209 BUSINESS CASE Mobile Broadband

8/12/2019 209 BUSINESS CASE Mobile Broadband

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mobile broadband business case

using this site would be . per or . per subscriber per month. No sitewill ever be utilized to its theoretical maxi-mum, but it could be used up to and above percent. Thus the cost per lands at . and the cost per subscriber at . per month. Adding the site acqui-sition/build into the equation with, forexample, a , investment depre-ciated over years results in around . per . A more loaded site with a configuration brings this cost down toaround . per . A shared G/Gsite with a configuration costs around . per .

If we do the same type of calculation forthe equivalent of a NodeB in a net-work, namely the , the result is asfollows: Assuming a price of around , and an existing site in a suburban

scenario with an average speed of around Mbps, the price per is around ..The opex related to maintaining the cop-per lines will of course add to this cost andadds another .. if we assumethe cost to be shared with voice () andan average consumption of GB permonth.

Traffic distribution in the networks Eric-sson is monitoring (some deployedaround the world) shows that only a fewsites carry most of the traffic. A normalscenario shows around percent of the

sites carrying more than percent of totalnetwork traffic.This means that most of the sites

deployed in a network, whether for voiceor broadband, can be considered cover-age sites. The number of sites carryingheavy traffic is even lower, perhaps percent for broadband. These sites will bethe first to require upgrading to secondcarrier or higher modulation schemes toprovide better capacity. But they are usu-ally the sites that provide the shortest pay-back time.

Considering that cost per is related to

how the nodes are used, the operatorschallenge is to make use of available freecapacity rather than risk congestion.

THEIMPORTANCEOFSCALE

When subscriber numbers increase, bothtraffic and revenue rise. (see graph ) Theoperator will eventually have to invest inmore capacity, in the form of additionalcarriers, each using MHz of the spectrum. Each added carrier represents aninvestment. Because these investments aredriven by traffic from more subscribers,

there is, of course, a correlation to revenue.That makes the ability to improve cost-

Revenue Opex

-45%

Network OPEX

Core 16% Core 14%

Radio 30%Radio 30%

Backhaul54%

Backhaul31%

Non-

network

EBITDA

55%

DA

Network CAPEX

-8%

EBIT

47%

Income statement

100%

80%

60%

40%

20%

0%

Source: Ericsson Analysis; BNET Sales Development Mobile Broadband Team

5%

Network OPEX Network CAPEX

[graph 1]Profitability of mobile broadband

Assuming percent of the population has been reached four years after launch, with an ARPU of EUR usingunlimited flat rate and average traffic per subscriber of GB per month. All costs related to mobile broadbandare included in the case. The revenue bar is aggregated revenue based on subscribers times ARPU (EUR ).Non-network costs include terminal subsidies, marketing, customer care, and IS/IT. Network opex includespower consumption and support for related equipment. Capex includes any expansions or additions requiredto support HSPA depreciated over years for hardware and years for software.

efficiency important; otherwise, marginswould slowly deteriorate as users demandmore capacity and tariffs are lowered.Meeting this requirement is what the tech-nical evolution is all about. Consider agiven site configuration, starting at. Mbps and going up to Mbps using Evolution, which adds a cost ofaround percent. At the same time,capacity increase is around percent.Going to even higher speeds using dualcarriers and other features improves thesites efficiency.

Lets look at a site with a cell radius ofm using Mhz spectrum and

0,00

0,50

1,00

1,50

2,00

2,50

3,00

3,50

4,004,50

Year 1 Year 2 Year 3 Year 4 Year 5

Monthly usage per subscriber (GB)

44%

46%

48%

50%

52%

54%

56%

58%

60%

Usage per subscriber - (Normal)

EBITDA margin - (Normal)

EBIT margin - (Normal)

[graph 2]Projected 30 percent YoY growth


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(GB/month, percent busy hour). It has acapability to handle over subscribersat percent load. That cell radius equalsapproximately km and can be comparedto New York with around , peopleper km. Assuming an operator gets percent of the total population, that equals, subscribers per site.

These examples show only the cost per for a NodeB. But if we look at the entire network (reasonably well utilized,with the cost of site acquisition and buildincluded), we see that all costs, including

the radio network controller () and thecore nodes and , typically rep-resent a small part of the total cost per .The mobile backhaul and optical transmis-sion in the core cost less than . per compared to a NodeB at .per . (see graph )

REAL-LIFEBUSINESSCASES

Simple calculations dont tell the full storyof a real business, but they provide a goodindicator. Lets turn our focus to real-lifecases, based on research in cooperation

with established operators from all parts ofthe world.Ericsson has developed a tool to make a

complete end-to-end analysis, including allaspects relevant to the business case. Even

voice and traffic, though not part ofmobile broadband, should be consideredbecause they affect overall network dimen-sions. Mobile broadband must share net-work capacity with other services, espe-cially the radio bearer, and voice in partic-ular. All operators in our research have aG network covering percent oftheir respective populations.

We have noticed that operators oftenstruggle with their own calculationsbecause of difficulties in identifying orallocating costs that are strictly related to

mobile broadband.In our work to produce real business case

examples, we have proceeded as follows:Analysis is based on existing traffic pat-

terns and forecasts, creating a scenario forthe next five years. The traffic and sub-scriber growth scenario determines thecapacity required in all nodes includingradio and backhaul, and thus drives costover the five-year scenario. The caseincludes all non-network costs, such ashandset subsidies, marketing, and cus-tomer care. Although marketing costs, for

example, may be much higher initially, webelieve that within three to five years theywill stabilize at a level similar to today.Therefore, the non-network costs will bearound percent of revenue for a West-ern world operator and somewhat lower inlow- regions.

Analyzing a static network wont satisfyan operator looking for real-life answers.So we look at key areas where there arequestion marks.

What would happen, for instance, if trafficper subscriber increased dramatically? Notthe statistical average, which can increase

because a few users generate huge amountsof data, such as when using peer-to-peer;but rather a traffic increase that an operatormust consider when dimensioning the net-work. We also investigate what would hap-pen if an operator moved away from E/T(backhaul on leased lines) and used micro-wave links instead. Finally we consider whateffects that variations in subscriber uptakecould have on the business case.

The graph (see graph ) shows how anincrease of traffic per subscriber affectsprofitability, assuming all other things are

equal. We conclude that, within limits, wecan maintain strong profitability even if

CAPEX

RADIO BACKHAUL CONTROLLER TRANSPORT PACKET TOTAL

SUM

OPEX

Network costs are less than EUR 1,0 per GB

New sites including site acquisition and build

RNC/BSC

0,37 /GB

< 0,6 /Sub/Year

GGSN

SGSN

0,19 /GB

0,01 /GB

0,01 /GB

0,08 /GB

0,08 /GB


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traffic increases drastically. In the scenariosmodeled with operators, shown in thegraph, we have calculated with networkcapabilities up to Mbps, being intro-duced in some networks during . Butwe need to remember that technology isevolving very fast. When allowing the net-work to evolve all the way into a five-yearscenario and assuming speeds up to Mbps, we have the tools we need to keepup with demand and remain profitable.

The most important element of profita-bility is subscribers paying for the service.The graph shows how profitability dropsunless enough subscribers are added (see

graph ). Many operators still have a longway to go before they have enough sub-scribers to be profitable. At the same time,we do see a few operators who, after two

years, have reached a population penetra-

tion above what we use in this sensitivityanalysis. What still has an effect on the endresult for these operators is the amount ofnodes that they have built out so far. Thepopulation coverage does vary betweenoperators and the prerequisites vary bycountry. The Nordic countries for examplehave quite low population density andtherefore require more sites per inhabitantthan countries with high population density.

HANDLINGTHE THREATS

If distribution cost per is counted in

euro cents, and traffic is not an issue atmost of the sites, why do we keep hearingthat traffic will kill the networks?

The most common argument is thatheavy downloading through file sharing viapeer-to-peer applications generates hugeamounts of traffic. As a consequence, fewoperators dare adopt the de facto pricemodel on wireline broadband, namely,unlimited flat rate. Even though this flatrate promotes subscriber uptake and is theeasiest pricing for consumers to under-stand, operators still worry about uncon-trolled costs from heavy increases in traffic.

All or most mobile networks today havebeen running voice, , , and somemobile data traffic. None of these have gen-erated much traffic per subscriber. Revenuegrowth has been well aligned with trafficgrowth (and thus traffic cost) per sub-scriber. Then along came this new servicethat, compared to , for example, easilygenerates , , or even times moretraffic per subscriber. This has triggered aknee-jerk reaction among operators, whothink that such a service cant be profitable.

The three applications generating the

highest volume on the internet today arepeer-to-peer file sharing, web browsing,

Network cost per GB per month

25

20

15

10

5

0

0,25 M subs1.5xPrice

18.7

1,25 M Subs

4.3

Base case2,5 M Subs

2.5

3,75 M Subs

1.9

60%

40%

20%

0%

Profitability

Source: Ericsson Analysis

EBITDA

EBIT

OPEX

CAPEX

[graph 5]Customer uptake: The driver for profitability due to economies of scale

and video streaming. Peer-to-peer aloneaccounts for over percent of all house-hold-generated traffic. And with traffic persubscriber increasing at a yearly rate of percent, driven mainly by file sharing, weshould look at peer-to-peer for opportunity.

Operators want as many profitable sub-scribers as possible. This means thatinvestments made in the network aredriven by the bulk of subscribers and not

by a few heavy users. Ericsson addressesthis by introducing traffic-handling prior-

Data usage does not significantly impact the businesscase due to economies of scale

Network cost per GB per month

3

2

1

1GB

2.2

2GB

1.3

Base case

4GB

0.8

8GB

0.6

60%

40%

20%

0%

Profitability

Dimensioning traffic per subscriber per month

Source: Ericsson Analysis

EBITDA

EBITOPEX

CAPEX

[graph 4]Economies of scale


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business case mobile broadband

ity throughout the network, which allowsthe network itself to manage its resources.The operator must introduce a fair-useclause in the subscribers contract so it canmanage heavy usage intelligently. Mostcommonly, mobile broadband operatorsuse unconditional throttling today, whichmeans that once the fair-use level isreached, the throughput drops to a prede-termined level. Typically, though, thesespeeds dont allow for meaningful use ofthe broadband connection.

Traffic-handling priority (see graph )gives the heavy user a lower priority in thenetwork once the fair-use level is reached.The heavy user experiences a degradationof the service only when competing forresources in a congested situation. But inpeer-to-peer, the experienced reduction ofthe throughput will, over time, be limited.

Only in heavily loaded cells does a peer-to-peer user experience serious problems.Those sites would soon be targeted forcapacity upgrades since it is normal usagethat is creating the congestion.

Traffic-handling priority allows an oper-ator to focus on dimensioning the networkfor normal usage while still allowingunlimited or all you can eat traffic. Theconsumer gets better overall quality andthe comfort of using an unlimited servicethat does not generate surprises on the bill.

In the long run, unlimited flat rate with a

fair-use clause is potentially cheaper andmore profitable for the operator thanbucket plans. Subscriber uptake aside, wesee that bucket size is increasing drasti-cally, driven by competition and as a waymeans to segment the market. Its probablyfair to assume that buckets of , , or

even already on the market must befulfilled by the operators. With bucketplans, the traffic volumes for dimensioningthe network would continually increase,and the only limitation the operator has isthe bucket size. However, the fair-use levelfor an unlimited flat rate offer may notneed to change at all, or at least very little,over time since it does provide an all youcan eat model. The segmentation isinstead achieved through speed and price.

Unlimited flat rate is a complex issue,and it is difficult to predict what will actu-ally happen in a network when this modelis applied. Although the model does alloweach user to generate as much as theywant, other factors influence the outcome.The operators chosen position in the mar-ket determines which subscribers itattracts. This in turn defines the behavior

of its subscriber base. Great variationsexist between operators in the same mar-ket with similar packaging and pricing.

We have based this pricing discussionentirely on -based subscribers to provethat there is good profitability even inoffering a simple bit pipe. Introducingintelligent management functions in thenetwork allows the operator to handle allsorts of situations, such as separating appli-cation streams from each other, or varyingtraffic and perhaps pricing dependingon time of day; or giving different priority

to smartphone users over users; or giv-ing paying mobile- viewers a higher pri-ority than best effort internet. The possi-bilities are nearly endless, and it comfortsoperators to know they exist.

When we add them all together and putthem on top of the simple bit pipe, weimprove on an already powerful conceptthat will continue to generate good profitfor operators in the future.

And finally, it is nice to get the kind ofconfirmation we recently received whenone of Ericssons customers reported to usthat its current cost per for mobile

broadband is now down below , afteronly two years of operation.

AUTHOR

GREGER BLENNERUDis

Director of Business Develop-

ment at Ericsson Business

Unit Networks, responsible

for mobile broadband for op-

erators and consumers. He has over years in tele-

com with experience in software development, busi-

ness intelligence, sales, and marketing. He holds a

masters degree in Business Administration and Econ-

omy from the University of Uppsala, Sweden.([email protected])

Heavily loaded cell, filled by p2p traffic

Regular users still experience the full bandwidth Bittorrent

YouTube

Internet Radio

www.web.com

Time

Bandwidth7.2 Mbps limit

Average throughputexperienced byheavy user

Experienced throughput,all others (web, email,streaming)

[graph 6]Traffic handling priority

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209 BUSINESS CASE Mobile Broadband