01 MEAopex
Capex trends
The model
32
3. Network design to network element costing
Network design
Coverage network deployment
Network element costing
Incremental network deployment
Full network deployment
The model
+
=
33
4. Economic cost to network element costing
Economic cost Economic cost for each item Network element costing
The model
34
E. Network element costing
Coveragenetwork
cost
Incrementalnetwork
cost
Full networkcost
Full network deployment
Economic cost for each item
Coverage network deployment
Incremental network deployment
The model
+
=
35
5. Network element costing to service costing
Network element costing
Common costs of coverage
Service costing
Average incremental cost of each network element per unit output
The model
36
F. Service costing
Mark-upsto recovercommon
costs
Unitised incremental
cost per service
Common costs of coverage
Average incremental cost of each network element per unit output
Routeing factors
The model
37
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
38
We assume four primary cost drivers
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
Define how the increments will interact
Define what the drivers of cost are
Define the associated
services and increments
Cost drivers, services
and increments
The model Cost drivers
39
Coverage requirements are defined in terms of population and area coverage
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):
converting population coverage into area requirements usually requires detailed demographics
We define a number of area types that effectively capture the broad range of radio environments in a country. In the UK, we used:
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
100%
100%
90%
60%
Urban
Sub
urban
Rural
Highway
Area
Pop
ulat
ion
The model Cost drivers
40
Notes re implementation in theLRIC 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
The model Cost drivers
41
Customer-driven costs are not significant ...
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
Hence, the model contains the (year average) number of subscribers as a driver
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 mark-up regime
Similarly, the (year average) number of subscribers is used to drive handset costs
HandsetsInfrastructure related
The model Cost drivers
42
... whereas traffic and quality of service are significant cost drivers
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 on-net 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 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
Quality of serviceTraffic
The model Cost drivers
43
What is the significance of orthogonal and parallel services?
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)
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
dedicated costs also occur for each service, where appropriate
For example, two drivers of cost, each with a corresponding service increment:
HLR – for customers only TRX – for traffic only
TRX – for voice traffic TRX – for GPRS traffic
GGSN – for GPRS only
The model Cost drivers
44
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:
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
Resolving the common and incremental costs associated with each increment absolutely is a complex algebraic calculation and a time consuming process:
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
The model Cost drivers
45
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 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
Services
Coverage
Traffic
Busy hour total traffic load
Busy hour call attempts
Peak SMS throughputCustomers
Cos
ts
Number of location updates
Cov
erag
eIn
crem
enta
l
The model Cost drivers
46
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
47
Define how the increments will interact
Define what the drivers of cost are
Define the associated
services and increments
Cost drivers, 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
The handset increment can be considered separately from (i.e. is orthogonal to) the other increments
Handsets
Customers
Mobile originated off-net minutes
Mobile originated on-net minutes
Mobile terminated minutes
SMS messages
GPRS Mbytes
HSCSD Mbytes
The model Services and increments
48
Considering all permutations of service demand requires a large number of calculations (16 calculations for 4 increments)
Raw incremental costs
e.g. 80%
Common costs
e.g. 5%
Coverage cost
e.g. 15%
Voice
SMS
GPRSHSCSD
Coverage
Voice + SMS GPRS + HSCSDVoice +… … + GPRS
Voice +… .. + HSCSDSMS + GPRS
SMS +… .. + HSCSD
Voice + SMS + GPRS
SMS + GPRS + HSCSD
Voice + SMS + GPRS + HSCSD
Voice + SMS + … .. + HSCSD… + GPRS + HSCSDVoice +…
1,23
456
8
7
910
11
Areas are not to scaleVoice represents customers and voice minutesFully and separately resolving 8 increments would require 64 separate calculations
Incremental costs using single traffic increment
The model Services and increments
49
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:
for example, equal-proportionate?
mark-up on mark-up?
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
GPRSHSCSD
Coverage
Voice + SMS GPRS + HSCSDVoice +… … + GPRS
Voice +… .. + HSCSDSMS + GPRS
SMS +… .. + HSCSD
Voice + SMS + GPRS
SMS + GPRS + HSCSD
Voice + SMS + GPRS + HSCSD
Voice + SMS + … .. + HSCSD… + GPRS + HSCSDVoice +…
1,23
456
8
7
910
11
The model Services and increments
50
Define how the increments will interact
Define what the drivers of cost are
Define the associated
services and increments
Cost drivers, services
and increments
Hence, after investigation, we implemented a single increment for traffic in the Oftel model
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
The model Services and increments
51
In addition, the definition of the coverage network was altered …
The coverage network is required to:
support at least one incoming or outgoing voice call, anywhere within the coverage area of the network
Such a network, due to equipment divisibility, actually contains enough capacity to support many more voice calls at no additional cost
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
The model Services and increments
52
Coverage network
Minimum coverage presence
Coverage capacity
… to better reflect the relationship between capacity and cost
The coverage network was broken into two parts:
the minimum coverage presence
– network management system (NMS) and points of presence (macro site acquisition, preparation and rental)
the coverage capacity
– equipment deployed in the coverage network providing more capacity than actually required to support just one voice minute
BSCBTS
Inter-switchtransmission
BSC–MSCtransmission
Backhaultransmission
Macro-cellsite and TRXs
HLR
MSCVLR
NMS
Macro-cellsite acquisition,
preparation and rental
BSCBTS
Inter-switchtransmission
BSC–MSCtransmission
Backhaultransmission
Macro-cellBTS and TRXs
HLR
MSCVLR
NMS
The model Services and increments
53
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
The model Services and increments
54
The Oftel model is a good representation of reality and significantly more manageable than possible alternatives
Combinatorial multiple increment Single increment, MCP
Voice
SMS
GPRS
HSCSD
Coverage
Voice + SMS GPRS + HSCSDVoice +… … + GPRSVoice +… .. + HSCSD
SMS + GPRSSMS +… .. + HSCSD
Voice + SMS + GPRSSMS + GPRS + HSCSD
Voice + SMS + GPRS + HSCSD
Voice + SMS + … .. + HSCSD… + GPRS + HSCSDVoice +…
Minimum coverage presence
Voice
SMS
GPRS
HSCSD
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
The model Services and increments
55
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
56
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:
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
We primarily require a set of reasonable forecasts which will enable the model to be run, investigated and produce reasonable information:
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 Demand forecasts
57
Base case demand forecast: subscribers
The model Demand forecasts
0
10
20
30
40
50
60Jan-92
Jan-94
Jan-96
Jan-98
Jan-00
Jan-02
Jan-04
Jan-06
Jan-08
Jan-10
one 2 one
Orange
BTCellnet
Vodafone
TIW/Hutchison 3G
58
Base case demand forecast: outgoing minutes per subscriber per quarter
The model Demand forecasts
0
100
200
300
400
500
600
Oct-99 Oct-01 Oct-03 Oct-05 Oct-07 Oct-09
Vodafone BTCellnet Orange one 2 one
59
Base case demand forecast: incoming minutes per subscriber per quarter
The model Demand forecasts
0
50
100
150
200
250
Oct-99 Oct-01 Oct-03 Oct-05 Oct-07 Oct-09
Vodafone BTCellnet Orange one 2 one
60
The forecasts contain a number of inputs, calculations and outputs
S-curves, for parameters which grow to a saturation point
Simple percentages for time dependent shares or divisions
Mobile subscribers, by operator
Incoming and outgoing* voice minutes, on 2G and 3G networks
Demand parameters in each year
Quarterly growth rates, for parameters which increase or decrease in a smooth fashion
SMS messages
HSCSD, GPRS and UMTS transport service users and Mbytes of traffic
Demand parameters in future years, in order to calculate allowances for reasonable growth
Inputs take the form of:
The following demand parameters are calculated:
Outputs of the forecast are:
*outgoing voice minutes forecast includes outgoing on-net minutes
The model Demand forecasts
61
S-curves are used for parameters which grow to a saturation point
The inputs required for an s-curve are:
saturation of x
base year
x(A) at time A
x(B) at time B
Used for:
mobile market penetration
migration of voice traffic from 2G to 3G
data transport service penetration
x(t)
tA B
x(A)
x(B)
base
saturation of x
The model Demand forecasts
62
Percentage inputs are used for time dependent shares or divisions
A simple percentage is used to distribute a parameter across different categories
Used for:
market shares
Mbytes across GPRS, HSCSD and UMTS
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Jul-0
0
Jul-0
1
Jul-0
2
Jul-0
3
Jul-0
4
Jul-0
5
Jul-0
6
Jul-0
7
Jul-0
8
Jul-0
9
Pa
rtiti
on
of
Mb
yte
s b
y te
chn
olo
gy
UMTS GPRS HSCSD
Example
The model Demand forecasts
63
Quarterly growth rates are used for parameters which increase or decrease in a smooth fashion
Simple exponential growth (or decline) can be specified with a single percentage
Annual growth rates are the compound of quarterly growths:
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
x(t)
tt1 t2 t3t0
grow
th 1
grow
th 2
grow
th 3
The model Demand forecasts
64
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 operatorby technology
2G/3G
Outgoing voiceminutes
by year quarters by operatorby technology
2G/3G
SMS messages by year quarters by operator
Data transport Mbytes by year quartersby technology
HSCSD, GPRS, UMTS
Data transport users by year quartersby technology
HSCSD, GPRS, UMTSidentical for
each operator
identical for each operator
The model Demand forecasts
65
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
The model Demand forecasts
66
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
67
The Oftel model network design algorithms are based on anumber 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
The model Network design
* 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
Simplified network diagram
BSCBTS
Inter-switchtransmission
BSC–MSCtransmission
Backhaultransmission
Macro-cellsite and TRXs
HLR
MSCVLR
NMSBackhaultransmission
Micro-cell or pico-cell site
Internet
PCU
SGSN GGSN
* For the purposes of inter-switch transmission, we assume BSC, SGSN and MSC are co-located
Dedicated GPRS infrastructure
The model Network design
69
Omnimacrocell
Bi-sectoredmacrocell
Tri-sectoredmacrocell
Microcell
Picocell
We define a number of area and cell types
Six cell typesFour area types
Suburban
Urban
Highway
Rural
Tri-sectored GSM 1800 dual spectrum
overlay
The model Network design
70
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
The model Network design
71
The six cell types allow differences in network designby 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
The model Network design
72
The use of a single increment for traffic requiresservice 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
The model Network design
73
SMS and HSCSD voice equivalent erlangs (VEErl)
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
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
SMS messages
40 bytes per SMS voice channel rate of
767 bit/s
1 minute 82 SMS
HSCSD mbytes
70% channel occupancy
voice channel rate of 14.4 kbit/s
1 minute 0.135 HSCSD Mbyte
80% of user demand in the downlink
The model Network design
74
GPRS voice equivalent erlangs
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
12% additionalIP overheads
an allowance for packetised nature
1 minute 0.09 GPRS Mbyte
100% channel occupancy
voice channel rate of 9.05kbit/s (CS1)
80% of user demand in the downlink
The model Network design
75
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 Network design
76
GPRS service demand interacts with a number of dedicated and traditional GSM network infrastructure
Total GPRS BH kbit/s(+12% IP)
Downstream GPRS BH kbit/s
GGSN100
SGSN100
Downstream GPRS voice equivalent BHE
Backhaul
Air interface
IP transmission
PCU
GPRS subscribers
Dedicated GPRS infrastructure
Existing GSMinfrastructure
The model Network design
BH = busy hour
77
The HSCSD service places demands upon all traditional GSM infrastructure
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
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)
Radio and transmission MSC/VLR processing
The model Network design
78
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
to account for this effect, an additional ½ TRX is deployed on each sector
The requirement for half an additional unit of capacity at each point in the network was calculated by Analysys using a network simulation tool
erla
ngs
per
sect
or
Area type
Urb
an
Sub
urba
n
Rur
al
Hig
hway
erla
ngs
per
sect
or
Area type
Urb
an
Sub
urba
n
Simplified average situation Non-homogeneous reality
Rur
al
Hig
hway
Additional capacity requirement over the average
Diagrams not to scale
The model Network design
79
Equipment utilisation is an important input parameterto 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.
The model Network design
80
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
The model Network design
81
Calculation method for reasonable growth utilisation
Assign a key driver to each class of infrastructure, e.g. demand:
(demand at time t) = xt
define planning period (2p), and determine demand at time half planning period later:
(demand at time t + p ) = xt+p
Number of elements deployed at time t, if no future growth:
= xt / (capacity * normal utilisation)
Number of elements deployed at time t+p, if no future growth:
= 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 * (x t / xt+p)
t t+ptime
Dem
and
normal utilisation = design utilisation * scorched node utilisation allowance
The model Network design
82
An example of maximum utilisation
Macrocell BTS:
design utilisation input at 80%
scorched node allowance input at 90%
Reasonable growth driver set to “traffic”
Look-ahead selected as 2 years ahead
Traffic in two years time is 60% higher than today’s traffic, hence
reasonable growth allowance = 1/1.6 = 63%
Calculated maximum utilisation of a macrocell BTS is thus:
80% * 90% * 63%
= 45%
Vendor says “do not run a BTS at more than 80% peak capacity”
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
The main driver of the deployment of BTSs is traffic
BTSs (sites) have a long planning period
The model Network design
83
Key demand drivers
Year average subs
Year total incoming minutes
Year total outgoing minutes
Year total SMS messages
Year total GPRS Mbytes
Year total HSCSD Mbytes
Year average GPRS users
Year total minutes
Year total approx traffic
Asset classes
TRX
BTS – macro, micro and pico
backhaul links
BSC
BSC-MSC transmission
MSC/VLR – CPU and ports
HLR
Inter-switch transmission
SMSCs
PCU
GSNs – connections and peakthroughput
IP transmission
For each asset class, the key demand driver andperiod of planning must be selected
Look-ahead period
Current time
2 weeks ahead
1 month ahead
1 quarter ahead
6 months ahead
1 year ahead
2 years ahead
3 or more years ahead
The model Network design
84
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
Scorched node utilisation allowance
100%
y
x(t)
time
100% utilisationDesign utilisation allowance
Actual out-turn utilisation Output utilisation profile for economic depreciation is
x(t) / y
The model Network design
85
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
The model Network design
86
Base station sitesSpectrum
Reuse
TRX bandwidth
Utilisation of TRX and BTS
TRX Traffic (BHE)
BTS and TRX unit capacity
Site type proportions
Maximum achievable capacity of a sector
Effective capacity of a sector
Sectors required for capacity
Spectral capacity of a sector
Sites (by type) required for capacity
Maximum cell radii
Area to coverMaximum cell
area
Sites required for coverage
Number of sites (by type)
used in TRX calculations
Non-uniformallowance (0.5 TRX/sector)
The model Network design
87
Base station sites (2) Spectrum
Reuse
TRX bandwidth
Utilisation of TRX and BTS
TRX Traffic (BHE)
BTS and TRX unit capacity
Site type proportions
Maximum achievable capacity of a sector
Effective capacity of a sector
Sectors required for capacity
Spectral capacity of a sector
Sites (by type) required for capacity
Maximum cell radii
Area to coverMaximum cell
area
Sites required for coverage
Number of sites (by type)
used in TRX calculations
Non-uniformallowance (0.5 TRX/sector)
Spectrum, reuse and TRX bandwidth are reasonably well defined parameters
The non-uniform allowance is the ½ unit of capacity per sector allowance for the fact that traffic is not evenly distributed (in both time and space) across each area type
The model Network design
88
Base station sites (3) Spectrum
Reuse
TRX bandwidth
Utilisation of TRX and BTS
TRX Traffic (BHE)
BTS and TRX unit capacity
Site type proportions
Maximum achievable capacity of a sector
Effective capacity of a sector
Sectors required for capacity
Spectral capacity of a sector
Sites (by type) required for capacity
Maximum cell radii
Area to coverMaximum cell
area
Sites required for coverage
Number of sites (by type)
used in TRX calculations
Non-uniformallowance (0.5 TRX/sector)
Different cell radii are used for each area type, and for GSM 900 and GSM 1800.
The area to cover is again by area type, and in terms of km2
TRX traffic is the (routeing weighted*) sum of all the traffic types, allocated to each area and cell type using percentage inputs
Site type proportions are simplified assumptions for:
• all urban and suburban as tri-sectored
• all highway as bi-sectored
• all rural as omni-sectored
• micro and pico sites are defined asomni-sectored
* routeing weighted: for example, one on-net mobile-to-mobile minute has two contributions to TRX BHE
The model Network design
89
Base station sites (4) Spectrum
Reuse
TRX bandwidth
Utilisation of TRX and BTS
TRX Traffic (BHE)
BTS and TRX unit capacity
Site type proportions
Maximum achievable capacity of a sector
Effective capacity of a sector
Sectors required for capacity
Spectral capacity of a sector
Sites (by type) required for capacity
Maximum cell radii
Area to coverMaximum cell
area
Sites required for coverage
Number of sites (by type)
used in TRX calculations
Non-uniformallowance (0.5 TRX/sector)
The number of sites deployed (for each area and cell type) is determined as the greater of those required for coverage or traffic
The model Network design
90
Typical results of Base station site calculations
The model Network design
0
2 000
4 000
6 000
8 000
10 000
12 000
93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03
Micro
Urban Macro
Suburban Macro
Highway Macro
Rural Macro
91
TRXs
TRX traffic (BHE)
TRX unit capacity and utilisation
Sectors per site (by site type)
Minimum TRXs per sector
Number of sectors
Traffic per sector (BHE)
TRXs per sector to meet traffic requirements
Number of sites
Number of TRXs per sector Number of TRXs (all sectors)
used in Site–BSC transmission calculations
from Sites calculations
used in BSC calculations
Non-uniformallowance (0.5 TRX per sector)
The model Network design
92
TRXs (2)
TRX traffic (BHE)
TRX unit capacity and utilisation
Sectors per site (by site type)
Minimum TRXs per sector
Number of sectors
Traffic per sector (BHE)
TRXs per sector to meet traffic requirements
Number of sites
Number of TRXs per sector Number of TRXs (all sectors)
used in Site–BSC transmission calculations
from Sites calculations
used in BSC calculations
Non-uniformallowance (0.5 TRX per sector)
These assumptions are the same as used in the BTS calculations
The minimum TRX deployment is 1 TRX per sector
The model Network design
93
TRXs (3)
TRX Traffic (BHE)
TRX unit capacity and utilisation
Sectors per site (by site type)
Minimum TRXs per sector
Number of sectors
Traffic per sector (BHE)
TRXs per sector to meet traffic requirements
Number of sites
Number of TRXs per sector Number of TRXs (all sectors)
used in Site–BSC transmission calculations
from Sites calculations
used in BSC calculations
Non-uniformallowance (0.5 TRX per sector)
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)
The model Network design
94
Typical results of TRX calculations
The model Network design
0
10 000
20 000
30 000
40 000
50 000
60 000
70 000
93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03
Micro
Urban Macro
Suburban Macro
Highway Macro
Rural Macro
95
Base station site – BSC transmission
Required circuits per TRX Required circuits per sector
Link capacity(by link rate)
Links required per site(by link rate)
Number of TRXs per sector
Links required per site(at selected link rate)
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave hops (by link rate)Link type proportions
Hops per link
used in BSC calculations
from TRX calculations
Required circuits per siteSectors per site (by site type)
Link utilisation
The model Network design
96
Base station site – BSC transmission (2)
Required circuits per TRX Required circuits per sector
Link capacity(by link rate)
Links required per site (by link rate)
Number of TRXs per sector
Links required per site(at selected link rate)
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave hops (by link rate)Link type proportions
Hops per link
used in BSC calculations
from TRX calculations
Required circuits per siteSectors per site (by site type)
Link utilisation
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 than one link per site, selecting the required link capacity
The model Network design
97
Base station site – BSC transmission (3)
Required circuits per TRX Required circuits per sector
Link capacity(by link rate)
Links required per site (by link rate)
Number of TRXs per sector
Links required per site(at selected link rate)
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave hops (by link rate)Link type proportions
Hops per link
used in BSC calculations
from TRX calculations
Required circuits per siteSectors per site (by site type)
Link utilisation
For example, 80% microwave self provided and 20% leased lines, specified for macro, micro and pico sites in each area type
Again, specified for macro, micro and pico sites in each area type
The model Network design
98
BSCs
Number of TRXs (all sectors)
Leased lines(by link rate)
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave links (by link
rate)
Number of BSCs Number of MSC-facing ports
BSC capacity Utilisation
Number of BTS-facing ports
Ports per link (by link rate) Ports per link (by link rate)
used in BSC – MSC transmission calculations
used in MSC calculations
from TRX calculations from Site – BSC calculations from BSC – MSC calculations
The model Network design
99
BSCs (2)
Number of TRXs (all sectors)
Leased lines(by link rate)
Microwave links (by link
rate)
Number of BSCs
BSC capacity Utilisation
Number of BTS-facing ports
Ports per link (by link rate)
used in BSC – MSC transmission calculations
from TRX calculations from Site–BSC calculations
BSC deployments are simply driven by the number of TRXs deployed in the radio network
Leased lines(by link rate)
Microwave links (by link
rate)
Number of MSC-facing ports
Ports per link (by link rate)
used in MSC calculations
from BSC – MSC calculations
The number of BSC ports does not drive the deployment of BSCs, but the number of MSC-facing ports is taken into account in the MSC dimensioning
The model Network design
100
BSC – MSC transmission
BSC–MSC traffic (BHE) Traffic per BSC
Link capacity(by link rate)
Links required per BSC (by link rate)
Link utilisation
Number of BSCs
Links required per BSC(at selected link rate)
used in BSC calculations
from BSC calculations
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave hopsLink type proportions
Hops per link
The model Network design
101
BSC – MSC transmission (2)
BSC – MSC traffic (BHE) Traffic per BSC
Link capacity(by link rate)
Links required per BSC (by link rate)
Link utilisation
Number of BSCs
Links required per BSC(at selected link rate)
used in BSC calculations
from BSC calculations
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave hopsLink type proportions
Hops per link
BSC – MSC traffic is again a (routeing weighted) sum of all traffic types passing from BSC to MSCs
The model Network design
102
BSC – MSC transmission (3)
BSC–MSC traffic (BHE) Traffic per BSC
Link capacity(by link rate)
Links required per BSC (by link rate)
Link utilisation
Number of BSCs
Links required per BSC(at selected link rate)
used in BSC calculations to define number of MSC-facing ports required (but not the number of BSCs)
from BSC calculations
Microwave links (by link
rate)
Leased lines(by link rate)
Microwave hopsLink type proportions
Hops per link
These calculations are similar to those used for base station site – BSC transmission, though involve different assumptions where appropriate
The model Network design
103
MSCs
Minimum MSCs
CPU capacity (BHms)
CPU utilisation
MSC capacity (CPUs)
Interswitch traffic (BHE)
Switch port capacity
Switch port utilisationProcessing demand (BHms)
Number of MSC-facing ports
Number of MSC/VLRs
Number of interswitch ports
Total number of ports
Number of interconnect-facing ports
Minimum interconnect ports
Switch port capacity
Switch port utilisation
Interconnect traffic (BHE)
used in MSC transmission calculations
from BSC calculations
MSC capacity (ports)
Number of MSCs required to meet demand for ports
Number of BSC-facing ports
The model Network design
104
MSCs (2)
Minimum MSCs
CPU capacity (BHms)
CPU utilisation
MSC capacity (CPUs)
Interswitch traffic (BHE)
Switch port capacity
Switch port utilisationProcessing demand (BHms)
Number of MSC-facing ports
Number of MSC/VLRs
Number of interswitch ports
Total number of ports
Number of interconnect-facing ports
Minimum interconnect ports
Switch portcapacity
Switch port utilisation
Interconnect traffic (BHE)from BSC calculations
MSC capacity (ports)
Number of MSCs required to meet demand for ports
Number of BSC-facing ports
MSC/VLRs are deployed in response to the CPU processing requirements of the network, generated by a number of services and processes, including:
• subscriber authentication
• incoming and outgoing circuit switched call set-ups
• SMS message send and delivery
• subscriber location updating
The model Network design
used in MSC transmission calculations
105
MSCs (3)
Minimum MSCs
CPU capacity (BHms)
CPU utilisation
MSC capacity (CPUs)
Interswitch traffic (BHE)
Switch port capacity
Switch port utilisationProcessing demand (BHms)
Number of MSC-facing ports
Number of MSC/VLRs
Number of interswitch ports
Total number of ports
Number of interconnect-facing ports
Minimum interconnect ports
Switch portcapacity
Switch port utilisation
Interconnect traffic (BHE)
used in MSC transmission calculations
from BSC calculations
MSC capacity (ports)
Number of MSCs required to meet demand for ports
Number of BSC-facing ports
In addition, the number of MSCs should also have sufficient capacity to support port demands.
However, this link is not automatic in the model, and must be completed with a manual check.
The model Network design
106
MSCs (4)
Minimum MSCs
CPU capacity (BHms)
CPU utilisation
MSC capacity (CPUs)
Interswitch traffic (BHE)
Switch port capacity
Switch port utilisationProcessing demand (BHms)
Number of MSC-facing ports
Number of MSC/VLRs
Number of interswitch ports
Total number of ports
Number of interconnect-facing ports
Minimum interconnect ports
Switch port capacity
Switch port utilisation
Interconnect traffic (BHE)
used in MSC transmission calculations
from BSC calculations
MSC capacity (ports)
Number of MSCs required to meet demand for ports
Number of BSC-facing ports
The number of ports are summed up from the three major types of ports present in the MSC
• each MSC-facing port in a BSC requires a reciprocal port in the MSC
• interconnect ports are driven by interconnect traffic (routeing weighted sum of all relevant traffic types), capacity and utilisation inputs
• there may be a contractual QoS minimum requirement for the number of interconnect ports
• interswitch ports are also driven by interswitch traffic (routeing weighted sum of all relevant traffic types), capacity and utilisation inputs
The model Network design
107
Interswitch transmission
Transmission utilisation Number of interswitch circuits
Number of interswitch ports from MSC calculations
The model Network design
108
Interswitch transmission (2)
Transmission utilisation Number of interswitch circuits
Number of interswitch ports 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)
The model Network design
109
HLR capacity
Number of customers
Minimum number of HLRsHLR capacity
Number of HLRs
HLR utilisation
HLR upgrade capacityNumber of HLR upgrades
The model Network design
110
HLR capacity (2)
Number of customers
Minimum number of HLRsHLR capacity
Number of HLRs
HLR utilisation
HLR upgrade capacityNumber of HLR upgrades
HLRs are again driven by a simple calculation involving capacity, demand and utilisation.
However, at least two HLRs are required, at minimum, for redundancy
The model Network design
111
HLR capacity (3)
Number of customers
Minimum number of HLRsHLR capacity
Number of HLRs
HLR utilisation
HLR upgrade capacityNumber of HLR upgrades
Capacity upgrades to the HLRs are deployed, however the full cost of a HLR is assumed in the base HLR, and hence HLR upgrades do not impact the cost results
The model Network design
112
Typical results of BSC, MSC and HLR calculations
The model Network design
0
20
40
60
80
100
120
140
93/94 94/95 95/96 96/97 97/98 98/99 99/00 00/01 01/02 02/03
BSCs
MSCs
HLRs
113
SMS centres
SMSC throughput capacity
Utilisation
Number of SMSCs
SMS throughput demand
Minimum number of SMSCs
The model Network design
114
SMS centres (2)
SMSC throughput capacity
Utilisation
Number of SMSCs
SMS throughput demand
Minimum number of SMSCs
SMS throughput demand is again a routeing weighted sum of all SMS types:
• Mobile originated (MO) off-net
• MO on-net
• MT
• server originated (voicemail, info-service, etc)
The model Network design
115
Dedicated GPRS equipment – PCU boards
PCU throughput capacity
Utilisation
GPRS MB throughput demandNumber of BSCs
from BSC calculations
Number of PCUs by throughputNumber of PCUs by 1 per BSC
minimum
Number of PCUs
The model Network design
116
PCU boards (2)
PCU throughput capacity
Utilisation
GPRS MB throughput demandNumber of BSCs
from BSC calculations
Number of PCUs by throughputNumber of PCUs by 1 per BSC
minimum
Number of PCUs
The number of PCUs deployed (packet control unit upgrades to BSCs) is calculated as the greater of capacity demands or one per BSC
The model Network design
117
Dedicated GPRS equipment – GGSNs
GGSN throughput capacity
Throughput utilisation
GPRS MB throughput demand
Number of GGSNs by throughput
Number of GGSNs by PDP contexts
Number of GGSNs
Active GPRS PDP contexts
GGSN PDP context capacity
PDP context utilisation
Minimum number of GGSNs
The model Network design
118
GGSNs (2)
GGSN throughput capacity
Throughput utilisation
GPRS MB throughput demand
Number of GGSNs by throughput
Number of GGSNs by PDP contexts
Number of GGSNs
Active GPRS PDP contexts
GGSN PDP context capacity
PDP context utilisation
Minimum number of GGSNs
The greatest of three requirements are taken into account when calculating the number of GGSNs deployed:
• at least two for redundancy
• throughput traffic requirements
• PDP context (IP address) requirements
The model Network design
119
Dedicated GPRS equipment – SGSNs
SGSN throughput capacity
Throughput utilisation
GPRS MB throughput demand
Number of SGSNs by throughput
Number of SGSNs by subscribers
Number of SGSNs
Connected GPRS subscribers
SGSN subscriber capacity
Subscriber utilisation
Minimum number of SGSNs
The model Network design
120
SGSNs (2)
SGSN throughput capacity
Throughput utilisation
GPRS MB throughput demand
Number of SGSNs by throughput
Number of SGSNs by subscribers
Number of SGSNs
Connected GPRS subscribers
SGSN subscriber capacity
Subscriber utilisation
Minimum number of SGSNs
The greatest of three requirements are also taken into account when calculating the number of SGSNs deployed:
• at least two for redundancy
• throughput traffic requirements
• GPRS subscriber requirements
The model Network design
121
Dedicated GPRS equipment – IP transmission
Transmission utilisation
Number of IP transmission 2Mbit/s links
GPRS IP Mbit/s
The model Network design
122
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
123
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.
The model Economic Depreciation
124
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)
The model Economic Depreciation
125
What difference does it make whether a market is fullyor 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
The model Economic Depreciation
126
Why then can’t incumbents in a less than fully contestable marketover-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
The model Economic Depreciation
127
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”)
The model Economic Depreciation
128
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
The model Economic Depreciation
129
The inputs
0
200
400
600
800
1000
0 1 2 3 4 5 6 7 8 9 10 11 12
Year of life
0%
20%
40%
60%
80%
100%
Capital investment
Operating expenses
Output (utilisation)
Underlying cost trend(capital and opex combined)E
xpen
ditu
re
The model Economic Depreciation
130
First calculate the total expenditure…(We will initially assume a lifetime of 10 years)
0
200
400
600
800
1000
1200
1400
1600
1800
0 1 2 3 4 5 6 7 8 9 10 11 12
Year of life
0
200
400
600
800
1000
1200
1400
1600
1800
Capital investment
Operating expenses
PV of total expenditure(up to year 10)
Exp
end
iture
The model Economic Depreciation
131
…then calculate the total relative output value(assuming the same lifetime of 10 years)
0%
50%
100%
150%
200%
250%
300%
350%
0 1 2 3 4 5 6 7 8 9 10 11 12
Year of life
0%
50%
100%
150%
200%
250%
300%
350%
Relative output value
PV of total relative outputvalue (up to year 10)
Underlying cost trend(capital and opex combined)
Output (utilisation)
The model Economic Depreciation
132
Divide one by the other to yield the unit pricefor a relative output value of 100%
1644
492
334%
PV of total expenditures PV of total relative output value Unit price at 100% output value
The model Economic Depreciation
133
Multiply this by the relative output value in each year to yield annual revenues
0
50
100
150
200
250
300
350
400
450
500
0 1 2 3 4 5 6 7 8 9 10 11 12
Year of life
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Revenue
Unit price at 100%output value
Relative output value
The model Economic Depreciation
134
Economic depreciation is then the difference between revenues and operating expenses
-200
-100
0
100
200
300
400
500
0 1 2 3 4 5 6 7 8 9 10 11 12
Year of life
Economic depreciation
Operating expenses
Revenue
Economic lifetime = last year in which economic depreciation is positive
Check that this matches with earlier assumption
The model Economic Depreciation
135
Check that everything is consistent!
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
PV of totalrevenues
PV of totalannualised costs
PV of totalexpenditures
Revenues Operating expenses Economic depreciation Capital investment
The model Economic Depreciation
136
Notes re implementation in theLRIC 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
The model Economic Depreciation
137
Notes re implementation in theLRIC 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
The model Economic Depreciation
138
Notes re implementation in theLRIC 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
The model Economic Depreciation
139
Notes re implementation in theLRIC 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
The model Economic Depreciation
140
Notes re implementation in theLRIC 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
The model Economic Depreciation
141
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
142
Network costing is the multiplication of economic cost per item and network deployment per item
Coveragenetwork
cost
Incrementalnetwork
cost
Full networkcost
Full network deployment
Economic cost for each item
Coverage network deployment
Incremental network deployment
The model Network costing
+
=
143
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
The model Network costing
144
A number of similar calculations produce coverage, incrementaland total costs
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
Economic cost per item
1
2
3
…
MCP
Number of items deployed
1
2
3
…
x
MCP
Total cost for each item
1
2
3
…
=
Total cost
TotalIncremental
TotalIncremental
The model Network costing
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
Incrementalcost of each network element
1
2
3…
Routeing factors
Demand by service
1 2 3 …
x Average incrementalcost per unit output of each network element
1
2
3…
=
=Output of each
network element
146
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
147
The matrix of routeing factors is key to the allocation of incremental costs to services
* Routeing factors defined below
The model Service costing
Mark-upsto recovercommon
costs
Unitised incremental
cost per service
Common costs of coverage
Average incremental cost per unit output of each network element
Routeing factors*
148
Routeing factors are relative numerical weightings for the consumption of resources by services
Capacity of each network element required by each
service (per unit of demand)
=Routeing factors
The model Service costing
149
The axes of the routeing factor matrix are services and network elements
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:
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
Cus
tom
ers
Inco
min
g m
ins
OG
off
-net
min
s
OG
on
-net
min
s
SM
S m
ess
age
s
etc
Services
Assets
3-sector macro
BSC
HLR
MSC/VLR
etc
1 1 2 0.01
1
1000 50 20 70
1 1 2 0.01
* Illustrative routeing factors; OG = outgoing
The model Service costing
150
Unitised incremental cost per item, for service 2
1
2
3…
The output of the service costing calculation is unitised incremental service costs
Average incrementalcost per unit output of each network element
1
2
3…
Routeing factorsx =
Unitised incremental cost per item, for service 1
1
2
3…
Unitised incremental cost per item, for service 8
1
2
3…
Unitised incremental cost per item, for service 2
1
2
3…
Unitised incremental cost per item, for service 2
1
2
3…
Unitised incremental cost per item, for service 2
1
2
3…
Unitised incremental cost per item, for service 2
1
2
3…
…
Total unitised incremental cost for service 1
Total unitised incremental cost for service 8
…
The model Service costing
151
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
152
For each year of calculation:
The key outputs of the model are unitised and total costs
Total cost of Coverage MCP
etccustomers incoming calls outgoing calls
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
The model Results
153
The costs of the coverage network must be recovered (marked-up) from the services
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:
equal proportionate, as selected by Oftel: mark-up 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
LRIC
Mark-up
Cus
t-om
ers
Coverage MCP
Traffic
Outgoing Incoming SMS…
LRIC
Mark-up
Cus
t-om
ers
LRIC
Mark-up
Cov
erag
eM
CP
Cus
t-om
ers Traffic
Outgoing Incoming SMS…
Coverage MCP
Traffic
Outgoing
Traffic
Incoming SMS…
Equal proportionate
Premium on mobility
Attributable to access
The model Results
154
We discuss four key sensitivities
Base modelIncreasing long term
growth in demand
Modifying networkdesign parameters
Reducing the price of (modern equivalent)
equipment
Modifying servicerouteing factors
A
B
C
D
The model Results
155
Sensitivity – service routeing factors
Base model
Modifying servicerouteing factors
A
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 Results
156
Sensitivity – long term demand
Base modelIncreasing 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 Results
157
Sensitivity – network design parameters
Base model
Modifying networkdesign parameters
C
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
The model Results
158
Sensitivity – equipment prices
Base modelReducing the price of (modern equivalent)
equipment
D
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
The model Results
159
Executive summary
Background to the Oftel model
Introduction to LRIC modelling
Cost drivers
Service costing
Demand forecasts
Network design
Network costing
Model results
Conclusions
The model:
Services and increments
Economic depreciation
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
Conclusions