MobileBB_NetworkCost

7/28/2019 MobileBB_NetworkCost

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Mobile BroadbandNetwork Costs

Modelling network

investments and keycost drivers

February 2011

inormatm.com


2/1202

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3/12www.inormatm.com 03

Introduction

Kris Szaniawski

Principal Analyst

Inorma Telecoms & Media

In recent years we have seen an explosion

in mobile data trac driven by signicant

improvements in user experience and at-

rate data plans. Although this has increased

operators data revenue it has also led to a

decoupling o usage and revenue. As usage

increases, costs can now rise aster than

revenues, leading to lower margins.

This shit in the underlying economics o

a network has meant that cost control has

now become the primary strategic ocus o

many operators. As a result, we have received

numerous requests rom our clients or

greater transparency and an understanding

o the uture costs o networks. In response

to this we have undertaken a practical,

robust, independent study o network cost

behaviour and the uture cost per GB.

In order to ully understand network costs

we have built a modelling tool, which

allows us to change key actors and utilise

our incredible wealth o market data and

orecasts. As well as using this tool in our own

analysis and research we are able to:

Work closely with clients to change the

parameters and input options based on

their own criteria

Present our ndings back in an interactive

one-to-one or one-to-many strategysession

Present a number o scenarios, based on a

clients particular criteria

Answer questions and provide advice on

the back o this exercise.

This is a new service or clients and is

principally aimed at network operators

and inrastructure vendors that want an

independent perspective to eed in to their

business strategy, identiy cost savings,

assess vendor claims or to support business

development and marketing activities.

As well as including an example o our

analysis, this document contains urther

inormation on the project and deliverables.

To learn more about the benets it could

bring to your organisation:

call us on: +44 (0)20 7017 4994

or email: [email protected]

Contents

04

Case study on meeting the UK capacitycrunch: LTE not economically viablebeore 015

05

Project scope and methodology

08

The Analysts

10

Utilising our insight


4/1204

Meeting the UK capacity crunch: LTE noteconomically viable beore 2015

Duetotheirdensedeploymenttomeet

coverage requirements, the UKs HSPA

networks will be able to handle current

and uture trac demands. Inorma

does not expect trac congestion to

start appearing until 2013 and even

then only in certain hotspot areas.

Withthecurrentmobileuserbehaviour

patterns in the UK, large-scaleLTE deployment does not oer an

economically viable solution to meet

trac demand.

InformaestimatesthatanewLTE

deployment will cost an additional

US$58 million compared with upgrades

to existing networks, assuming that the

LTE deployment begins during 2013.

Costpergigabyte(cost/GB)intheUK

is orecast to be US$6.79 during 2011,

gradually declining to US$2.74 during

2015.Giventhatnetworkdeployment

is primarily coverage-driven and

networks are densely deployed, there

is signicant unused capacity in the

network throughout the orecast period,

increasingthecost/GBaboveaverage

values.

Background

Inorma has created an end-to-end

mobile-network-planning tool, used here

to identiy key cost drivers when deploying

a new mobile broadband network. Using

Inormas orecasts and subscriber data, it

is possible to model a specic set o inputs

that resemble a real-lie network and draw

conclusions according to the country

prole, subscriber inormation, trac

orecasts and several other parameters. By

changing these parameters, it is possible

to identiy the most cost-ecient long-

term network plan in order to meet trac

demands.

This section presents the background to the

mobile-network-planning tool, including

methodology, input data and orecast used

to power this specic scenario.

The inputs or the simulations in themobile-network-planning tool have been

gathered rom Inormas existing databases,

secondary and primary research; they have

been validated by key contacts in industry,

including operators, vendors, nancial

experts and regulators. More inormation

about the methodology can be ound on

page 8 o this document.

Country and operator prole

The country modelled here is the UK, a

developed market where there is erce

price competition and severe capacity

bottlenecks in densely-populated areas.

Mobile operators are currently upgrading

their existing inrastructure to meet the

trac demands to ensure a high quality o

experience or all mobile broadband users

but under current economic conditions this

is challenging and costly.

As in all Inormas network-planning

simulations, geographic areas are

segmented in our distinct groups:

DenseUrban:Areas that are densely

populated in large cities and consist o

both oces and residential housing.

Urban: Metropolitan areas that surround

the Dense Urban geotype and typically

include some oce but primarily housing

locations.

Suburban:Residential areas with a lower

population distribution. These areas are

likely to exhibit high trac during the

evening, when subscribers are at home.

They are also the most demanding in

terms o geographical area to be covered.

Source: Inorma Telecoms & Media

Rural

12%

25%

27%

36%

Suburban

Urban Dense Urban

Fig 2

UK, population distribution


Fig 1UK, geographical inputs

Country UK

Total population (mil.) 61.6

Population annual growth rate (%) 1.0

Geotype Area (km2)

DenseUrban 11,076

Urban 44,306

Suburban 75,775

Rural 113,663

Dimitris Mavrakis

Senior Analyst

[email protected]

Twitter: @dmavrakis


5/1205www.inormatm.com

Rural: Large areas o open country with a

low population distribution and typically

lower capacity/trac requirements.

Almost two-thirds o the UK population can

be ound in the Dense Urban and Urban

areas, which only account or 3% o the

countrys land area (see gs. 1 and ).

Although Suburban and Rural geotypes

cover by ar the largest share o geographical

area in the UK, the Dense Urban and Urban

locations present the biggest challenge

or mobile operators, since they are highly

populated with demanding user groups

Here mobile operators typically limit cell

sizes to a ew hundred meters in order to

increase capacity and deploy a network with

sucient capacity to service these areas.

However, the Suburban geotype will

also present capacity challenges sincecommuters are likely to use the mobile

network in the evening rather than the

morning hours when the Dense Urban

and Urban locations are likely to be

congested creating new bottlenecks in

non-metropolitan areas. Finally, although

networks in rural locations are likely to be

underused, they still need to be deployed in

order to ull regulations and service areas

where there is no copper inrastructure.

Inorma orecasts that the Dense Urban and

Urban areas will generate by ar the largest

share o trac throughout the UK network

between 010 and 015, ollowed by the

Suburban and Rural geotypes (see g. 3).

Typical base stations rom most vendors

oer the capability to extend coverage

beyond the normal cell sizes. However,

this study is ocused on mobile broadband

network planning where most operators

will seek to balance wide coverage area and

high capacity. Traditionally, operators have

sought wider coverage area to cover as

many subscribers as possible with voice-

oriented networks.

However, these networks have not been

subject to severe capacity constraints in

the same way as current mobile broadband

networks are. In these networks, operators

aim to articially reduce cell size so that

more cells cover a certain area, leading to

a higher total o capacity available to data-

hungry subscribers.


0

5000

10000

15000

20000

2010 2011 2012 2013 2014 2015

Rural

Totalda

tatrafc(PBperyear)

Suburban Urban Dense Urban

Fig 3

UK, trac orecast by geotype, 010-015


Dense Urban Up to 1km


6/1206

Inorma has dened the cell sizes to be used

as guidelines in the modelling tool (see

g. 4). The modelling tool initially lays out

cell sites in order to cover the area set by

subscriber and coverage requirements.

However, it is almost certain that capacity

constraints will require upgrades, additional

base stations or even new radio access

technologies to be deployed in order to

ull trac demands and make sure that

subscribers enjoy a consistent mobile

broadband experience. Particularly in

Dense Urban areas, it is common or

capacity constraints to appear within a

year or two assuming that a new network

is deployed today. For mobile operators

that oer mobile broadband services, this

means a constant cycle o upgrades and

assessing whether the time is right to start

the migration to LTE or upgrade congested

cell sites with as much capacity as possible

beore upgrading to LTE.

Results

Network simulations illustrate that there is

signicantly more capacity than currently

required in the UK network. Coveragerequirements are currently driving network

deployments and simulations show that

network-wide capacity restrictions will be

not be reached throughout the orecast

period, even though a relatively high

average consumption per active device has

been used.

Although coverage requirements are driving

deployment in order to cover as many

potential subscribers as possible with 3G/

HSPA technologies capacity bottlenecks

are expected to orm during the latter years

o the orecast period. Inorma expects these

trac bottlenecks to seriously degrade the

user experience or this mobile network in

certain areas. When this point is reached,

the mobile operator will be presented with

the choice o either upgrading the existing

radio networks with additional capacity (or

example, new HSPA carrier introduction,

upgrade to HSPA+ or existing HSPA sites,

MIMO or HSPA+) or commencing the

migration to LTE in order to enjoy longer-

term cost savings.

The close-knit distribution o base stations in

Dense Urban areas satises current capacity

requirements even though these areas are

data-hungry and requently perceived as

congested. The Dense Urban and Suburban

areas are expected to experience congestion

during 013 and the Rural areas during 01,

ater which upgrades will be necessary.

However, as Rural areas are usually covered


0

5000

10000

15000

20000

25000

30000

2010 2011 2012 2013 2014 2015

Rural Suburban Urban Dense Urban

Totalins

talledb

asestations(000s)

Fig 5

UK mobile broadband operator orecast, total installed base stations, 010-015


0

100

200

300

400

500

600

2011 2012 2013 2014 2015

Rural Suburban Urban Dense Urban

NetworkTCO(US$millions)

Fig 6

UK mobile broadband operator orecast, annual network TCO, by geotype, 011-015


7/12

by deployments that are very sparse (typical

cell radius may be as high as 10km), capacity

constraints are expected when coverage

is the most dominant deployment actor.

Moreover, simple capacity upgrades, such

as upgrading HSPA sites to 64QAM, or even

deploying a ew hundred sites will solve the

capacity constraint in Rural areas; in contrast,

capacity constraints in the Urban areas will

require more intensive expenditure but

these are not expected to happen during the

orecast period.

The number o required base stations

that are primarily driven by coverage

requirements are expected to rise rom

13,846 at the end o 010 to 9,703 by the

end o 015 (see g. 5).

From this, the annual total cost o ownership

(TCO) or the mobile network was calculated

(see g. 6), which also included:

Depreciated capex or continuous

build-out to increase coverage in all

geographical areas. Capex is dominated

by base-station costs, site construction,

engineering & support, core network

equipment and spare parts.

Opex includes backhaul, site leases,

utilities, maintenance and various other

costs that recur on a monthly basis.

The TCO is primarily driven by base-station

build-out in the Dense Urban and Suburban

areas that are expected to meet capacity

constraints during 013.

These orecasts enable the cost o supplying

a GB over the next ve years to be calculated

(see g. 7).

Inorma viewpoint

Given that signicant capacity constraints

will not appear in the mobile network until

ater 01 and only in areas which are prone

to congestion (Dense Urban and Rural

locations), deploying LTE is not economically

viable when existing sites can be eectively

upgraded to cater or capacity demands. In

Dense Urban areas, mobile operators have a

variety o cost-eective options to upgrade

their existing network:

Adding new HSPA carriers in congested

areas.

Introducing MIMO, Dual Cell HSPA+ and

6-sector sites are also advanced techniques

that may prolong the lie o existing HSPA

networks.

Cost per gigabyte (cost/GB) in the UKis orecast to be US$6.79 during 011,

gradually declining to US$.74 during

015. In the early years o the orecast,

cost/GB may not be a relevant metric since

deployment is coverage-driven and there is

unused capacity in the network. However,

as the usage o the network increases,

cost/GB drops sharply and aligns with the

cost/GB gures usually cited by network

vendors. In any case, existing mobile

broadband networks are cost-eective

even in demanding trac scenarios and

are expected to remain so throughout the

orecast period. However, it is possible that

drastic changes in mobile user behaviour

may trigger even urther trac generation,

which will congest networks quicker, orcing

operators to upgrade to LTE aster.

Inorma does not expect LTE to be

deployed in the UK market beore 015

due to the existing dense deployment o

HSPA networks, which can cater or the

current and near-term uture mobile trac

demands. However, there may be alternative

reasons to deploy LTE these include being

rst in the market with a 4G technology or

where there is a mobile broadband network

that has not been constantly upgraded to

meet trac demands.

This is an extract from our analysis into

deploying LTE in the UK. The full research and

analysis is available to clients through the

Networks channel of the Intelligence Centre.


0

1

2

3

4

5

6

7

8

20152014201320122011

6.79

4.61

3.66

3.092.74

C

ost/GB

(US$)

Fig 7

UK mobile broadband operator orecast, cost/GB, 011-015

07www.inormatm.com


8/1208

Project scope and methodology

In order to calculate the Total Cost o

Ownership(TCO)ofamobilenetwork,

several aspects have to be included in

network planning in order to capture

critical elements o the mobile network

that aect cost. Thereore, an end-to-

end mobile network has been designed,

includingRAN,backhaulandcore(seeg.

1).Severalparametersforeachstageof

the mobile network have been included in

order to address current operator demands,including3.9Gradioaccessnetworks,

ofoad, MIMO and emtocells, as well as

popular backhaul technologies to address

capacity bottlenecks while reducing costs.

Contrary to traditional orecasts and data,

the CPG methodology does not calculate

data or a region or country but only or an

operator. Since network deployment plans,

network costs and trac characteristics

dier signicantly per operator, it is not

easible to introduce a generic network

deployment plan or a whole country.

However, the coverage target or most

mobile broadband operators is nearly 100%

o the country population in the long term

but only a raction o the trac throughout

the national inrastructure will take place

through a single operator.

In order to avoid inconsistency by

generalizing network design and

dimensioning, only single operators are

modelled. Moreover, all assumptions are

clearly stated, especially those that are critical

to the overall cost o the network. Theseparameters include over-provisioning actors

(or RAN, backhaul and core), RAN capacity

specications, busy-hour dimensioning and

upgrade options.

Contrary to TCO, the cost/GB metric is only

relevant in certain cases and phases o the

mobile broadband network. In the early

phases o deployment, when coverage is

the driver or deployment (in rst years o

mobile broadband, there is usually a lag

between the mobile network deployment

and an average network utilization), costs

are high due to deployment and trac is

low, the cost/GB metric is ar higher than an

average value and can reach US$00/GB.

However, this value is not indicative and not

relevant until the mobile network is being

well-used. Network TCO is a better indication

o costs during these early phases but cost/

GB can still illustrate the dierence when

choosing to implement an enhancement in

the mobile network (ofoad or optimization).

In the advanced stages o deployment, when

the mobile network is well-used, cost/GB

can illustrate the dierence in cost betweendierent network upgrade options and

provide visibility or critical decisions; or

example, whether to deploy LTE early or to

upgrade the current network to HSPA+ and

roll out LTE when network reaches saturation?

Several parameters have been introduced

into the model, primarily grouped in our

distinct categories:

Population inormation: Including

addressable population, distribution

between our geotypes (Dense Urban,

Urban, Suburban and Rural), operator

subscriber base and subscriber targets.


Radio Backhaul Core Internet

RAN: various technologies

Macro, miciro, pico and

femto

New carrier introduction Spectrum

Wi-Fi ooad

Antennas (MIMO)

Network Sharing

Site costs

Leasing, ber, copper,

hybrid

Deploying: ber, RF

(PTP & PTMP) Carrier Ethernet costs

Statistical multiplexing

EPC, SAE costs

Capacity upgrades

Optimization

Policy and priority-basedmanagement

Fig 1

Mobile network design



These parameters in part dictate network

deployment according to coverage

requirements, which may also be driven

by strict regulations tied to the associated

spectrum acquisition.

Country inormation: Including total area

segmented by the our geotypes and

coverage requirements.

Trac demand: Base data that is driven bytrac orecasts, which include real trac

collected rom live networks coupled

with Inormas expert orecasts. More

inormation on Inormas trac orecast

methodology is available upon request

Network deployment: Several parameters

are provided to the network deployment

algorithm, which calculates the number o

base stations, needed to satisy capacity

and coverage demands. Base station

numbers ultimately drive backhaul and

core but over-provisioning (capacity or

backhaul and capacity/signalling or core)

are also implemented.

Inorma has created a high-level overview othe our distinct groups o parameters that

are used to calculate network TCO and cost/

GB (see g. ).


Total population

Distrubution

(per geotype) Operator

subscriber base

and targets

Total area (per

geotype)

Coveragerequirements

Capacity

requirements

Per technology Per geotype

Per device type

Per subscriber

Indoor/outdoor

Spectrum

Technology

Backhaul Core network

Ofoad

Optimization

Population

inormation

Country

inormation

Trafc

demand

Network

deployment

Network TCO

Cost/GB

Fig 2

Cost/GB calculation inputs


10/1210

The Analysts

Dimitris Mavrakis

Senior Analyst

Inorma Telecoms &

Media

Dimitris Mavrakis is a

Senior Analyst with Inorma Telecoms &

Media. He is part o the Networks team

where he covers a range o topics including

Next Generation Networks, IMS, LTE, WiMAX,

OFDM, core networks, network APIs andidentiying emerging strategies or the

mobile business. Dimitris is also actively

involved in Inormas consulting business and

has led several projects on behal o Tier-1

operators and key vendors.

Dimitris has over 6 years experience in

the telecommunications market. He has

a strong background in mobile and xed

networks and an in depth understanding o

market dynamics in the telecoms business.

In the past, Dimitris has worked as a project

leader to perorm challenging network

measurements and has lead a team o

researchers to produce pioneering research

and acclaimed publications.

Dimitris holds a PhD in Mobile

Communications and a MSc in Satellite

Communications rom the University o

Surrey.

[email protected]

Gareth Sims

Head of Forecasting

Inorma Telecoms &

Media

Gareth is Head o

Forecasting within Inorma Telecoms &

Medias Industry Research division, leading

its centralised orecasting team. In his role

Gareth is responsible or the management

and development o Inorma Telecoms &Medias orecasts covering the mobile, xed

and media industries. Over the last eight

years he has spearheaded the development

o numerous orecasting products, spanning

a range o sectors rom devices and networks

through to applications and services. He

also manages the orecasts within WCIS, an

industry leading market intelligence database

whose numbers are quoted extensively

throughout the ICT Industry.

His most recent work involved building a

mobile network planning tool to help identiy

the most cost eective ways that operators

can deploy uture networks.

Gareth has over ten years experience in

statistical and nancial modelling in the

ICT industry. Beore joining Inorma, Gareth

worked as a commercial analyst or MCI

where he ocused on European telecom

pricing.

Gareth holds a degree in Business Economics

in which he specialised in Econometrics.

[email protected]

Kris Szaniawski

Principal Analyst

Inorma Telecoms &

Media

Kris is a Principal Analyst

with Inorma Telecoms & Media. He heads

up the research programmes and analyst

team tracking the mobile networks and

inrastructure topic area. Kriss areas o

expertise include network vendor strategyand managed services although he tracks

and comments on a broad range o

topics in the mobile space ranging rom

mobile broadband to support systems. His

recent research interests include network

outsourcing and sharing and mobile rural

connectivity in developing markets.

Kris has 17 years experience in the telecoms

sector as a journalist and analyst, including

the last seven years with Inorma Telecoms &

Media and roles beore that with Ovum and

the Financial Times group. He has worked

on a wide range o business intelligence

services, reports and consulting projects

and contributed to numerous industry

publications and events.

Kris holds a Masters degree in European

politics, business and law and a combined

honours degree in English and social sciences.

[email protected]



Customized insight, analysis and advicemodelled on the basis o your inputs

Given the nature o this project, the

deliverables are heavily customised to

meet the needs o our clients. During the

process we will work closely with you

and key stakeholders to look at trac

demand scenarios, network deployment

scenarios and costs, and then we take

your specifc inputs such as:

devicetype geotype

technology

ooad(femtocell,Wi-Fi)

optimisation

backhaul

corenetworktype.

Once the model has been built using your

criteria and inormation, our analysts will

present our ndings through a dedicated

and interactive strategy session to discuss theresults with you or work with you to explore

the dierent outcomes and provide advice.

Plus, all clients will receive an exclusive copy

o our Mobile Broadband Network Costs

report, which includes analysis o sample

scenarios.

Why participate?

Operators:

Createyourownnetworkprolespecic

to your customer demands

Usebuilt-inscenariostohelpmodelyour

network

Proleyourcompetitorsnetwork

EvaluateNetPresentValue(NPV)of

network deployment options

Modeltracbydevicetypeandgeotype

Comparevendorclaimswithan

independent and validated tool.

Vendors:

Proleyourcustomersnetworksto

understand their uture requirements

compared to your own

UseCost/GBtoillustratetheeectofyour

solution in a real-lie network and how it

can reduce costs or the operator

UseCost/GBaspointofcomparisonandto

validate existing methodologies you may

be using or network analysis.

Investor community and nancial

institutions:

Assessinvestmentdecisionsbeingmade

by operators and the choices available to

them

Evaluatevendormessagesandoerings

and the impact it will have on costs

Tosupportstrategicadvice.

Why partner with Inorma Telecoms &

Media?

WehaveextensiveNetworktechnology

expertise provided by a dedicated team

tracking, analysing and consulting on

the inrastructure market, LTE and other

mobile access technologies, backhaul,

emtocells and policy management

Ourresearchbenetsfromunparalleled

access to key industry gures via our

conerence communities, including

the industrys leading annual event,

Broadband Trac Management Congress.

Ourstrategicinsightissupportedbya

comprehensive range o primary data

sources including WCIS and WBIS

Ourclosepartnershipwithakeysetof

collaborators to allow us to compare

notes on methodologies and modelling

approaches and to validate our inputs

Wehaveaprovenintegratedapproach

to orecasting. Uncertain and dynamic

environments such as the mobile

broadband market require a collaborative

orecasting methodology. We use this

approach to integrate both industry and

modelling expertise, to share ownership,

create a holistic view o the market

and ultimately ensure high levels o

consistency and robustness

Ourscenario-basedtracforecasting

model is one o the oundations o this

project. We have built on three-years-

worth o trac orecasting experience.


12/12

www.inormatm.com

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