8/4/2019 10 8320 Final Model With Tracks Mobile
1/83
Report for the National Post and TelecomAgency (PTS)
New mobile long-run incremental
cost (LRIC) model
Documentation for the final cost model
16 May 2011
Ref: 13392-86b
.
8/4/2019 10 8320 Final Model With Tracks Mobile
2/83
Ref: 13392-86b .
Contents
1
Introduction 1
1.1 Structure of this document 12 Background to the model 32.1 Motivation for the new cost model 32.2 Summary of the new cost model 42.3 Overall flow of the new model 53 Operator input template 84
Market calculations 10
4.1 Voice traffic 104.2 Data traffic 124.3 Worksheet MarketDemand 155 Demand calculations 165.1 WorksheetNetworkLoad 165.2 WorksheetNetworkShare 196 Network calculations 216.1 Network design inputs 6.2 Radio network 246.3 LMA 276.4 Hub to core transmission 286.5 BSCs and RNCs 296.6 Remote BSC and remote RNC to core transmission 306.7 Core-to-core transmission 316.8 Switches and support systems 317 Expenditure 337.1 WorksheetInAsset 337.2 WorksheetFullNw 347.3 WorksheetNwDeploy 347.4 Worksheet CostTrends 357.5 Worksheet UnitCapex 367.6 Worksheet UnitOpex 367.7 Worksheet TotalCapex 367.8 Worksheet TotalOpex 378 Depreciation 388.1 Overview of economic depreciation 38
8/4/2019 10 8320 Final Model With Tracks Mobile
3/83
New mobile long-run incremental cost (LRIC) model
Ref: 13392-86b .
8.2 WorksheetRFs 408.3 WorksheetNwEleOut 418.4 WorksheetDF 418.5 WorksheetED 429 Results 449.1 Calculation of LRAIC(+) 449.2 Calculation of pure LRIC 469.3 WorksheetResults 4910 Supplementary worksheets 5010.1 WorksheetLists 5010.2 WorksheetAreaToPop 5010.3 WorksheetErlang 5111 How to use the new model 5211.1 Basic operation 5211.2 Adding additional operators 5311.3 Worksheet Ctrl 53
Annex A Acronyms 55
Annex B
Changes made to the draft model during finalisation 59
Annex C Source of the inputs used in the model 62
8/4/2019 10 8320 Final Model With Tracks Mobile
4/83
New mobile long-run incremental cost (LRIC) model
Ref: 13392-86b .
Copyright 2011. Analysys Mason Limited has produced the information contained herein
for PTS. The ownership, use and disclosure of this information are subject to the
Commercial Terms contained in the contract between Analysys Mason Limited and theNational Post and Telecom Agency (PTS).
Analysys Mason Limited
St Giles Court
24 Castle Street
Cambridge CB3 0AJ
UK
Tel: +44 (0)845 600 5244
Fax: +44 (0)1223 460866
www.analysysmason.com
Registered in England No. 5177472
8/4/2019 10 8320 Final Model With Tracks Mobile
5/83
New mobile long-run incremental cost (LRIC) model | 1
Ref: 13392-86b .
1 Introduction
The National Post and Telecom Agency (Post-och telestyrelsen, or PTS) has commissioned
Analysys Mason Limited (Analysys Mason) to develop a long-run incremental cost (LRIC)
model for the purposes of understanding and regulating the cost of mobile voice termination in
Sweden. This wholesale service falls under the designation of Market 7, according to the European
Commission (EC) Recommendation on relevant markets.1
Analysys Mason and PTS have agreed a process to deliver the LRIC model, which will be used by
PTS to inform its regulation for mobile termination. This process presents industry participants
with the opportunity to contribute at various points during the project.
The first phase of the project to set out the specification for the cost model has been completed,
and a final model specification was issued on 17 January 2011. This paper also sets out the
background to the process.
The draft cost model has been developed, reflecting this model specification, and exploring a
number of critical modelling aspects which have been discussed with interested industry parties at
a meeting in Stockholm (10 February 2011). This document accompanies the final model released
after consultation with industry parties.
1.1 Structure of this documentThe remainder of this document describes the new mobile LRIC model and is structured as
follows:
Section 2 summarises the background to this modelling work
Section 3 describes the operator input template, which allows alternative network
configurations to be considered within the model
Section 4 describes the market-related calculations
Section 5 describes the demand-related calculations
Section 6 describes the network design calculations
Section 7 describes the expenditure calculations
Section 8 describes the depreciation calculations
1
Seehttp://ec.europa.eu/information_society/policy/ecomm/doc/implementation_enforcement/article_7/recom_term_rates_en.pdf
8/4/2019 10 8320 Final Model With Tracks Mobile
6/83
New mobile long-run incremental cost (LRIC) model | 2
Ref: 13392-86b .
Section 9 describes the display of results in the model
Section 10 describes a small number of supplementary worksheets in the model
Section 11 describes how a user can operate the model.
A supplementary annex includes a list of the acronyms used within this document.
Additional annexes describe the changes made in finalising the model and additional descriptions
on the inputs to the model.
8/4/2019 10 8320 Final Model With Tracks Mobile
7/83
New mobile long-run incremental cost (LRIC) model | 3
Ref: 13392-86b .
2 Background to the model
This section summarises the background to the modelling work, as follows:
Section 2.1 describes the motivation for designing the new cost model
Section 2.2 summarises the principles of the new cost model
Section 2.3provides an overview of the flow of information in the new cost model.
2.1 Motivation for the new cost modelIn 2004, Analysys Consulting Limited built a bottom-up mobile LRIC model for the PTS, with the
aim of calculating the cost of voice termination for the GSM mobile operators in Sweden. In
2007/2008, an upgrade process was undertaken so that UMTS networks could be included within
the model. Quality checks were subsequently undertaken of this upgraded model in 2009 and
2010. The latest version of this model (v6.3) was released in June 2010.
The previous approach calculated the costs of seven actual networks and blended the costs of these
networks together into the actual costs of the operators, based on the infrastructure-sharing
relationships present between the four major mobile network operators (MNO) in Sweden. This
resulted in the modelling of effectively seven separate networks. Due to limitations on the flow of
information from the shared network joint ventures to their parent companies, it was difficult to
demonstrate full reconciliation transparently to all MNOs.
We note that this lack of flow of information has intensified since the previous model upgrade in
2008, with other joint ventures now present in the market (e.g. the Net4Mobility (N4M) GSM joint
venture between Telenor and Tele2). This increasing complexity is summarised in Figure 2.1.
Figure 2.1: Increasing complexity of mobile network infrastructure sharing in Sweden [Source:
Analysys Mason]
Relevant networks in
the 2003 original model
Relevant networks in
the 2007/2008 upgrade
Relevant networks in
the 2010/2011 upgrade
GSM network UMTS network LTE networkKEY:
Tele2 Telenor
TeliaSonera
Tele2
TeliaSonera
SUNAB
Tele2 Telenor
TeliaSonera
3GIS
Hi3G
Telenor
SUNAB
3GIS
Hi3G
N4M
N4M
8/4/2019 10 8320 Final Model With Tracks Mobile
8/83
New mobile long-run incremental cost (LRIC) model | 4
Ref: 13392-86b .
A new LRIC model has thus been proposed for the current modelling process, which no longer
captures actual operators explicitly, but seeks a simpler approach.
2.2 Summary of the new cost modelAnalysys Mason has developed a new mobile LRIC model for PTS, to provide cost-based
information for future wholesale termination regulation in Sweden. This bottom-up model has
been developed using demand and network parameter information submitted by Market 7
stakeholders in Sweden, combined with estimates and calculations performed by Analysys Mason.
The three broad types of inputs that feed into the LRIC model calculation are related to network
design, service volumes and costs, as shown below in Figure 2.2.
Figure 2.2: Overview of
the new mobile LRIC
model [Source: Analysys
Mason ]
The model then calculates long-run incremental costs for mobile network operations in Sweden.
These service costs are derived using both long-run average incremental cost (LRAIC) and pure
long-run incremental cost (pure LRIC) principles. The latter is in accordance with the EC
Recommendation, as referenced in in Section 1. This requires the LRIC model to be run twice,
under different situations, as shown in Figure 2.3.
Network cost
model:
Schedules of asset
volumes, total service
output, total capex,
total opex
Network designinputs
(e.g. technologies,
coverage)
Traffic inputs
(e.g. volumes
carried by service,
busy-hour
characteristics)
Cost inputs
(e.g. unit capex,unit opex, cost
trends, asset
lifetimes)
8/4/2019 10 8320 Final Model With Tracks Mobile
9/83
New mobile long-run incremental cost (LRIC) model | 5
Ref: 13392-86b .
Figure 2.3: Costing approaches within the new LRIC model [Source: Analysys Mason]
A variety of operator network configurations can be defined by choosing the input parameters
appropriately in the model. The model has been set up to calculate costs for a generic Swedish
operator, but it is also capable of reflecting different configurations through inputs on market
share, spectrum and coverage, including configurations similar to the actual MNOs.
For a configuration defined by a given set of inputs, the model derives the assets in a forward-
looking manner and then determines the costs of these assets over a specified timeframe (up to 50
years).
These costs are then recovered by the services assumed to be conveyed over this network during
its lifetime using an economic depreciation calculation. Capital costs are determined using a
weighted average cost of capital (WACC) determined by PTS in a separate workstream. No
remaining terminal value is applied within the LRIC model at the end of the cost recovery period.
The model applies the scorched-node principle, as described in the final model specification
referenced in Section 1. This allows some top-down validation of the bottom-up asset calculation.
In particular, based on operator information, we have:
compared the modelled number of radio sites with the actual number (by geotype)
used typical average numbers of switch locations to identify a reasonably efficient, typical
network structure for a modern national operator.
In addition, the overall expenditures in the model have been checked in aggregate against the total
top-down expenditure information submitted to us by the mobile operators.
2.3 Overall flow of the new modelThe overall flow of the new LRIC model is shown below in Figure 2.4.
Network cost
model:
Schedules of assetvolumes, total
service output, total
capex, total opex
Network design
inputs
(e.g. technologies,
coverage)
Traffic inputs
(e.g. volumes carriedby service, busy-hour
characteristics)
Cost inputs
(e.g. unit capex, unit
opex, cost trends,
asset lifetimes)
LRAIC calculation
(as in the previous model)
Pure LRIC calculation
(calculate difference in the
two cases, as in the EC
Recommendation)
Run network cost
model with all
traffic
Run network cost
model with all
traffic except
termination
increment volume
8/4/2019 10 8320 Final Model With Tracks Mobile
10/83
New mobile long-run incremental cost (LRIC) model | 6
Ref: 13392-86b .
Figure 2.4: Overview of the model calculation flow [Source: Analysys Mason]
The model uses PTS market information (from 2008 onwards) as inputs, and projects these market
parameters over time in order to have a long-term forecast for the model calculations. Demand and
network inputs are defined, either as universal standard parameters or for specific operator
definitions (e.g. generic average operator). Maximum utilisation factors are applied to various
network element capacities in order to reflect realistic and design loading.
The network requirement is combined with cost inputs which determine how much capital and
operating expenditures (capex and opex) are required for the network, including the ongoing
replacement of assets. The model depreciates the expenditures over time, using an economic
depreciation algorithm which takes into account network output (based on LRAIC routeing
factors), price trends, and a discount rate to reflect the return on capital employed (i.e. the time-
discounting of cost recovery relative to expenditure outflow).
Finally, the model produces two sets of outputs:
the costs of termination according to the LRAIC+ methodology
a pure LRIC of termination which is derived by running the model twice (once with, and once
without, wholesale termination traffic).
In this model documentation we denote the source of various inputs as follows:
[1] Analysys Mason estimate
[2] Analysys Mason estimate informed by operatorinputinformation or data
Input Calculation Output
4. Costs 5. Depreciation 6. Results
PTS market
information
Total market Network drivers
Operatorspecification/
market share
Network
design inputs
Network
requirement
Projections Demand drivers Maximum
utilisation %
Asset inputs
Unit costs and
cost trends
Capex and opex
LRAIC routeing
factors
Annualised
economic costs
Network
common costs
and EPMU
Discount rate
1. Market 2. Demand 3. Network
LRAIC+
(as previous
model)
Pure LRIC
(difference in the
two cases)
Run network cost
model with all traffic
Run network cost
model with all traffic
except MT volume
Key:
8/4/2019 10 8320 Final Model With Tracks Mobile
11/83
New mobile long-run incremental cost (LRIC) model | 7
Ref: 13392-86b .
[3] Analysys Mason estimate informed by operatoroutputinformation or data (e.g. scorched-
node reference to total amounts of operator equipment, or reconciliation reference to total
amounts of opex)
[4] Swedish market average based on operator data (rounded or standardised where
appropriate)
[5] standard technical parameter
[6] operator-specific input or choice.
8/4/2019 10 8320 Final Model With Tracks Mobile
12/83
New mobile long-run incremental cost (LRIC) model | 8
Ref: 13392-86b .
3 Operator input template
The model is set up so that a subset of inputs is defined in an operator template. This template
forms a separate worksheet in the LRIC model. Through this method, additional operator
templates can be added to the model by:
duplicating the template worksheet and renaming the worksheet to beInput_(new name)
ensuring that the new operator worksheet name is added to the list of operators, in the Lists
worksheet, column Z
selecting the new worksheet name from the operator selector in the model control panel.
The structure of the inputs on theInput_(new name) worksheet is summarised below.
1. Share of market Specifies the share of the national market for GSM, UMTS, HSPA
(mobile broadband) and LTE (mobile broadband) traffic.
Specifies where the operator has network deployed (e.g. it can be used
for 3GIS to reduce network deployment in urban areas).
2. Coverage and
spectrum
Specifies the population covered by each of the different technologies
for each year the model is running.
Specifies the number of urban micro sites for coverage.
Specifies the frequency used to deploy coverage for each network. This
is used to calculate the number of coverage sites required based on a
predetermined cell radius by frequency and geotype.
Specifies the amount of paired spectrum by technology and whether this
spectrum is used for coverage or capacity.
Specifies the number of UMTS channels set aside for UMTS rather thanHSPA traffic.
3. Network design
parameters
Specifies the proportion of links that are leased and the transmission
protocol they use in each geotype.
Specifies the proportion of sites collocated with hubs and the
transmission protocol they use in each geotype.
Specifies the proportion of sites connected via a hub to the core
network, rather than being connected directly to the core network, thenumber of sites per hub, and the number of hubs per hub-core
8/4/2019 10 8320 Final Model With Tracks Mobile
13/83
New mobile long-run incremental cost (LRIC) model | 9
Ref: 13392-86b .
transmission link, in each geotype.
Specifies the number of locations where base station controllers (BSC)
and radio network controllers (RNC) are deployed, and the share of
radio traffic in the suburban or rural geotypes that is handled by a BSC
or RNC in the same geotype rather than being transferred to a BSC or
RNC in the urban geotype.
Specifies the transmission protocol used by BSC/RNC to core nodes for
voice and data.
Specifies the number of core sites in each geotype (by default 0 except
in the urban geotype).
Specifies the proportion of voice and data conveyed across core-core
links, and the transmission protocol.
4. Adjustment
factor for operator
assets
By default, all adjustments are set to 100%. However it is possible to
use this input to remove or reduce various assets from the cost base of
individual operators.
8/4/2019 10 8320 Final Model With Tracks Mobile
14/83
New mobile long-run incremental cost (LRIC) model | 10
Ref: 13392-86b .
4 Market calculations
The model uses PTS statistics on the total market in Sweden to drive the forecasts for both mobile
market subscribers and traffic. This market information is then rearranged to suit the categories
used in the model. Three subscriber types are modelled: voice-only handset, voice+data handset,
and mobile broadband laptop/dongle. Voice and data traffic are treated separately. Both are split
into sub-categories: incoming, outgoing and on-net traffic for voice; handset data usage and
mobile broadband data usage for data. Both are also split into the different access technologies
used. SMS is modelled as voice-equivalent traffic, but has very little impact on the large-scale
network.
An outline of the market calculation is shown in Figure 4.1.
Figure 4.1: Market calculation steps [Source: Analysys Mason]
The rest of this section describes the voice traffic (Section 4.1) and data traffic (Section 4.2)
captured in the model, and concludes with a summary of the structure of the MarketDemand
worksheet (Section 4.3).
4.1 Voice trafficHistorical total voice traffic and number of subscribers from 1H 2008 to 2H 2010 are used to
derive a forecast for the duration of the model. Originated traffic from mobiles (including on-net)
and incoming traffic both increase until 2013. Originated traffic is assumed to increase at a faster
PTS market
information
20082010
Mobile-originated
minutes per
subscriber
Mobile-terminated
minutes per
subscriber
Projected growth
201020152020
Projected growth
201020152020
Mobile-originated
SMS per
subscriber
Mobile-terminatedSMS per
subscriber
Projected growth
201020152020
Projected growth
201020152020
Proportion of
people who
use data
Proportion of
people who have
broadband
Projected growth
201020152020
Projected growth
201020152020
Data traffic per
handset user
Data traffic per
broadband user
Total market
200820102010 = 1H + estimated 2H, to be updated in May 2011
8/4/2019 10 8320 Final Model With Tracks Mobile
15/83
New mobile long-run incremental cost (LRIC) model | 11
Ref: 13392-86b .
rate than incoming traffic. Usage per subscriber is then assumed to have reached a steady state,
remaining constant from 2013 onwards. This evolution is shown in Figure 4.2.
Figure 4.2: Evolution of
voice usage in Sweden
[Source: PTS, Analysys
Mason]
From this traffic by user, and assuming the number of voice users remains constant from 2010
onwards, the total voice traffic is calculated for on-net, outgoing (excluding on-net) and incoming
traffic. These three categories are added up in Figure 4.3, showing that total voice traffic is
forecast to increase from 32 billion minutes in 2010 to 36 billion minutes in 2013.
Figure 4.3: Evolution of
total voice usage in
Sweden [Source: PTS,
Analysys Mason]
In the previous model, the share of voice traffic carried by the GSM network decreased until
0
50
100
150
200
250
2008 2010 2012 2014 2016 2018 2020
Mobile originated minutes per user per month
Incoming minutes per user per month
ActualForecast
0
5
10
15
20
25
30
35
40
2008 2010 2012 2014 2016 2018 2020
Billions
Mobile incoming minutesMobile outgoing minutesMobile on-net minutes
Actual Forecast
8/4/2019 10 8320 Final Model With Tracks Mobile
16/83
New mobile long-run incremental cost (LRIC) model | 12
Ref: 13392-86b .
disappearing in 2016. In this model, it is no longer assumed that the GSM network will be shut
down. The main reason for this new assumption is that it is now known that Telenor and Tele2 are
jointly deploying a new GSM network under the N4M joint venture. The share of voice traffic
carried on the 2G network is now assumed to decrease to 40% in 2013, remaining constant
thereafter. Figure 4.4 illustrates this new forecast.
Figure 4.4: Evolution of
the share of voice traffic
by technology [Source:
PTS, Analysys Mason]
4.2 Data trafficThe model continues the strong growth of handset data users, associated with the increasing
penetration of smartphones. From 54% in 2010, the proportion of handset data users is forecast to
reach a steady state of 74% of voice subscribers from 2017, as illustrated in Figure 4.5. Mobile
broadband (i.e. dongle) users are much fewer in number, representing only 16% of voice
subscribers in 2010. This proportion is assumed to increase faster than handset data users to reach
24% of voice subscribers in 2019, remaining constant thereafter.
0%
10%
20%
30%
40%
50%
60%
70%
80%
2008 2010 2012 2014 2016 2018 2020
Percentage of total voice traffic on the 2G network
Percentage of total voice traffic on the 3G network
Actual Forecast
8/4/2019 10 8320 Final Model With Tracks Mobile
17/83
New mobile long-run incremental cost (LRIC) model | 13
Ref: 13392-86b .
Figure 4.5: Proportion of
voice subscribers who
are also data users
[Source: PTS, Analysys
Mason]
Data usage per handset data subscriber is forecast to remain constant from 2010, as illustrated
below in Figure 4.6.
Figure 4.6: Evolution of
data usage for handsets
and dongles [Source:
PTS, Analysys Mason]
On the other hand, data usage from dongles (or broadband) is assumed to start at a much higher
use per subscriber than handset usage, and it is forecast to approximately double between 2010 and
2014. As a result, the vast majority of data traffic is expected to originate from dongles, as shown
in Figure 4.7.
0%
10%
20%
30%
40%
50%
60%
70%
80%
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Proportion of users who are handset datausers
Actual Forecast
0
1,000
2,000
3,000
4,000
5,000
6,000
0
20
40
60
80
100
120
2008 2010 2012 2014 2016 2018 2020
Broa
dban
dusers
Han
dse
tusers
Mbytes per handset data user per month
Mbytes per broadband data user per month
Actual Forecast
8/4/2019 10 8320 Final Model With Tracks Mobile
18/83
New mobile long-run incremental cost (LRIC) model | 14
Ref: 13392-86b .
Figure 4.7: Evolution of
total data usage for
handsets and dongles
[Source: PTS, Analysys
Mason]
Between 2008 and 2010, HSPA is assumed to carry almost all of the data traffic (HSDPA for the
downlink traffic and HSUPA for the uplink traffic). R99 is forecast to decline quickly to comprise
only a small proportion of data traffic in 2011. GPRS and EDGE are marginal throughout the
modelling period, and LTE has not yet reached significant volumes. From 2011, LTE is assumed
to grow steadily to account for 45% of the total data traffic by 2014, whilst HSDPA and HSUPA
are projected to decline to 43% and 12% of data traffic, respectively, as shown below in Figure
4.8. This decline in the share of HSPA traffic is not linked to a decline in data volumes carried, as
data volumes are assumed to quadruple between 2010 and 2018, but rather indicates that most of
the increased traffic is carried on LTE networks rather than HSPA networks.
0
20
40
60
80
100
120
140
160
180
2008 2010 2012 2014 2016 2018 2020
Billions
Total Mbytes of broadband data Total Mbytes of handset data
Actual Forecast
8/4/2019 10 8320 Final Model With Tracks Mobile
19/83
New mobile long-run incremental cost (LRIC) model | 15
Ref: 13392-86b .
Figure 4.8: Evolution of
the share of data traffic
by technology [Source:
PTS, Analysys Mason]
4.3 Worksheet MarketDemand1. PTS source
market information
Collates data from the PTS market statistics from 1H 2008 to 2H 2010.
Reorders the data into the categories used in the model and only keeps
end-of-year values.
2. Forecast marketinformation
Derives forecasts for the whole duration of the model (until 2058),starting from the existing market information. [1, 4]
Splits the traffic by technology (2G/3G for voice traffic and SMS,
GPRS/EDGE/R99/HSDPA/HSUPA/LTE for data traffic) and by device
(handsets or dongles). [2]
3. Total market
volumes
Calculates the volume of traffic by technology and service for the whole
duration of the model.
4. Output total
market volumes
Calculates the total volume of traffic by technology and service after
applying a sensitivity multiplier.
0%
10%
20%
30%
40%
50%
60%
70%
80%
2008 2010 2012 2014 2016 2018 2020
GPRS EDGE R99
HSDPA HSUPA LTE
Actual Forecast
8/4/2019 10 8320 Final Model With Tracks Mobile
20/83
New mobile long-run incremental cost (LRIC) model | 16
Ref: 13392-86b .
5 Demand calculations
The demand calculations are used to determine the traffic measures that dimension the network of
the modelled operator. They determine, from the whole market and the market share of thisoperator, what is the peak traffic load that the network needs to be able to handle. This is
calculated based on the share of traffic in the busy hour, the average duration of voice calls, and
the proportion of data traffic in the busiest data path (uplink or downlink).
The remainder of this section is structured as follows:
the calculation of network loading on theNetworkLoadworksheet (Section 5.1)
the spreading of this load across the modelled geotypes (Section 5.2).
5.1 Worksheet NetworkLoadThis worksheet calculates the loading at the various levels of the network based on the traffic
throughput.
1. Market share Links in the total market and the operatorsmarket share.
Calculates the average number of voice/voice+data subscribers and
mobile broadband subscribers.
2. Total volumes
for the network
Multiplies the total market by the operators market share to obtain the
total volume of traffic carried by the selected operator.
3. Load
calculations
Specifies inputs for busy days, busy-day traffic and busy-hour traffic.
[2, 4]
Calculates busy-hour Erlangs (BHE) for each voice service.
Specifies inputs for call attempts, ring minutes per call and radio
loading factors. [2, 4]
Specifies inputs for average call duration. [4]
Calculates BHE in the radio network for each voice service.
Calculates SMS in the busy hour.
Specifies inputs for the proportion of data service traffic in the uplink
versus the downlink. [1,2]
8/4/2019 10 8320 Final Model With Tracks Mobile
21/83
New mobile long-run incremental cost (LRIC) model | 17
Ref: 13392-86b .
Calculates data Mbit/s in the busy hour.
4. Radio load
for voice
Calculates total 2G and 3G BHE in the radio network.
5. Network load for
GPRS and EDGE
Calculates downlink busy-hour Mbit/s for voice and data traffic in their
respective busy hours.
Determines total GPRS and EDGE Mbytes, using a conversion factor
for EDGE traffic [1].
6. Network load
for UMTS and R99
data
Calculates BHE for voice and data traffic in their respective busy hours,
converting R99 UMTS data into voice-equivalent channels using a
conversion factor based on the assumed CE rate for R99 data [1].
Calculates the peak BHE, by taking the maximum of the voice busy
hour and the data busy hour.
7. Network load
for HSPA
Links in total HSDPA and HSUPA load in the data busy hour.
8. Network load
for LTE
Links in total downlink LTE load in the data busy hour.
9. Network load for
traffic from radio
layer into core/ring
network
Defines the amount of provisioned bandwidth for supporting the busy-
hour Mbit/s in the radio network for each data bearer [5].
Calculates the provisioned downlink data in the voice and data busy
hours for data traffic.
Defines the amount of provisioned bandwidth for supporting the voice
BHE in the radio network [5].
Calculates the provisioned upstream/downstream data for voice traffic
in both the voice and data busy hours.
Calculates the total load in both the voice and data busy hours, and the
peak load, by taking the maximum of the voice and data busy hour.
10. Network load
for BSC traffic
Defines the amount of provisioned bandwidth for supporting BSC-core
data traffic [5].
Calculates the provisioned downlink data in the voice and data busy
hours for data traffic.
Defines the amount of provisioned bandwidth for supporting the voice
8/4/2019 10 8320 Final Model With Tracks Mobile
22/83
New mobile long-run incremental cost (LRIC) model | 18
Ref: 13392-86b .
BHE in the radio network in BSC-core links [5].
Calculates the provisioned duplex data in the voice and data busy hours
for voice traffic.
Calculates the total load in the voice and data busy hours, and the peak
load, by taking the maximum of the voice and data busy hour.
11. Network load
for RNC traffic
Defines the amount of provisioned bandwidth for supporting the busy-
hour Mbit/s in the radio network. This is undertaken for each data bearer
and is calculated in terms of the RNC throughput. [5]
Calculates the provisioned downlink data in the voice and data busy
hours for data traffic through the RNC.
Defines the amount of provisioned bandwidth for supporting the voice
BHE in the radio network through the RNC. [5]
Calculates the provisioned duplex data in the voice and data busy hours
for voice traffic through the RNC.
Calculates the total load in the voice and data busy hours, and the peak
load, by taking the maximum of the voice and data busy hour.
12. Network load
for core-core traffic
Calculates the network BHE for voice traffic in the voice and data busy
hours.
Calculates the amount of core-core busy-hour Mbit/s for voice traffic in
the voice and data busy hours, by applying the proportion of voice
traffic that is conveyed between core sites.
Calculates the amount of core-core busy-hour Mbit/s for data traffic in
the voice and data busy hours, by applying the proportion of data traffic
that is conveyed between core sites.
Calculates the peak core-core Mbit/s, by taking the maximum of the
voice and data busy hour.
13. Network load
for switches and
servers
Calculates the load on the data servers using the number of data
subscribers and inputs for active packet data protocols (PDP)
contexts [1] and simultaneous active users (SAU) [1].
Calculates the number of minutes in a busy day for the wholesale billing
system.
Calculates the number of 2G and 3G call attempts in the busy hour.
8/4/2019 10 8320 Final Model With Tracks Mobile
23/83
New mobile long-run incremental cost (LRIC) model | 19
Ref: 13392-86b .
Calculates the number of SMS in the busy hour.
For each server in the list, calculates or links in the individual load
amount.
5.2 Worksheet NetworkShareThis worksheet splits out network loading by geotype.
1. Traffic by
geotype
Determines input for the proportion of traffic by geotype, if full network
coverage. [2,3]
Determines input for the proportion of national traffic which occurs on
micro sites. [2,3]
Links in the network location inputs.
2. Coverage by
geotype
Links in the population coverage by technology, and micro sites for
coverage.
Calculates area coverage by geotype.
Calculates the proportion of population covered by each technology in
each geotype.
Calculates the actual distribution of traffic within the covered areas.
3. Network GSM
voice traffic by
geotype
Links in 2G voice BHE in the radio network.
Calculates 2G voice BHE in the radio network by geotype.
4. Network UMTS
R99 voice traffic by
geotype
Links in UMTS R99 BHE in the radio network.
Calculates UMTS R99 BHE in the radio network by geotype.
5. Network HSPA
traffic by geotype
Links in HSDPA and HSUPA busy-hour Mbit/s of the radio network.
Calculates HSDPA and HSUPA busy-hour Mbit/s of the radio network
by geotype.
6. Network LTE
traffic by geotype
Links in downlink LTE busy-hour Mbit/s of the radio network.
For each geotype, calculates the LTE busy hour Mbit/s, in the downlink,
of the radio network.
8/4/2019 10 8320 Final Model With Tracks Mobile
24/83
New mobile long-run incremental cost (LRIC) model | 20
Ref: 13392-86b .
7. Network traffic
into RNC/BSC
core nodes
Links in peak Mbit/s load passing into the core network.
Calculates peak Mbit/s load passing into the core network by geotype.
8. Network traffic
for RNC Mbit/s
Links in peak RNC load in Mbit/s.
Calculates peak RNC Mbit/s passing into the core network by geotype.
8/4/2019 10 8320 Final Model With Tracks Mobile
25/83
New mobile long-run incremental cost (LRIC) model | 21
Ref: 13392-86b .
6 Network calculations
The network calculations within the model take the demand drivers and other network inputs and
compute the number of each network element that is needed. The structure and nature of the
network design inputs is described in Section 6.1. These network design calculations cover the full
range of layers in the network hierarchy, as follows:
network design inputs and utilisation factors (Section 6.1)
radio network (Section 6.2)
last-mile access (Section 6.3)
hub to core transmission (Section 6.4)
BSCs and RNCs (Section 6.5)
remote BSC and remote RNC to core transmission (Section 6.6)
core-to-core transmission (Section 6.7)
switches and support systems (Section 6.8)
6.1 Network design inputsNetwork design inputs are either operator-specific or universal. Operator-specific inputs are linked
(using an INDIRECT function) from the relevant operator input template. Universal network
design inputs are entered in this part of the model.
6.1.1Worksheet NetworkDesignInputs1. Coverage Cell radius for outdoor coverage [1].
Cell pi which is used to calculate the cell area covered [5].
Frequency used for coverage added in each year, linked from the
selected operator [6].
2. Spectrum Amount of paired spectrum in each coverage and capacity layer, linked
from the selected operator. [6]
Size of a radio channel, in MHz. [5]
Calculation of the number of channels available.
8/4/2019 10 8320 Final Model With Tracks Mobile
26/83
New mobile long-run incremental cost (LRIC) model | 22
Ref: 13392-86b .
Number of UMTS channels reserved for voice and low-speed R99 data
(not HSPA). [6]
Number of channels available for traffic load.
3. GSM capacity Input of cell reuse factor. [5]
Input of the average sectorisation of GSM sites. [2]
Input of physical TRX per sector limit, along with the calculation of the
effective limit on average by geotype. [2]
Calculation of the maximum number of TRX per sector, either by
spectrum or by geotype.
Input of the number of GSM channels reserved for GPRS/EDGE packetdata and for signalling. [1, 5]
Input of GSM channel rates. [5]
Input of GSM blocking probability. [1, 5]
Calculation of Erlang capacity per site.
4. UMTS capacity Input of R99 channel rate in Mbit/s. [1, 5]
Input of the average sectorisation of UMTS sites. [2]
Input of soft- and softer-handover overheads. [1, 5]
Input of the number of R99 signalling channels per carrier, minimum
and maximum R99 carriers per carrier (pooled at the NodeB). [1, 5]
Input of UMTS blocking probability. [1, 5]
Calculation of Erlang capacity per carrier (pooled at the NodeB).
Calculation of Erlang capacity per site.
Input of channel kit size (in CE). [5]
5. HSPA capacity Input of the cell peak to effective rate for data throughput. [1]
Specification of the HSDPA and HSUPA rate ladder. [5]
6. LTE capacity Input of the cell peak to effective rate for data throughput. [1]
8/4/2019 10 8320 Final Model With Tracks Mobile
27/83
New mobile long-run incremental cost (LRIC) model | 23
Ref: 13392-86b .
Specification of the LTE rate ladder. [5]
7. Physical sites Input of percentage for sites deployed as single technology or co-located
sites. [1]
Input of percentage of sites which are deployed on third-party
infrastructure. [1]
8. LMA and hub
to core
Specification of the LMA and hub-core rate ladders. [5]
Linked operator inputs for site transmission choice, hub co-location,
leased LMA, and hub-core link parameters for rings or point-to-point
hub-core transmission. [6]
9. RNC and BSC Linked operator inputs for the number of BSC/RNC locations, and the
proportion of load served in each geotype. [6]
Specification of the BSC and RNC capacity ladders. [5]
10. BSC-core
traffic
Specification of the remote BSC-core rate ladder. [5]
Input for the redundancy in BSC-core links. [1, 5]
11. RNC-core
traffic
Specification of the remote RNC-core rate ladders. [5]
Input for the redundancy in RNC-core links. [1, 5]
Linked operator input for the protocol used for voice and data
interfaces. [6]
12. Core-core
traffic
Linked operator input for the number of core sites, proportion of traffic
conveyed across the core, and transmission protocol for voice and data
layers. [6]
Specification of the core-core rate ladder, and number and distance of
hops in the dark-fibre core network. [1, 3]
13. Switches and
servers
Input of capacity for each network element in the list. [1, 2, 3]
Input of the minimum number and redundancy multiplier for each
network element in the list. [1]
14. Specify scope of
operator assets
Linked operator input for the specific assets which are included in each
operator network. [6]
8/4/2019 10 8320 Final Model With Tracks Mobile
28/83
New mobile long-run incremental cost (LRIC) model | 24
Ref: 13392-86b .
6.1.2Worksheet NetworkUtil1. Network capacity
utilisation factors
for calibration
Maximum utilisation factors for network capacity for each set of
network elements. [1, 3, 5]
6.2 Radio networkThe network design for the radio layer considers the three technologies (GSM, UMTS and LTE)
with radio capacity upgrades, as well as the physical site requirements (single technology sites, co-
located sites, own tower sites and third-party installations). The network design first considers sites
for coverage and then considers the radio interface traffic loading to calculate the additional assets
required to carry this loading.
Figure 6.1: Overview of the modelled radio networks [Source: Analysys Mason]
6.2.1Worksheet NwDesRadioCov1. GSM radio
network coverage
Links in the area to be covered.
Calculates area coverage added in each year.
Links in area per site.
Calculates the number of sites added for coverage in each year.
Calculates the total number of sites for coverage.
2. UMTS radio
As above but for UMTS.
BTS
TRX
Ancillary
power
Tower
Rooftop or
third-party
site
NodeB
R99-CK
Ancillary
power
eNodeB
LTE
Ancillary
power
HSPA
GSM
UMTS
LTE
Shared
Not costed
Site acquisition and
preparation
R99 CK = 16 duplex CEHSDPA
upgrades in
Mbit/s per25MHz:
1.8
3.6
7.2
10.1
14.1
21.1
HSUPA
upgrades in
Mbit/s per25MHz:
0.73
1.46
2
2.93
5.76
11.5
LTE
upgrades in
Mbit/s per25MHz:
10.8
16.2
21.6
32.4
43.2
86.4
own tower
or third
party
8/4/2019 10 8320 Final Model With Tracks Mobile
29/83
New mobile long-run incremental cost (LRIC) model | 25
Ref: 13392-86b .
network coverage
3. HSPA radio
network coverage
As above but for HSPA.
4 LTE radio
network coverage
As above but for LTE.
6.2.2WorksheetNwDesLoadPart of this worksheet contains the radio network calculation, for each technology.
1. GSM capacity
calculation
Links in sites for coverage and voice BHE.
Calculates capacity of the coverage deployment.
Calculates BHE which cannot be supported by the coverage deployment
and must be supported by capacity upgrades.
Calculates the number of capacity BTS layers which must be added to
coverage sites.
Calculates BHE which cannot be supported by upgraded coverage sites,
and must have new sites deployed.
Calculates the number of new (capacity) sites needed to support
remaining BHE.
Calculates the total number of GSM sites and BTS.
Calculates the number of TRX in the coverage layer of coverage sites.
Calculates the number of TRX in the coverage layer of capacity sites.
Calculates the number of TRX in the capacity layers.
Calculates the number of TRX in total.
Checks whether the reservation of channels for GPRS is sufficient for
the average throughput required.
2. UMTS capacity
calculation
Links in sites for coverage and R99 BHE.
Calculates capacity of the coverage deployment.
Calculates BHE which cannot be supported by the coverage deployment
8/4/2019 10 8320 Final Model With Tracks Mobile
30/83
New mobile long-run incremental cost (LRIC) model | 26
Ref: 13392-86b .
and must be supported by capacity upgrades.
Calculates the number of capacity carrier layers which must be added to
coverage sites.
Calculates BHE which cannot be supported by upgraded coverage sites,
and must have new sites deployed.
Calculates the number of new (capacity) sites needed to support
remaining BHE.
Calculates the total number of UMTS sites.
Calculates the total number of UMTS R99 NodeBs.
Calculates the total number of R99 carriers and CK in the coveragecarriers of NodeBs.
Calculates the total number of R99 carriers and CK in the additional
capacity carriers of NodeBs.
3. HSDPA ladder
calculation
Links in sites for coverage and BH Mbit/s.
Calculates BH Mbit/s per site.
Calculates maximum capacity based on the rate ladder and the numberof carriers (spectrum) available.
Checks that there are sufficient UMTS sites deployed to support the data
upgrades.
Calculates BH Mbit/s per site.
Calculates the rate needed in the first, second, third and fourth carrier
upgrade (if needed).
Calculates the number of sites at each step of the rate ladder.
4. HSUPA rate
ladder
As above except for HSUPA.
5. LTE rate ladder As above except for LTE.
6. Physical sites Calculates the number of GSM, UMTS and LTE sites on single-
technology sites, using leased or microwave LMA.
Calculates the number of multi-technology sites which are co-locating
8/4/2019 10 8320 Final Model With Tracks Mobile
31/83
New mobile long-run incremental cost (LRIC) model | 27
Ref: 13392-86b .
multiple radio layers, using leased or microwave LMA.
Calculates the number of sites on own towers and on third-party sites.
6.3 LMAThe LMA network is common for all three radio network technologies. It considers two
transmission protocols (ATM/SDH/PDH and Ethernet) with capacity upgrades, as well as the
physical transmission infrastructure (which can be either leased lines or microwave links).
Figure 6.2: Overview of the modelled LMA networks [Source: Analysys Mason]
6.3.1WorksheetNwDesLoad7. LMA Calculates the LMA capacity requirement for single-technology sites.
Calculates the LMA capacity requirement for multi-technology sites.
Determines the actual capacity of LMA links by geotype according to a
predefined ladder of options.
Calculates the number of leased-line LMA links and self-provided/
microwave LMA links by rate according to that same rate ladder.
Sites (single or multi-technology)
Next node in the network (site, hub, BSC/RNC, core)
Leased line
Microwave link
Traditional
for GSM
Mbit/s
2
4
8
16
32
155
622
Ethernet
for others
Mbit/s
10
30
100
150
200
300
1000
Traditional
for GSM
Mbit/s
2
4
8
16
32
155
622
Ethernet
for others
Mbit/s
10
30
100
150
200
300
1000
x% single
technology
y% multi-
technology
10% leased
lines for
outdoor sites
(100% indoor)
90%
microwave foroutdoor sites
2% sited on ahub (therefore
no LMA)
90% to hubs,
10% direct to core
10 sites per hub
GSM
UMTS
LTE
Shared
Not costed
8/4/2019 10 8320 Final Model With Tracks Mobile
32/83
New mobile long-run incremental cost (LRIC) model | 28
Ref: 13392-86b .
6.4 Hub to core transmissionThe hub to core transmission network is also common for all three radio network technologies.
There are again capacity upgrades, and the physical transmission infrastructure can at this level be
in rings (for leased lines) or point-to-point (for microwave links).
Figure 6.3: Overview of the modelled transmission between hubs and the core network [Source:
Analysys Mason]
6.4.1WorksheetNwDesLoad8. Hub to core
transmission
Calculates the number of radio sites connected via a hub.
Calculates the number of hubs and related point-to-point links and rings
to the core network.
Calculates the total network traffic at the hub layer, and split it by point-
to-point link or ring.
Determines the actual capacity of hub to core point-to-point links or
rings by geotype according to a predefined rate ladder.
Calculates the number of point-to-point links and rings by rate
according to that same rate ladder.
Calculates the number of hubs on rings by rate.
Hub
Microwave point-to-point
Traditional
Mbit/s
32
155
622
2488
Ethernet
Mbit/s
100
1000
2500
10000
BSC/RNC or core site
Access
point
Access
point
Multiple hubs
Leased dark fibre
520km
length per
ring by
geotype
OR
100% of sites
on four-hub
rings
GSM
UMTS
LTE
Shared
Not costed
Traditional
Mbit/s
32
155
622
2488
Ethernet
Mbit/s
100
1000
2500
10000
OR
8/4/2019 10 8320 Final Model With Tracks Mobile
33/83
New mobile long-run incremental cost (LRIC) model | 29
Ref: 13392-86b .
6.5 BSCs and RNCsBSCs and RNCs aggregate the 2G and 3G traffic respectively. In both cases, all the urban radio
traffic is routed through BSCs/RNCs in the urban geotype, but only a percentage of the suburban
radio traffic and a percentage of the rural suburban radio traffic is routed through BSCs/RNCs in
their respective geotype, the remaining share being sent to the urban geotype. There are capacity
upgrades implemented in the model for this level as well.
Figure 6.4: Overview of the modelled BSCs and RNCs [Source: Analysys Mason]
6.5.1WorksheetNwDesLoad9. BSC
(to total number of
BSC by capacity)
Reallocates the number of TRX needed in each geotype according to the
load served locally or sent to switches in the urban geotype.
Calculates the BSCs capacity requirement per location in each geotype.
Calculates the number of BSCs required in each geotype according to
the capacity requirement and the unit capacity of a BSC in each
geotype.
Calculates the number of BSCs by capacity according to a predefined
ladder.
10. RNC
(to total number of
RNC by capacity)
As above but for RNCs.
Rural
BSC site
Urban
BSC site
Suburban
BSC site
Rural
RNC site
Urban
RNC site
Suburban
RNC site
Rural TRXUrban TRXSuburban
TRX
Urban
micro TRX
BSCBSC BSC
Rural Mbit/sUrban Mbit/sSuburban
Mbit/s
Urban micro
Mbit/s
RNCRNC RNC
BSC capacity in TRX
384
512
2048
RNC capacity in Mbit/s
196
450
2600
Most load is carried back to large switch sites, a proportion of suburban and rural load
is served locally before being trunked back to core sites
50% 50%10% 10%
GSM
UMTS
LTE
Shared
Not costed
8/4/2019 10 8320 Final Model With Tracks Mobile
34/83
8/4/2019 10 8320 Final Model With Tracks Mobile
35/83
New mobile long-run incremental cost (LRIC) model | 31
Ref: 13392-86b .
6.7 Core-to-core transmissionThe core network is assumed to be a ring linking Stockholm to Gteborg to Malm, through eight
other large cities, and two links (for redundancy) linking Stockholm to Lule. It carries a
proportion of the data traffic and a proportion of the voice traffic. The ATM/SDH/PDH and
Ethernet protocols can be used for voice and data layers, or all traffic carried in a converged
Ethernet network. The capacity of links follows a predefined hierarchy of options.
Figure 6.6: Overview of modelled transmission within the core network [Source: Analysys Mason]
6.7.1WorksheetNwDesLoad11. Core-to-core
rings
Calculates the core-to-core traffic load (including the utilisation factor),
separately for ATM/SDH/PDH and for Ethernet.
Determines the actual capacity of the core-to-core links according to a
predefined rate hierarchy (separately for ATM/SDH/PDH and for
Ethernet).
Calculates the number of core nodes by speed.
6.8 Switches and support systemsDifferent types of switches are necessary to ensure the network of the operator modelled is able to
function as planned to offer mobile services. Figure 6.7 presents these switches and states the
minimum number required in any network. The traffic load on the network may then require larger
numbers of units to be deployed. Some switches are assumed to have redundant deployments.
Remote RNC
Main
switching site
Remote BSC
Remote RNC
Remote BSC
Main
switching site
Main switching
site
Remote RNC
Remote BSC
Remote RNC
Remote BSC
Stockholm,
Gothenburg
and Malmo
Upsala, Vasteras,
Orebro, Karstad,
Kristianstad, Karlskrona,
Jonkoping, Norkoping
Sundsval,
Lulea
900km dark
fibre pair
1645km dark
fibre pair
Voice and
data layers
(or all IP)
Traditional
for voice
Mbit/s
155
622
2488
9952
Ethernet
for data
Mbit/s
1000
2500
10000
40000
15% of datatraffic
2515% of
voice traffic
GSM
UMTS
LTE
Shared
Not costed
8/4/2019 10 8320 Final Model With Tracks Mobile
36/83
New mobile long-run incremental cost (LRIC) model | 32
Ref: 13392-86b .
All switches are shared between the different network technologies (GSM, UMTS, LTE), except
the GSM MSCs used only in the GSM network and the MMEs and SGWs are used only in the
LTE network.
Asset Assumed
capacity [1, 2]
Minimum
deployment [1]
Asset Assumed
capacity [1, 2]
Minimum
deployment [1]
GSM MSC 400 000 BHCA 2 AUC 1 000 000 subs 1
MSS 800 000 BHCA 2 EIR 1 000 000 subs 1
MGW 20 000 BHE 2 2 (for
redundancy)
MNP 1 per operator 1
SGSN 1 400 000 SAU 2 IN 500 000 subs 1
GGSN 80 000 PDP 2 VMS 50 000 subs 1
MME 10 Gbit/s 2 SMSC 1 000 SMS per
second
2 2 (for
redundancy)
SGW 10 Gbit/s 2 MMSC 1 per operator 1
HLR 1 800 000 subs 2 VAS 500 000 subs 1
PoI 2 422 BHE 2
Figure 6.7: Overview of the switch capacity assumptions [Source: Analysys Mason]
6.8.1WorksheetNwDesLoad12. Servers Calculates the number of each type of servers required to handle the
traffic determined in the NetworkLoad worksheet and applying to it
predetermined specifications about their capacity and utilisation factor.
6.9 Switch portsA number of port upgrades network elements are present in the model, for a variety of switches.
These network elements reflect the upgrade costs to connect links into switches.
6.9.1WorksheetNwDesLoad13. Switch ports Calculates the number of site-facing and core-facing ports for BSC and
RNC switches, using E1 or 10Mbit/s port units, and for voice and data
traffic heading into the core where applicable (to MGW or SGSN
accordingly).
8/4/2019 10 8320 Final Model With Tracks Mobile
37/83
New mobile long-run incremental cost (LRIC) model | 33
Ref: 13392-86b .
7 Expenditure
The network design algorithms compute the assets (network elements) that are required to support
a given demand in each year. A series of steps are then undertaken in order to arrive at the
schedule of capex and opex over the modelling period. These steps are detailed below and
summarised in the remainder of this section:
defining the list of assets on theInAssetworksheet (Section 7.1)
summarising the assets required in the network over time on the FullNw worksheet (Section
7.2)
determining the assets purchased in each year on theNwDeploy worksheet (Section 7.3)
calculating the unit cost trends for each asset over time on the CostTrends worksheet (Section
7.4)
calculating the unit capex over time on the UnitCapex worksheet (Section 7.5)
calculating the unit opex over time on the UnitOpex worksheet (Section 7.6)
calculating the total capex over time on the TotalCapex worksheet (Section 7.7)
calculating the total opex over time on the TotalOpex worksheet (Section 7.8).
7.1 WorksheetInAsset1. Standard cost
inputs
For a given set of cost input categories, specifies an assumed lifetime,
planning period, proportion of asset replaced per annum and opex as a
proportion of capex for each category [1,2].
2. Inputs by asset For each asset, specifies:
asset name
cost category
cost input category (from the list in the table of standard cost
inputs)
year of first possible deployment of asset [1]
first year of cost recovery of asset [1]
final year of capex (after which no further replacement capex is
8/4/2019 10 8320 Final Model With Tracks Mobile
38/83
New mobile long-run incremental cost (LRIC) model | 34
Ref: 13392-86b .
incurred) [1]
final year for cost recovery [1]
retirement period2
lifetime, planning period, proportion of assets replaced per
annum and opex as a proportion of capex based on the cost
input category [1,2]
[1]
unit capex in real 2010 SEK [1, 2, 3]
unit opex in real 2010 SEK [1, 2, 3].
Some additional cost inputs [1, 2, 3] are placed to the right of these
columns.
7.2 Worksheet FullNw1. Network
elements by year
Pulls together the assets required in the modelled network for each year
in the modelling period.
2. Network
elements,
accounting fornetwork activation
This switches off assets that are being specified either:
out of the scope of the modelled network configuration
outside the network lifetime.
7.3 WorksheetNwDeployThe network design algorithms compute the network elements that are required to support a given
demand in each year. In order for these elements to be operational when needed, they need to be
purchased in advance, in order to allow provisioning, installation, configuration and testing before
they are activated. This is modelled for each asset by inputting a planning period between 0 (noplanning required) and 18 months. The number of assets purchased in each year is derived on this
worksheet, accounting for:
additional assets required to provide incremental capacity
equipment that has reached the end of its lifetime and needs to be replaced
2
By setting the value to 0, 1 or 2, the model will remove the assets as traffic reduces, either in the same year, oneyear later, or two years later respectively. By setting the value to 100, the model will retain the asset in the networkuntil the last year of operation.
8/4/2019 10 8320 Final Model With Tracks Mobile
39/83
New mobile long-run incremental cost (LRIC) model | 35
Ref: 13392-86b .
advanced purchase in both cases based on the assumed planning period.
The steps taken are described below.
1. Required units
in full network
Links in the network elements, accounting for network activation from
theFullNw worksheet.
2. Deployed assets
with retirement
algorithm
Determines the maximum number of units required of each asset and the
first year in which this maximum is reached.
3. Annual
activation
(including
replacement)
Calculates the difference between the number of units required and the
number of units previously deployed that are still active (this does not
remove assets before the end of their lifetime even if they are no longer
required).
4. Direct equipment
purchases (incl.
replacement)
Determines the equipment required across all replacement cycles,
purchased prior to activation based on the planning period (fractional
units of purchase are permissible on the basis that they reflect phasing
of purchase over each modelled year).
5. Direct equipment
purchases (for
network
regeneration only)
Determines asset replacement (where activated for a given asset) on the
basis that equipment is purchased as part of the constant renewal of
parts of the network, rather than using the asset lifetime as the trigger
for replacement.
7.4 Worksheet CostTrendsThe cost of purchase for network assets varies over time. In the economic costing approach, the
modern equivalent asset (MEA) provides the appropriate cost basis for purchase. Real-term unit
asset cost trends are applied to 2010 unit asset costs to reflect the evolution of the modern
technology unit asset costs over past and future time. The evolution of MEA unit asset costs also
provides an important input into the economic depreciation calculation, as described in Section 8.
Certain quantities for the economic depreciation calculation, including the capex/opex indices, arealso calculated on the CostTrends worksheet.
These calculations are described below.
1. Equipment capex
trends
Specifies the year-on-year change in capex trends over time for a set of
specified categories [1, 2].
Determines the year-on-year change in capex trends for each asset,
based on a specified category.
Calculates the cumulative year-on-year change in capex trends for each
8/4/2019 10 8320 Final Model With Tracks Mobile
40/83
New mobile long-run incremental cost (LRIC) model | 36
Ref: 13392-86b .
asset, indexed with the first modelled year set to be 1.
Multiplies this capex index by the network element output, which is
described in Section 8.3, to give the capex cost-weighted output.
2. Equipment opex
trends
Specifies the year-on-year change in opex trends over time for a set of
specified categories [1].
Determines the year-on-year change in opex trends for each asset, based
on a specified category.
Calculates the cumulative year-on-year change in opex trends for each
asset, indexed with the first modelled year set to be 1.
Multiplies this opex index by the network element output, which is
described in Section 8.3, to give the opex cost-weighted output.
7.5 Worksheet UnitCapex1. Unit capex per
network element
Calculates the unit capex by asset in each modelled year, using the
MEA capex index, scaled by the capex index value in 2010. This
ensures that the unit capex is determined relative to the base year of the
inputs, which is 2010.
2. Shut-down capex
profile
Determines a binary multiplier, which is zero where an asset is assumed
to no longer incur replacement capex; otherwise, the binary multiplier is
one.
7.6 Worksheet UnitOpex1. Unit opex per
network element
Calculates the unit opex by asset in each modelled year, using the MEA
opex index, scaled by the opex index value in 2010. This ensures that
the unit opex is determined relative to the base year of the inputs, whichis 2010.
2. Shut-down opex
profile
Determines a binary multiplier, which is zero when an asset has been
assumed to be completely removed from the network; otherwise, the
binary multiplier is one.
7.7 Worksheet TotalCapex1. Total annual
Multiplies the unit capex derived in the UnitCapex worksheet by thenumber of assets purchased in each year, calculated in the NwDeploy
8/4/2019 10 8320 Final Model With Tracks Mobile
41/83
New mobile long-run incremental cost (LRIC) model | 37
Ref: 13392-86b .
capex worksheet.
The capex is set to be zero for those assets in those year when the shut-
down profile for capex from the UnitCapex worksheet is zero.
2. Category totals Aggregates the total capex by asset derived above by cost category.
Cumulates the capex by cost category over time, starting in the first year
of the modelling period.
7.8 Worksheet TotalOpex1. Total annual
opex
Calculates the working capital allowance in each year (currently
assumed to be 30/365 of the weighted average cost of capital (WACC)).
Multiplies the unit opex derived in the UnitOpex worksheet by the
number of assets active in the network in each year, calculated in the
NwDeploy worksheet.
The opex is set to be zero for those assets in those year when the shut-
down profile for opex from the UnitOpex worksheet is zero.
The opex is also uplifted by the working capital allowance.
2. Category totals Aggregates the total opex by asset derived above by cost category.
8/4/2019 10 8320 Final Model With Tracks Mobile
42/83
New mobile long-run incremental cost (LRIC) model | 38
Ref: 13392-86b .
8 Depreciation
This section describes the implementation of the economic depreciation algorithm used in PTSs
new mobile LRIC model. We describe this algorithm in several stages:
overview of the conceptual approach and the principles of the implementation (Section 8.1)
description of the location of the key inputs to economic depreciation (routeing factors,
network element output and discount rates respectively) (Sections 8.2, 8.3 and 8.4)
description of the calculation steps implemented to derive economic costs (Section 8.5).
8.1 Overview of economic depreciationBelow we describe the conceptual approach and the implementation principles of economic
depreciation.
8.1.1Conceptual approachAn economic depreciation algorithm recovers all efficiently incurred costs in an economically
rational way by ensuring that the total of the (cost-oriented) revenues generated across the lifetime
of the business are equal to the efficiently incurred costs, including cost of capital, in present value
(PV) terms. This calculation is carried out for each individual asset class, rather than in aggregate,in order to allow the price trends and opex cost trends for each asset to be reflected.
The calculation of the cost recovered needs to reflect the time value of money. This is accounted
for by the application of a discount factor on future cashflows, which is equal to the WACC of the
modelled operator.
The business is assumed to be operating in perpetuity, and investment decisions are made on this
basis. This means it is not necessary to recover specific investments within a particular time horizon
(e.g. the lifetime of a particular asset), but rather throughout the lifetime of the business. In the
economic depreciation model, this situation is approximated by explicitly modelling a period of50 years. At the real discount rate applied (which is derived using the WACC), the PV of the
cashflows in the last year of the model is very small and thus any perpetuity value beyond 50 years
is regarded as immaterial to the final result.
The constraint on cost recovery (NPV of costs = NPV of output calculated unit costs) can be
satisfied by (an infinite) number of possible cost-recovery profiles. However, it would be
impractical and undesirable from a regulatory pricing perspective to choose an arbitrary or highly
8/4/2019 10 8320 Final Model With Tracks Mobile
43/83
New mobile long-run incremental cost (LRIC) model | 39
Ref: 13392-86b .
fluctuating recovery profile.3 Therefore, we choose a cost-recovery profile that is in line with
revenues generated by the business. In a competitive and contestable market, the revenue that can
be generated is a function of the lowest prevailing cost of supporting that unit of demand, thus the
price will change in accordance with the costs of the MEA for providing the service.4
The efficient expenditure of the operator comprises all the operators efficient cash outflows over
the lifetime of the business, meaning that capex and opex are not differentiated for the purposes of
cost recovery. As stated previously, the model considers costs incurred across the lifetime of the
business to be recovered by cost-oriented revenues across the lifetime of the business. This
principle implies that the treatment of capex and opex should be consistent, since they both
contribute to supporting the cost-oriented revenues generated across the lifetime of the business.
The unit cost
is therefore assumed to follow the MEA unit asset cost trend for that asset class. The cost-recoveryprofile for each asset class is the product of the demand supported by the asset (i.e. its economic
output) and the MEA unit asset cost trend. This gives a unique solution.
8.1.2Principles of implementationThe PV of the total expenditure is the amount which must be recovered by the revenue stream. The
discounting of revenues in each future year reflects the fact that delaying cost recovery from one
year to the next accumulates a further year of cost of capital employed. This leads to the
fundamental equation of the economic depreciation calculation that is:
PV (expenditures) = PV (unit cost output)
The unit cost output which the operator gains from the service in order to recover its
expenditures plus the cost of capital employed is modelled as output year 1 unit cost MEA
price index. This quantity is discounted because it reflects future cost recovery. (Any costs
recovered in the years after a network element is purchased must be discounted by an amount
equal to the WACC in order that the cost of capital employed in the network element is also
returned to the operator.)
output the service volume carried by the network element
MEA price index the cumulated input price trend for the network element which
proportionally determines the trend of the unit cost that recovers the expenditure (effectively,the percentage change to the cost of each unit of output over time).
This leads to the following general equations:
cost recovery (year n) = unit cost in year 1 output MEA price index
3For example, because it would be difficult to send efficient pricing signals to interconnecting operators and their
consumers with an irrational (but NPV=0) recovery profile.
4 In a competitive and contestable market, if incumbents were to charge a price in excess of that which reflected the
MEA prices for supplying the same service, then competing entry would occur and demand would migrate to theentrant which offered the cost-oriented price.
8/4/2019 10 8320 Final Model With Tracks Mobile
44/83
New mobile long-run incremental cost (LRIC) model | 40
Ref: 13392-86b .
Using the relationship from the previous section, the above equation is equal to:
PV (expenditure) = PV (unit cost in year 1 output MEA price index)
This equation can be rearranged as follows:
unit cost in year 1 = PV (expenditure) / PV (output MEA price index)
Then, returning to the original equation for cost recovery in yearn, the yearly price over time is
simply calculated as:
yearly unit cost over time
This yearly price over time is calculated separately for the capex and opex components in one step
in the model.
= unit cost in year 1 MEA price index
8.2 WorksheetRFsRouteing factors determine the amount of each elements output required to provide each service.
The routeing factors used in the model are average traffic routeing factors and are converted into
equivalent traffic measures using a number of derived conversion factors. All of these inputs can
be found on this worksheet.
1. Source
calculations
Links in a series of standard technical parameters [1, 5].
Calculates factors for conversion of the following quantities on the airinterface into minute equivalents:
SMS, separately for GSM and UMTS
GPRS megabytes, separately for handset/mobile broadband
traffic
EDGE megabytes, separately for handset/mobile broadband
traffic
R99 megabytes, separately for handset/mobile broadband traffic
HSDPA megabytes, separately for handset/mobile broadband
traffic
LTE megabytes, separately for handset/mobile broadband
traffic.
Calculates factors for conversion of data traffic on transmission links.
2. Routeing factor For a list of asset measure options, derives a routeing factor for that
8/4/2019 10 8320 Final Model With Tracks Mobile
45/83
New mobile long-run incremental cost (LRIC) model | 41
Ref: 13392-86b .
options option for each of the modelled services.
3. Full routeing
factor table
For each asset and each modelled service, identifies the routeing factor
from the above table based on the asset measure option for that asset.
[1]
8.3 WorksheetNwEleOutThe quantity of network element output, by asset over time, is used as the basis on which to derive
economic costs. This quantity is taken to be the annual sum of service demand produced by the
asset, weighted according to the routeing factors of that asset for the modelled services. Network
element output is calculated on theNwEleOutworksheet.
1. Service demand
for the whole
market
Links in the service volumes for the modelled network over time from
theNetworkLoadworksheet.
2. Service routeing
factors
Links in the full routeing factor table from theRFworksheet.
3. Recovery profile Currently set to be 0% before cost recovery is assumed to start and after
cost recovery has ended, 100% otherwise.
4. Recovery profile
in binary form
Currently set to be 1 if the corresponding entry in the recovery profile
above is nonzero, and zero otherwise.
5. Network element
output
Calculated as:
service volumes routeing factors binary profile
8.4 WorksheetDFThe model operates in real terms and hence requires a real discount rate with which the modelled
cashflows can be discounted when deriving present values. This is derived using the real cost of
capital, specified on the Ctrlworksheet.
1. Discount rate
data
Links in the real discount rate (WACC) [4].
Derives the real discount rate multiplier.
Derives the real discount rate divider.
Derives the inflation multiplier from the retail price index [4].
8/4/2019 10 8320 Final Model With Tracks Mobile
46/83
New mobile long-run incremental cost (LRIC) model | 42
Ref: 13392-86b .
8.5 WorksheetEDThis worksheet is where the economic costs of capex/opex are calculated over time, using the
above inputs and the unit asset cost trends from the CostTrendworksheet, described in Section 7.4.
1. Capex per
unit output
Calculated separately for each asset across the modelling period.
Derived as the capex index over time scaled by a constant factor.
This factor is the ratio of the cumulative discounted asset capex and the
cumulative discounted capex weighted output (referred to as
PV(expenditure) / PV(outputMEA price index) above).
2. Opex per
unit output
Calculated separately for each asset across the modelling period.
Derived as the opex index over time scaled by a constant factor.
This factor is the ratio of the cumulative discounted asset opex and the
cumulative discounted opex weighted output (referred to as
PV(expenditures) / PV(outputMEA price index) above).
This is calculated separately to the capex per unit output since the asset
unit capex trend could differ to the asset unit opex trend.
3. Total cost per
unit output
Calculates the sum of the capex per unit output and the opex per unit
output, multiplied by the binary recovery profile.
4. FAC per
service unit
Calculates the multiplication of the cost per unit output matrix and the
routeing factor matrix to give unit fully allocated costs (FAC) by
service.
5. Total economic
costs
Calculates the total cost per unit output multiplied by the network
element output.
Calculates the total economic costs over time.
Calculates the total discounted economic costs over time.
Calculates the cumulative discounted economic costs over time.
Calculates the present value of the economic costs.
6. Total costs
recovered by FAC
Multiplies the FAC per service unit by the modelled network service
volumes.
Calculates the total discounted FAC.
8/4/2019 10 8320 Final Model With Tracks Mobile
47/83
New mobile long-run incremental cost (LRIC) model | 43
Ref: 13392-86b .
8/4/2019 10 8320 Final Model With Tracks Mobile
48/83
New mobile long-run incremental cost (LRIC) model | 44
Ref: 13392-86b .
9 Results
The model calculates service costs using both LRAIC and pure LRIC principles. The outputs of
these calculations can be found on theResults worksheet.
The remainder of this section describes these calculations, as set out below:
Section 9.1 describes how the LRAIC (and LRAIC+) are derived in the model
Section 9.2 describes how the pure LRIC is derived in the model
Section 9.3 describes where to find the major outputs of the model.
9.1 Calculation of LRAIC(+)This calculation takes the total economic costs for each network asset, and applies a proportion to
that asset, derived on the Common worksheet. This proportion is the number of assets assumed to
be common to all services in the network, expressed as a percentage of the total assets. These costs
are then entirely included within the common cost base.
On theED worksheet, the cost per unit output calculated for each asset is separated into common
and incremental components using the common cost proportions derived on the Common
worksheet. Incremental service costs are derived by multiplying the incremental cost per unit
output by the routeing factors according to the following equation:
),()(___cos)( kiassets
ik serviceassetctorRouteingFaassetoutputunitpertServiceCost =
Total common costs (network common costs and business overheads) are then marked up onto
each incremental service cost in an equi-proportional manner, according to the ratio of common to
incremental network costs, resulting in the LRAIC+. This approach is illustrated below in Figure
9.1.
Figure 9.1: Illustration ofLRAIC+ costing
approach [Source:
Analysys Mason ]
Incremental cost ofall traffic
(MSC, BSC, radio sites, etc.)
Network share of business overheads
Subscriber
SIM
Network common costs
(some coverage, spectrum)
E
P
M
U
E
P
M
U
8/4/2019 10 8320 Final Model With Tracks Mobile
49/83
New mobile long-run incremental cost (LRIC) model | 45
Ref: 13392-86b .
Below we describe the derivation of the common cost proportions on the Common worksheet,
followed by a description of the remaining calculations required for the LRAIC (and LRAIC+) on
theLRAIC+ worksheet.
9.1.1Worksheet CommonThe common cost proportions are derived on this worksheet, so that incremental and common
costs can be separated within the model.
1. Source
calculations
Links in GSM and UMTS coverage sites separately.
Determines the number of common coverage sites in each year [1].
2. Full table of
common number
of assets
Calculates the number of common assets (i.e. used by both GSM and
UMTS networks).
3. Full table of
common cost
proportions
For each asset, calculates common assets as a proportion of total assets
over time [1].
9.1.2WorksheetLRAIC+
On this worksheet, economic costs are mapped to services and mark-ups are applied.
1. Total economic
costs
Links in the total economic costs by asset over time from the ED
worksheet.
2. Total common
costs
Multiplies the total economic costs by the common cost proportions
from the Common worksheet.
3. Total
incremental costs
Derives the difference of the economic costs and common economic
costs.
4. Calculation of
mark-ups
Calculates common economic costs as a proportion of incremental
economic costs in order to arrive at the equi-proportional mark-up
(EPMU).
5. Calculation of
unit LRAIC
Calculates the incremental cost per unit output by multiplying the total
cost per unit output from the ED worksheet by the common cost
proportions.
Multiplies the incremental cost per unit output matrix and the routeing
factor matrix to arrive at the unit LRAIC by service.
8/4/2019 10 8320 Final Model With Tracks Mobile
50/83
New mobile long-run incremental cost (LRIC) model | 46
Ref: 13392-86b .
Multiplies the unit LRAIC by service by the network service volumes to
derive the total LRAIC by service.
For a selected year, calculates the breakdown of network service unit
costs by asset and service, by multiplying the incremental cost per unit
output in that year by the routeing factors.
Aggregates this breakdown by cost category.
Calculates the total network service costs by asset and service for the
selected year, and aggregates this breakdown by cost category.
6. Calculation of
unit LRAIC+
Applies the derived EPMU to the unit LRAIC by service to derive the
unit LRAIC+ by service.
Derives the total LRAIC by service.
Multiplies the unit LRAIC+ by service by the network service volumes
to derive the total LRAIC+ by service.
Calculates the discounted LRAIC+ by service and the total present
value of the LRAIC+.
7. Calculation of
cost recovery
Calculates LRAIC+ by service group.
Calculates the total cumulative LRAIC+ by service group.
9.2 Calculation of pure LRICThis requires that the model is run in two different states: with and withoutmobile terminated
traffic on the modelled network. Clicking on the Run Pure LRIC and LRAIC+ macro button on
the Ctrl worksheet will result in the model calculating twice the total capex and total opex
required by asset over time in each case is then pasted on thepureLRICworksheet. The pure LRIC
of termination is then calculated as shown below in Figure 9.2.
8/4/2019 10 8320 Final Model With Tracks Mobile
51/83
New mobile long-run incremental cost (LRIC) model | 47
Ref: 13392-86b .
Figure 9.2: Calculation of pure LRIC [Source: Analysys Mason]
The difference in both capex and opex (the avoidable costs) is determined from the two model
calculations, and economic depreciation is then applied to this difference. This is run separately for
capex and opex, in order to use their respective unit asset cost trends. The pure LRIC of
termination in each year is then calculated as the total economic cost in that year divided by the
total terminated minutes.
Another option for the pure LRIC calculation is also included within the model. The above
approach is the economic cost of the difference in expenditure. An alternative approach is to
simply take the difference in the economic costs of the two modelling states. This is derived at
the bottom of thepureLRICworksheet.
A comparison of the avoidable cost base within the pure LRIC costing approach compared with
the average incremental cost base is shown below in Figure 9.3.
Figure 9.3: Comparison of LRAIC+ with the pure LRIC approach [Source: Analysys Mason]
These calculations are all undertaken on thepureLRICworksheet, as described below.
Run model
with all
traffic
Run model
with all
traffic
except
termination
increment
volume
Expenditure with
voice
termination
(asset, time)
Output profile
with voice
termination
(asset, time)
Expenditure
without voice
termination(asset, time)
Output profile
without voice
termination
(asset, time)
Difference in
expenditure
(asset, time)
Difference in
output (asset,time)
Capex and opex
cost trends
(asset, time)
Economic cost
of difference in
expenditure(asset, time)
Total economic
cost of the
difference in
expenditure (time)
Pure LRIC per
minute (time)
Voice
termination
traffic minutes
(time)
Key Input Calculation Output
Incremental cost ofall traffic
(MSC, BSC, radio sites, etc.)
Network share of bus
Top Related