developed for Oftel by Analysys, September 2001

friendlybathMobile - Wireless

Nov 12, 2013 (3 years and 9 months ago)

140 views

[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 method

e.g. LRIC, LRIC+

Costs

Other factors

e.g. externalities

Costing method

e.g. forward
-
looking

economic costs

Data

e.g. unit

input costs

Assumptions

e.g. demand

forecasts



Background

10

The models developed for Oftel by Analysys
only

derived the costs of mobile
termination, and enabled a number of mark
-
up regimes to be applied



Prices

Pricing method

e.g. LRIC, LRIC+

Costs

Other factors

e.g. externalities

Costing method

e.g. forward
-
looking

economic costs

Data

e.g. unit

input costs

Assumptions

e.g. demand

forecasts

Illustration of

alternatives

not
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
P
2000/01
,
P
2005/06

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 the

LRIC Model of UK Mobile Network Costs


Information about the networks of the four UK mobile network operators was collected from a variety of
sources


in particular the number of base stations, BSCs and MSCs


Information about the coverage and traffic carried by each of the networks was also obtained or estimated


The network design algorithms and parameters in the model were then fixed at reasonable values (based on
general industry data)


A specific parameter of the network design algorithms (the “scorched node utilisation”) was then adjusted
for each network element until the number of units of that element predicted by the model was reasonably
close, for all network operators, to the actual number of units of that element believed to be in use in the real
networks


The resulting value for the scorched node utilisation parameter simply describes how much lower (or
higher) than expected (on the basis of the standard network design algorithms and parameters used in
the model) the actual utilisation of network elements really is


The model can then predict the number of nodes that a 25% market share operator would be likely to have,
with a reasonable degree of accuracy, based on the actual number of nodes in use by the UK operators today

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 flow

Data or

assumptions

Calculations

or 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
-
curve

penetration

Minutes

per sub

MByte user

penetration

2G/3G

partition

2/2.5/3G

partition

MByte

per sub

SMS

penetration

SMSs per

user

2G incoming

minutes

2G outgoing

minutes

SMS

volumes

GPRS

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:

00/01

01/02


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

Coverage

network

design

Full

network

design

Incremental

network

design

Demand inputs

Selected

year

Design

parameters

Coverage

Selected

operator

The model



30

2. Network design to economic cost

Network
design

Selected year

Economic cost

Selected operator

Out
-
turn utilisation profiles

The model



31

D. Economic cost

Economic

lifetime

Annualisation

percentage

Selected year

Selected operator

Out
-
turn utilisation profiles

* Calculation performed for each item

Economic

cost

calculation

00/01 MEA

capex

Opex

trends

00/01 MEA

opex

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

Coverage

network

cost

Incremental

network

cost

Full network

cost

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
-
ups

to recover

common

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

Suburban

Rural

Highway

Area

Population

The model

Cost drivers

40

Notes re implementation in the

LRIC Model of UK Mobile Network Costs


In
-
building penetration is not explicitly quantified in the model


The scorched node approach ensures that the level of in
-
building coverage included in the
model is comparable with that typically provided by UK operators


Likewise, the effects of secondary cost drivers, such as the number of location updates and call
handovers, are not explicitly quantified in the model


The values of other network design parameters have been set conservatively to provide
sufficient capacity to deal with these activities

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




Handsets

Infrastructure 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 service

Traffic

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 throughput

Customers

Costs

Number of location updates

Coverage

Incremental

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

GPRS

HSCSD

Coverage

Voice + SMS

GPRS + HSCSD

Voice +…

… + GPRS

Voice +…

.. + HSCSD

SMS + GPRS

SMS +…

.. + HSCSD

Voice + SMS + GPRS

SMS + GPRS + HSCSD

Voice + SMS + GPRS + HSCSD

Voice + SMS + …

.. + HSCSD

… + GPRS + HSCSD

Voice +…

1,2

3

4

5

6

8

7

9

10

11

Areas are not to scale

Voice represents customers and voice minutes

Fully and separately resolving 8 increments would require 64 separate calculations


Incremental
costs using
single traffic
increment

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

GPRS

HSCSD

Coverage

Voice + SMS

GPRS + HSCSD

Voice +…

… + GPRS

Voice +…

.. + HSCSD

SMS + GPRS

SMS +…

.. + HSCSD

Voice + SMS + GPRS

SMS + GPRS + HSCSD

Voice + SMS + GPRS + HSCSD

Voice + SMS + …

.. + HSCSD

… + GPRS + HSCSD

Voice +…

1,2

3

4

5

6

8

7

9

10

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



BSC

BTS

Inter
-
switch

transmission

BSC

MSC

transmission

Backhaul

transmission

Macro
-
cell

site and TRXs

HLR

MSC

VLR

NMS

Macro
-
cell

site acquisition,
preparation and rental

BSC

BTS

Inter
-
switch

transmission

BSC

MSC

transmission

Backhaul

transmission

Macro
-
cell

BTS and TRXs

HLR

MSC

VLR

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 + HSCSD

Voice +…

… + GPRS

Voice +…

.. + HSCSD

SMS + GPRS

SMS +…

.. + HSCSD

Voice + SMS + GPRS

SMS + GPRS + HSCSD

Voice + SMS + GPRS + HSCSD

Voice + SMS + …

.. + HSCSD

… + GPRS + HSCSD

Voice +…

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

58

Base case demand forecast: outgoing minutes per subscriber per quarter

The model

Demand forecasts

59

Base case demand forecast: incoming minutes per subscriber per quarter

The model

Demand forecasts

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)

t

A

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
-
00

Jul
-
01

Jul
-
02

Jul
-
03

Jul
-
04

Jul
-
05

Jul
-
06

Jul
-
07

Jul
-
08

Jul
-
09

Partition of Mbytes by technology

UMTS

GPRS

HSCSD

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)

t

t
1

t
2

t
3

t
0

growth 1

growth 2

growth 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 operator

by technology

2G/3G

Outgoing voice

minutes

by year quarters

by operator

by technology

2G/3G

SMS messages

by year quarters

by operator

Data transport Mbytes

by year quarters

by technology

HSCSD, GPRS, UMTS

Data transport users

by year quarters

by technology

HSCSD, GPRS, UMTS

identical 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 a

number of principles


Reflect industry practice with regard to base station layout, checked against existing networks


this checking is a combination of parameter calibration and application of industry
experience


Represent the use of modern technology


Satisfy the requirements of coverage and demand


Allow for reasonable growth (but no more)


Contain the key differences between GSM 900 and GSM 1800 radio network deployment


different cell radii and different radio layer spectral efficiency*


The model contains around 60 different units of equipment, sufficient to capture the required
fidelity in network design, yet small enough to be manageable


The model

Network design

* Spectral efficiencies vary between GSM 900 and GSM 1800 networks in the UK because the 900MHz spectrum allocation is more f
rag
mented


than the 1800MHz spectrum allocation

68

Simplified network diagram

BSC

BTS

Inter
-
switch

transmission

BSC

MSC

transmission

Backhaul

transmission

Macro
-
cell

site and TRXs

HLR

MSC

VLR

NMS

Backhaul

transmission

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

Omni

macrocell

Bi
-
sectored

macrocell

Tri
-
sectored

macrocell

Microcell

Picocell

We define a number of area and cell types

Six cell types

Four 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 km
2


Rural


postcode sectors with a population density less than 721 per km
2


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 design

by area type to be reflected


The model contains a number of inputs for:


the proportion of cells of each macro type, in each area type


However, the inputs currently assigned in the model reflect a simplified situation:


tri
-
sectored macro sites are deployed in urban and suburban areas


bi
-
sectored macro sites are deployed in highway areas


omni
-
sectored macro sites are deployed in rural areas


These cell types are deployed in response to the
greater
of coverage or traffic requirements


Micro and pico sites (defined as single sector, 2 and 1 TRX respectively) are deployed in response only to
traffic requirements, and furthermore, only in urban and suburban areas:


the amount of traffic that is carried on these cell layers is specified by a percentage (by area type) of
total traffic in that area type


In the UK, the GSM 900 operators also have GSM 1800 spectrum.. The model deploys a GSM 1800 layer
upgrade to these operators’ urban macro sites, and expands this in response to the amount of traffic loaded
onto this cell layer

The model

Network design

72

The use of a single increment for traffic requires

service demand drivers to be added together


In reality, the radio interface responds differently to voice circuit, GPRS packet and signalling
traffic. However, constructing a complex radio engineering model which separately deals with
these traffic types is not recommended in a LRIC costing exercise


Rules are required to combine traffic from voice, SMS, HSCSD and GPRS in a suitable way


The Oftel model contains
voice equivalent erlangs
:


the amount of traffic equivalent to one voice erlang


rules are defined for converting service demand (eg SMS messages, GPRS Mbytes) into
voice equivalent erlangs


Voice equivalent erlangs can then be added to normal voice erlangs, in order to drive the
network design algorithms with the aggregate traffic load


It is assumed that all services have a coincident busy hour (which may lead to some
overstatement of costs), and highly complex effects (such as different link margins (i.e. cell
radii) for GPRS traffic) are neglected

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% additional

IP 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 GSM

infrastructure

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

erlangs per sector

Area type

Urban

Suburban

Rural

Highway

erlangs per sector

Area type

Urban

Suburban

Simplified average situation

Non
-
homogeneous reality

Rural

Highway

Additional capacity

requirement over

the average

Diagrams not to scale

The model

Network design

79

Equipment utilisation is an important input parameter

to the network design algorithms


A large number of network design calculations are based upon the following relationship:


number of items required = demand / capacity per item * utilisation


The utilisation parameter contained in the Oftel model is used to reflect the explicit combination of a number
of different ‘under
-
utilisation’ effects:


Design utilisation:
most equipment has a (vendor designated) maximum utilisation parameter (for
example, 90%). This utilisation parameter ensures that the equipment in the network is not overloaded
by any transient spikes in demand


Scorched node utilisation:
the deployment of a scorched node network is captured explicitly by the
use of additional utilisation parameters. These indicate the degree to which equipment is unable to
reach the level of utilisation that would be achieved in a scorched earth deployment, as a direct result
of adhering to the scorched node constraint


Reasonable growth utilisation:
in a real mobile network, equipment is deployed in advance of
expected demand (weeks to years), depending on the equipment modularity and the time it takes to
make all the necessary preparations to bring new equipment online. The model explicitly determines
the level of under
-
utilisation in the network, as a function of equipment planning periods and expected
demand.

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) = x
t


define planning period (2p), and determine demand at time half planning
period later:


(demand at time t + p ) = x
t+p


Number of elements deployed at time t, if no future growth:


= x
t

/ (capacity * normal utilisation

)


Number of elements deployed at time t+p, if no future growth:


= x
t+p

/ (capacity * normal utilisation)


Hence actual utilisation of elements at time t, given forward looking
deployment is:


x
t+p

/ (capacity * normal utilisation) = x
t

/ (capacity * actual utilisation)


hence:


actual utilisation = normal utilisation * (x
t

/ x
t+p
)



t

t+p

time

Demand



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 peak

throughput


IP transmission

For each asset class, the key demand driver and

period 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% utilisation

Design 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 sites

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 cover

Maximum cell
area

Sites required for coverage

Number of sites (by type)

used in
TRX

calculations

Non
-
uniform

allowance (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 cover

Maximum cell
area

Sites required for coverage

Number of sites (by type)

used in
TRX

calculations

Non
-
uniform

allowance (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 cover

Maximum cell
area

Sites required for coverage

Number of sites (by type)

used in
TRX

calculations

Non
-
uniform

allowance (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
km
2

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 as

omni
-
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 cover

Maximum cell
area

Sites required for coverage

Number of sites (by type)

used in
TRX

calculations

Non
-
uniform

allowance (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

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
-
uniform

allowance (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
-
uniform

allowance (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
-
uniform

allowance (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

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 site

Sectors 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 site

Sectors 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 site

Sectors 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 hops

Link 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 hops

Link 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 hops

Link 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 utilisation

Processing 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 utilisation

Processing 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)

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 utilisation

Processing 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

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 utilisation

Processing 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 HLRs

HLR capacity

Number of HLRs

HLR utilisation

HLR upgrade capacity

Number of HLR upgrades

The model

Network design

110

HLR capacity (2)

Number of customers

Minimum number of HLRs

HLR capacity

Number of HLRs

HLR utilisation

HLR upgrade capacity

Number of HLR upgrades

HLRs are again driven by a
simple calculation involving
capacity, demand and
utilisation