Modern Telecommunication
The Very Basics
Dr. Kim Kyllesbech Larsen, TechNEconomy.
Training Material 2016.

Anonymous Art

Compounded Annual Growth Rate CAGR
• Growth
Year 2014 2015 2016 2017 CAGR
Data Volume 3.45 4.83 6.28 7.53 ~ 30%
Yr by Yr growth 50% 40% 30% 20%
Wiki
Data Volume 2017
Data Volume 2014

Profit & loss (P&L).
Wiki
Total Revenue
Technology Cost (ca. 15% – 20+%)
Usage Cost−
Market Invest SAC & SRC
−
= EBITDA (APAC ca. 45%)
Personnel Cost
Other Cost
−
−
−
Network Depreciation−
Spectrum Amortization−
Capex (new rollout  +20+% of Revenue)−
Spectrum invest (0.5 – 1.0 $ per MHz-Pop)−
+ New Revenue?
Defend philosophy!
Stop / Slow Revenue Decline
New business?
QoS, LTE, IoT, Media/TV,
FMC/FMS, …
Efficiency game
Optimize: Defend / Slow
Ebitda Decline
Increased cash pressure
New technology (Fiber,
LTE, 5G,..) & Modernize
SAC: Subscriber Acquisition Cost
SRC: Subscriber Retention Cost
EBITDA: Earnings Before
Interest, Tax, Depreciation &
Amortization
Cash
Careful! Cash
calculation involves
more than what is
depicted here!
EBITDA & Margin
(EBITDA/Revenues) Key
metrics for assessing financial
health of business
Note: From Revenue we can
calculate the ARPU (Average
Revenue per User) by Revenue
divided by the Average over
Period Users.

Mega, Giga, Tera, Peta, Exa … Bytes
Name Symbol 10n Decimal
Yotta Y 1024 1 000 000 000 000 000 000 000 000
Zetta Z 1021 1 000 000 000 000 000 000 000
Exa E 1018 1 000 000 000 000 000 000
Peta P 1015 1 000 000 000 000 000
Tera
(Trillion)
T 1012 1 000 000 000 000
Giga
(Billion)
G 109 1 000 000 000
Mega
(Million)
M 106 1 000 000
kilo k 103 1 000
Source: Cisco VNI Global IP Traffic Forecast, 2014–2019
Global IP Traffic
1992: 0.001 GB per second.
↓× 30 over 5 years
1997: 0.03 GB per second.
↓× 3,333 over 3 years
2000: 100 GB per second.
↓ CAGR +44% per year
2014: 16,000 GB per second.
↓ CAGR +46% per year
2019: 50,000 GB per second.
100 MB ~ 4 minutes Youtube at HD (720p).
700 MB ~ size of standard movie on normal DVD.
1 GB ~ 5 minutes of 4K UHD TV viewing.
10 GB or 5 hours of Youtube watching per month.
25 GB ~ 1 Blue-ray movie size.
1 TB ~ 250,000+ HD songs (~ 1+ million hours of music).
1 PB ~ 13+ years of HD-TV videos.
50 PB ~ Entire written works of Mankind from the beginning.
4.5+ Billion Years (GY)
~Age of Earth
7000 Yotta atoms
In a typical human body
~ 100 T Ants
in the world
~ Number of planets in
the Universe
Less than 50 k elephants
left in the wild
~ 50 M died as a direct
consequence of WW II
Wiki

Minutes, Bytes & bits per second.
6
• Voice Usage is well defined & understood, it is a capacity & cost driver!
• Calls measured in minutes (or Erlang).
• Network Impact per time unit of voice usage is “always” the same (i.e., fixed bandwidth or resource allocation).
• Voice Usage is well defined & understood, it is a capacity & cost driver!
• Calls measured in minutes (or Erlang).
• Network Impact per time unit of voice usage is “always” the same (i.e., fixed bandwidth or resource allocation).
Voice Minutes
• Byte B is a measure of total information consumed; ∝ ∑ ; …
, rb is the supplied network bit rate in bits per second.
• Its a volumetric unit of data consumption and similar (in principle) to a Voice Minute.
• Network impact per time unit of data usage can vary enormeously (i.e., variable bandwidth or resource allocation).
• Byte B is a measure of total information consumed; ∝ ∑ ; …
, rb is the supplied network bit rate in bits per second.
• Its a volumetric unit of data consumption and similar (in principle) to a Voice Minute.
• Network impact per time unit of data usage can vary enormeously (i.e., variable bandwidth or resource allocation).
Byte (8 bits)
MB, GB, TB, …
Note ∝ ∑ ∆ =
, rb is constant. e.g., 12.2 kbps
• bits per second is a fundamental measure of the information rate.
• For data consumption the bit rate can (and often will) vary significantly between one and another instant of time.
• Networks are planned according with the expected maximum gross demanded bit rate arising from all users.
• bits per second is a fundamental measure of the information rate.
• For data consumption the bit rate can (and often will) vary significantly between one and another instant of time.
• Networks are planned according with the expected maximum gross demanded bit rate arising from all users.
bits per second
kbps, Mbps, Gbps
Byte is NOT a capacity or cost driver!!!
Bits per second is the capacity or cost driver!!!
Wiki

7
Throughput drives network expansion & cost
…Volume (Bytes) does NOT!
TRAFFIC PROFILES
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 Hour of Day
Throughput
Mega
Bits
per second
(Mbps)
9 HOURS
4 HOURS
1
2
Traffic profile 2
same volume as 1, but
40% higher busy hour
throughput.
To keep same user
experience in the busy
hour more network
capacity needed.
Higher invest level
and network OPEX
required.
Same volumetric (Byte) demand can cause vastly different network cost
and invest levels.
Wiki

Video streaming requirements & impact.
Resolution
Width x Height
Video Rate Audio Rate
360p 0.5 – 1.0 Mbps
0.128 – 0.512
Mbps
480p (ED) 0.7 – 2.5 Mbps
720p (HD) 3.0 – 5.0 Mbps
1080p (Full HD) 4.0 – 8.0 Mbps
1440p 7.0 – 10 Mbps
2160p (4K UHD) 25 – 45 Mbps
Note: p stands for progressive scanning where all lines of each frame are drawn in sequence.
Best Video Format for Mobile: MPEG4, Best Video Codec for Mobile: H.264, Audio Codec: AAC
(Advanced Audio Codec).
Source: Sandvine Global Internet Phenomena, Asia-Pacific &
Europe, September 2015.
Busy Hour Traffic Distribution – APAC
(based on bits per second)
Example:
Radio cell sector has 1,000 users in the busy hour. Each watching 4 Minutes video stream (e.g.,
Youtube). Every 4 seconds a new video might be watched (0.25 per second).
On average over 4 minutes one would expect 60 simultaneous video streams, which at 720p would
be a BH demand of min. 180 Mbps or at 480p it would be min. 42 Mbps.
Wiki
4 min (duration) x 60 sec/min x ¼ videos/sec (arrival of new views)

Circuit-switched connections.
Circuit Switched (CS) Connections
A B
- End-2-End well defined circuit fully reserved
until user (or network) breaks connection.
- There is no changes to the circuit path
throughout a call.
- Capacity is reserved 100% throughout a call,
irrespective of activity.
- Highly reliable with less delay.
- If path is broken (due to quality or outage),
service is lost and needs to be built up again.
- It tends to be in-efficient in its use of
switching and transmission resources.
- Public Switching Telephony Networks (PSTN)
are circuit switched in nature.
- Today many PSTNs have migrated to VoIP and
(so-called) Next Generation (NG) IP switching
networks.
Communication paths
usually called circuit.
Wiki
Network resources 100% reserved when connection established.
No statistical advantage from variation in usage..
Connection establish
from A to B and kept
until user breaks it.

Packet-switched connections.
Packet Switched (PS) Connections
A B
- Uses Content (e.g., voice or data) broken up
in so-called (IP) packets & send over the
network.
- The path is changed based on quality, traffic
and priority.
- Network resources only used when user
packets send over the network.
- Can be very reliable although more delay
sensitive than circuit switched.
- Packet prioritization possible which can
provide almost same quality as a circuit
switched connections.
- PS Networks tend to be very efficient due to
the statistical nature of packet transmission.
- Most modern switching networks (e.g., LTE,
3G HSPA) are PS-based.
Wiki
Network resources used only when user uses.
Packets (of use) statistically distributed.
Packets of use can be transmitted
via many different paths
Uses broken down into
(IP) packets and send
into the PS network.
All (IP) packets re-assembled
(re-built) into a continues
stream of content.
123
1 1
1
1
2
2 2 2
3
3
3

What brings meat to your noodles?
(in Europe: we would say what brings the butter on your bread).

?
Write (maximum) 3 sentences
down describing what drives
your business.

Telecommunications in General
Tele-communications is the exchange of information
(bits) over a distance by electronic or optical means.
A complete, single telecommunications connection
consists of at least two devices, each device
equipped with a transmitter and a receiver.
Ancient Greek
means at a distance.

We are (almost) all Mobile
High GDP
APAC
Europe
North
America
APAC EMEA
Latin
America
Sources: United Nations, Department of Economic & Social Affairs, Population Division. . Mobile Penetration is based on Pyramid Research and Bank of America
Merrill Lynch Global Wireless Matrix Q1, 2014. Index Mundi is the source for the Country Age structure and data for %tage of population between 15 and 64
years of age and shown as a red dotted line which swings between 53.2% (Nigeria) to 78.2% (Singapore), with an average of 66.5% (red dashed line).
Mobile Penetration Urban Population
2013

Most urban areas have
3G Mobile Broadband
High GDP
APAC
Europe
North
America
APAC EMEA
Latin
America
Sources: United Nations, Department of Economic & Social Affairs, Population Division. . Mobile Penetration is based on Pyramid Research. Index Mundi is
the source for the Country Age structure and data for %tage of population between 15 and 64 years of age and shown as a red dotted line which swings
between 53.2% (Nigeria) to 78.2% (Singapore), with an average of 66.5% (red dashed line).
3G Penetration Urban Population Urban Area
2013

Revenue slows down, Cost grows faster
… & that’s a problem for profitability!
REVENUE GROWTH EXCEEDS
GROWTH OF OPEX
OPEX GROWTH EXCEEDS
GROWTH OF REVENUE
CAGR 2007 to 2013
High GDP
APAC
Europe North
America
APAC EMEA Latin
America
Source: Bank of America Merrill Lynch Global Wireless Matrix Q1, 2014.

18 18
Telco at a Cross-road
SMS Revenue
In decline
Voice Revenue
In decline
Data Revenue
Slow to pick up
The traditional mobile access-based
business model of Voice, SMS & Data
inevitably will decline.
Access in decline
Monetizing
the 4th Wave

Lets go back to …

The very old days …
A B
A B

History at a glance.
• 7th March 1876 Graham Bell receives patent for the telephone.
• 10th of March 1876 Graham Bell makes the “first” telephone call.
• 1876 Bell makes first long distance call (6 miles ~ 10 km).
• 1876 telephone switchboard exchange invented (Puska, Hungary).
• 1877 First commercial telephony company (Germany).
• 1878 First US commercial telephony company (New Haven, Connecticut).
• 1880 Graham Bell invented the Photo-phone transmitting voice signal over an optical beam.
• 1917 Patent for a “pocket-size folding telephone with a very thin carbon microphone” (Finland).
• 1926 First transatlantic telephone call (London, UK – New York, USA).
• 1930 First experimental videophones.
• 1930s Concept of digital switching developed in Europe and USA.
• 1936 First video phone service (Germany).
• 1941 Multi-frequency dialing introduced.
• 1946 First commercial mobile phone call.

History at a glance.
• 1960 First laser was built (USA).
• 1962 Telstar telecom satellite (TV pictures, telephone calls & fax images).
• 1965 First electronic switching system in commercial service.
• 1965 First working optical-fiber data transmission system (Borner, Germany).
• 1968 First fully digital central switch in commercial service (London).
• 1969 ARPANET (Advanced Research Projects Agency Network) Live.
• 1975 First commercial fiber communications systems developed.
• 1978 (D)WDM concept first published.
• 1980 First (D)WDM working system.
• 1990 First working worldwide web (WWW) as we know it today (Tim Berners-Lee).
• 2000 First commercial photonic crystal fibers.
• 2012 Record breaking 1.05 Peta bits per second over 52.4 km of 12-core optical fiber.

History at a glance.
• 1917 Patent for a “pocket-size folding telephone with a very thin carbon microphone” (Finland).
• 1946 First commercial mobile phone call
• 1978 First NMT (Nordic Mobile Telephone) call made (Finland).
• 1991 First GSM phone call and service (Finland).
• 1992 First SMS Message (Vodafone UK). 1993 First commercial SMS service (Telia, Sweden).
• 2000 First commercial GPRS (General Packet Radio Service on GSM) services (first mobile packet data).
• 2001 First commercial UMTS (Universal Mobile Telephony Service) by NTT DoCoMo (Japan).
• 2003 EDGE (Enhanced Data rates for GSM Evolution) in commercial service.
• 2004 GSM surpasses 1 Billion Users.
• 2006 GSM surpasses 2 Billion Users.
• 2007 HSDPA (High Speed Data Packet Access on UMTS) launches.
• 2007 iPhone 1 (June 29th) – GSM/GPRS/EDGE.
• 2008 iPhone 3G (July 11th)
• 2008 Global Mobile Connections surpass 4 Billion.
• 2009 First Commercial LTE (Long Term Evolution) Network launches (Sweden & Norway, TeliaSonera)
• 2010 iPad 1 (April 3rd)
• 2010 Global Mobile Connections surpass 5 Billion.
• 2011 First LTE Network in South Asia Sri Lanka Telecom Mobiltel (96 Mbps).
• 2014 VoLTE (Voice over LTE) in commercial service (first ~ May 2014, Hong Kong, Singapore, USA).
• 2014 LTE-advanced in commercial service (first ~ June 2014).

Important drivers to consider.

Important drivers to consider.
Gordon Moore’s (co-founder of Intel) law:
transistor count double every two years.
GPU particular important for
development of Artificial Intelligence
& Virtual/Augmented Reality Apps.
The higher the
number of
Transistors the
higher the
performance
+10Yrs
× ~ 100

Important drivers to consider.
Average
Top-50
Max
Top-50
On average over period a
factor 2 in power reduction
per year has been achieved.
Very few
Data points
Approx. factor 10
improvement per 5 years
On average 20+%
improvement per year

Important drivers to consider.
Note: after 2005 GPU outperform the CPU processing
power in terms of GFLOPS so maximum performance
should be used to calculate the initial price!
Ca. factor 6
reduction per year
In cost of computing!

Important drivers to consider.
Last 5 years cost of Flash
has reduced a factor 10+
Last 3 years cost of SSD
has reduced a factor 2.5
Last 5 (10) years cost of Memory
has reduced a factor 2.8 (50+)

Important drivers to consider.
+10Yrs
× 1,000
Improvement in
storage &
memory capacity

Access technologies development.
Caution: Above does not consider contention ratio (e.g., 1:32 or 1:64), concurrent user demand, assuming vastly different
bandwidths to get to the speed, nor does this consider that the technologies have very effective ranges at optimal speed
plotted above. So it is a bit of an apple and orange comparison!
Last 10 years
more than
× 1,000
Improvement
in user speed

Last 10 years.
The amount of computer power performance
quantum leaped new applications (not possible prior).
The cost of computing and storage has reduced dramatically
Becoming cheap and un-locking boost in software-driven innovation.
Access technologies have improved with at least factor 10 in user speed
allowing for fast low-latency access to computing and storage on the go.
What before had to be built in expensive customized hardware can now be
supported by software on cheap off the shelf hardware.

Enablers
Drivers
Transistor
Count
×1,000 over period
Computing
cost
~ 1/6 per year
Last 10 Years
Cost of
Storage
~ 1/50 over period
Storage
Capacity
×1000 over period
Cellular Access
Speed
×1000 over period
Cloudization
Virtualization
NFV
SDN
SW replacing HW
functionalities
Data
DemandSW as a Service
Storage
Higher performance for much less cost
Technology
Progress

Telecom
Today &
Tomorrow.

Global mobile subscriptions
per technology.
Ca. 7.2 Billion Subscriptions
Ca. 5.5 Billion Unique Users
75% of world population
Ca. 9.2 Billion
Ca. 5.3 Billion
Unique user has (on average)
1.3 subscriptions
38%
42%
20%
50+% from
Asia Pacific

Video content rules the internet
Global Monthly usage in Exa-Bytes (Million GB).
Note: Asia, North America & Western Europe makes up for 80% of the Total
Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI.
30+ Billion
Full Movie DVDs
4+ DVD Movies
per person per month
150 Billion
Full Movie DVDs
20+ DVD Movies
per person per month
Mobile Ca. 20% of Total
IP Traffic
CDN 45+% of Total
IP Traffic
60+% of Total
IP Traffic in Metro
Exa-Bytes
Video-only traffic considered

APAC towards 2020 – Total IP Trafic.
Ca. 50+% of World Population lives here!
40% of Global IP Traffic
55% of Total* is Metro-based
60% Consumer IP Video Traffic
40% of Total is CDN-based
2020 APAC Projections:
Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI.
Source: Pyramid Research 2013 – 2017; 2018 to 2020 is authors own projection.
15+% of Pop have fixed broadband
15% still on 2G
Up-to 20% likely to have LTE
*Total always refers to the Total IP Traffic.
Fixed Broadband Penetration
30% of total IP traffic from mobile.
Exa-Bytes

MEA towards 2020 – Video Traffic only.
Ca. 1 in 5 of World Population lives here!
4% of Global IP Traffic
17% of Total* is Metro-based
Exa-Bytes
74% Consumer IP Video Traffic
14% of Total is CDN-based
2020 MEA Projections:
Source: Cisco VNI 2013 – 2018; 2019 & 2020 is authors projection based on VNI.
Source: Pyramid Research 2013 – 2017; 2018 to 2020 is authors own projection.
5+% of Pop have fixed broadband
40% still on 2G
4+% likely to have LTE
*Total always refers to the Total IP Traffic.
Fixed Broadband Penetration
30% of total IP traffic from mobile.

Fundamentals of traffic growth.
Interest
- Growth of customers.
- Growth of traffic (per customer & total).
- Growth of revenue.
- Growth of profitability.
Technology
Adaptation
#Users
Usage
Adaptation
Usage per User
?
LIMITED?
×
Exponential?
S-curve-like?

Growth – technology adaptation.
Technology
adaptation
#Users
(is an IoT a user?)
LIMITED?
(maybe)
Population
Availability
Economics
2014: ca. 40% of APAC1
on 3G or better
2020: 70+% of APAC1
1 Pyramid Research APAC.
Subscriptions
APAC 2014
~ 1 sub per pop.
By 2020
~ 1.2 sub per pop.
What about
Internet of Things (IoT)?
1 Million IoT per km2
The 15 – 64 years

Growth – usage adaptation.
Cellular Usage
Adaptation
Usage per User
?
LIMITED?
(maybe)
Pricing
Use Cases
Technology
Convenience
Spectral capacity
Network Speed
Device performance
Transport infrastructure
20 hrs. per week TV viewing
@ 1Mbps unicast stream
20 GB per Month per user
2014: ~400 MB Cellular!
per Month per User in APAC
2020: ~5 GB Cellular!
Note: CELLULAR TV
Cloud
Cellular off-load

Global mobile revenue structure.
Total Revenue 2014
was ca. 1.0 Trillion US$
Total Revenue 2020
Expected to be ca. 1.4 Trillion US$
+4.5% pa (CAGR)
Note: SMS revenues are blended into the data revenues.
Note! Data + Voice Revenues

Global mobile revenue structure.
(an optimistic view)
ARPU Turn around
Note: SMS revenues are blended into the data revenues. This will in general pull down the pure mobile broadband data revenues.
<2 % of expected global
GDP per capita
<2 % of expected global
GDP per capita
Abbreviated as ARPU

Asia expectations.
+5.5% pa
~ 1.5 % of expected
Asia GDP per capita
~ 1.0 % of expected
Asia per capita
Mobile Asia by 2020:
• Ca. 5.0 B subscriptions.
• Ca. 3.7 B unique users.
• LTE ca. 20%
• 3G ca. 40%
• 2G ca. 40%
• ARPUU ca. 9 US$ / month
• ARPU ca. 5.8 US$ / month
• Total Revenue 0.5+ Trillion US$
• 50+% from data.
Total Revenue 2014
was ca. 0.4 Trillion US$
Total Revenue 2020
Expected to be ca. 0.5 Trillion US$
ARPUU – Average Revenue
per Unique User

44
Customer Economics to Consider.
0 – 25%
25%– 80%
Beyond 80%
ARPU Decline
Customer Growth Slows
Increasing Customer Acquisition Cost
Revenue stagnation &
decline
Profitability Pressure
Attractive
urban areas
All urban &
Sub-urban
areas
Rural Areas
Note: “Crossing the Chasm” is attributed to Geoffrey Moore from his book “Crossing the Chasm: Marketing and Selling High-Tech Products to Mainstream Customers”.

45
Time
USERS
ARPU
SERVICE REVENUES
Time
SMS REVENUE
VOICE REVENUE
DATA REVENUE
TOTAL REVENUE
DIGITZED REVENUES
(The 4th Wave*)
?
* The 4th Wave is attributed to CHETAN SHARMA, MobileFutureForward.
The very basics …
Mistakes & Mess
deadly for profitability!
Mistakes, Incompetence &
Mess don’t really matter!

Old world communication…
When 1 + 1 was 2
... Bla …
Bla bla bla
Mobile Network
We talked (a lot)
We SMS’ed (even more)
Rarely did we use the (mobile) web.

A new usage paradigm …
1 + 1 is no longer “just” 2
1
User
Multiple
Device
User & application initiated bandwidth demand.
Device & application (IP address, keep alive, …) driven signaling resources.
Many applications

48
What we strive for!

Changing business model.

50
MOBILE
CONVINIENCE
HOMEDigitized!
RETAIL
Content
SECURITY
DEFENCE
HEALTH
SURVAILANCE
SMART GRID
DATA MINING
TOURISM
PROFESIONAL
SERVICES
TRANSPORT
BIONICS
QoE
ENVIRONMENT

“Todays” Access
Telco Environment
The New
Telco Environment
The new competitive climate.
Enabled by Technology.

52
Mobile
1,400+
Billion US$
(55% Data)
Global Digitized Economy 2020
Fixed
440+
Billion US$
(60% BB)
Mobile Banking
400+
Billion US$
Public Cloud
370+
Billion US$
Mobile Health
60+
Billion US$
M2M
140+
Billion US$
Mobile App
30+
Billion US$
Mobile Digital Advertising
170+ Billion US$
(70+% of Total)
Smartphones
250+ Billion US$
Mobile Content
8+ Billion US$
Managed Cloud Services
4+ Billion US$
Sources: http://www.statista.com/ premium account. Typically
up-to 2020 has been projected based on available data. This
applies to the following page as well.

53
Mobile
1,400+
Billion US$
(55% Data)
Global Digitized Economy 2020
Fixed
440+
Billion US$
(60% BB)
Mobile Banking
400+
Billion US$
Public Cloud
370+
Billion US$
Mobile Health
60+
Billion US$
M2M
140+
Billion US$
Mobile App
30+
Billion US$
Mobile Digital Advertising
170+ Billion US$
(70+% of Total)
Smartphones
250+ Billion US$
Mobile Content
8+ Billion US$
Another
Trillion Dollar+
Economy
in the most obvious
Digital Services
On top of Mobile.
Managed Cloud Services
4+ Billion US$
Sources: http://www.statista.com/ premium account. Typically
up-to 2020 has been projected based on available data. This
applies to the following page as well.

54
Mobile
1,400+
Billion US$
(55% Data)
Global Digitized Economy 2020
Fixed
440+
Billion US$
(60% BB)
Mobile Banking
400+
Billion US$
Public Cloud
370+
Billion US$
Mobile Health
60+
Billion US$
M2M
140+
Billion US$
Mobile App
30+
Billion US$
Mobile Digital Advertising
170+ Billion US$
(70+% of Total)
Smartphones
250+ Billion US$
Mobile Content
8+ Billion US$
Another
Trillion Dollar+
Economy
in the most obvious
Mobile Digital
Services Entertainment &
Media
2,500+
Billion US$
Travel & Tourism
9,800+
Billion US$
(<10% Online)
Internet of Things
7,000+
Billion US$
Residential Financial
Transaction Volume
5,000+
Billion US$
(50+% Online Penetration)
Note: 2013 had Globaly
ca. 30% Internet Users
Healthcare
11,000+
Billion US$Medicine
1,400+
Billion US$

Spend 3 minutes
writing down 3 bullet points
of what makes
mobile & wireless
technologies attractive?

Pricing

Writing down 3
treasured items
you would give up
for 1 year of internet access.

Value of internet1
What would you give up a year for internet access.
80 80
75 74
68
48
30
27
22
1 Source: The Boston Consulting Group Report on “The Internet Economy in the G-20”, March 2012.

Value of internet1
Need, Love and then taken for granted?
Perceived Value of Internet
(relative to GDP per Capita)
1 Source: Analysis based on The Boston Consulting Group Report on “The Internet Economy in the G-20”, March 2012.
0%
10%
20%
30%
40%
0% 25% 50% 75% 100%
Perceived Value of Internet
(relative to GDP per Capita)
Price of Internet
(relative to GDP per Capita)
0%
10%
20%
30%
40%
0% 2% 4% 6%
Internet penetration < 50%
Internet penetration > 50%
Japen & South-Korea
Taken for granted
Internet Penetration
The perceived value of internet drops as internet becomes a commodity
!

Normal price setting in mobile industry.
1 Most price levels are not
designed in isolation from
competition, In fact often
competition is the main
“inspiration” for pricing.
2 Quality could be speed but is
not exclusively so.
Price ( Volume ( Quality, Product, Time ) , Cost, Competition1, Regulation)
Volume
(eg Allowance
vs Unlimited)
Time
Possible
FUP based
feedback
COST
mainly driven by Quality & Product
Quality2
(eg speed,
latency, …)
Products
(eg Bundles)
Illustration
e.g., Interconnect tariffs,
roaming tariffs,
MTR (for voice), …

Dimensioning of pricing
+
Volume Time
ProductQuality
Mobile Data pricing policies
focus on Volume
Fixed Data pricing policies
focus on Speed
sometimes combined
with Volume limits.
Most WiFi pricing policies
focus on Time or
bundled with
mobile data plans
 Mobile bundled products
mainly Voice, SMS, and
Data.
 Fixed bundles with Media,
Broadband Data, Voice &
mobile access (if
available).Illustration

Changing the game!
New philosophies … new dimensions.
Volume
Time
Quality1
Product
Reduce
Cost of
Providing data
Differentiate on Quality.
Speed.
Latency.
Coverage.
Time.
Customer care & support, etc..
Always-Best-Connected
Leverage Fixed and Mobile.
Small Cell deployments.
WiFi / Femto-cell off-load, etc..
Product value add-on
VoIP.
Msg & notifications.
Internet Access.
Social media.
Mobile media player.
Handset, etc.. Illustration
1 Quality could be speed but is not exclusively so.

Pricing fundamental.
Cost
Minimum
Profit
Price
Range
Price Floor
Price Ceiling
Strategic price
Price
Quantity
Subject to Cost
Revenues
=
Price
×
Quantity
Price
leakage
Missing
volumes
Maximize Revenues
Illustration

Pricing fundamental.
Value
to
Customer
Benefits
Cost Profit
Price
Price – Cost = Profit
Benefits = Value / Price
Total
Value
Added
Cost
is a Function
of the Benefits
Price
Ceiling
Price
Floor
Value
Extracted
Value
Ceded
Illustration

Classical cellular pricing.
The old world thinking.
Myanmar Mobile Data Pricing:
Old school data pricing philosophy where data usage comes on-top of
what basic services (e.g., Voice & SMS) a customer has chosen.
Telenor most sophisticated with quality differentiated price depending
on speed range (i.e., up-to 500 kbps and up-to 2 Mbps). Neither MPT
or Ooredoo have quality differentiated pricing.
MPT appears to copy Telenor though does have a high cap data plan
(6.5GB) for 25 US$ (ca. 3.85 US$ per GB).
Telenor has the cheapest data prices at 3.7 US$ per GB if customer is
happy with up-to 500 kbps.
Group Study
Most expensive!
Highest Data Capacity per Customer
But Not the best in Quality class
US$ per GB

Pricing, quality & performance
Group Study
DL Speed UL Speed Ping DL Speed UL Speed Ping DL Speed UL Speed Ping DL Speed UL Speed Ping
ms ms ms ms
Telenor 2.20 1.07 222 2.81 1.35 179 1.41 0.99 142 3.57 1.22 144
Ooredoo 1.97 0.96 203 2.03 0.97 171 2.05 0.72 248 NA NA NA
MPT 1.53 0.71 249 1.82 0.97 189 2.62 0.46 266 1.71 1.06 175
MECTel 0.22 0.27 577 0.20 0.29 587 0.39 0.28 441 NA NA NA
Source: http://opensignal.com/coverage-maps/ for Yangon, Mandalay, Naypyitaw, etc..
Naypyitaw Average
MbpsMbps
Myanmar Average Yangon Average
Mbps
Mandalay Average
Mbps
Date: March 2016
Millions Telenor Myanmar Ooredoo Myanmar MPT Myanmar
US$ 2014 2015 2016 2014 2015 2016 2014 2015 2016
Customers 3.4 13.7 18 - 25 2.2 5.8 6.4 - 7.4 11.0 18.0 18 - 20
Employees 367 500 < 750 949 >1000 < 1000
ARPU 5.4 5.6 5.2 - 5.8 7.5 6.1 5.5 - 6.0
Revenue 39 615 1,200 - 1,600 52 292 450 - 500
Ebitda -68 244 550 - 900 -98 -21 0 - 50
Margin -1.8 40% 45% - 55% -1.9 -7% 0% - 10%
Opex 107 371 650 - 700 150 313 < 450
Capex 573 430 < 350 300 326 < 250
Capex / Revenue 15 70% 25% 6 112% 50%
Ebitda - Capex -641 -186 200 - 550 -398 -347 < -200
Sites 1,500 4,200 7,000 1,200 3,450 5,000
Data Users 52% 60% 80% 80% 80%
Market Share 20% 37% 42% - 48% 13% 15% 14% - 15% 66% 48% 38% - 44%
Source: https://www.telenor.com/about-us/global-presence/myanmar/ & http://ooredoo.com/uploads/misc/Ooredoo_at_a_Glance_Q4_2015_v2.pdf
Authors own prediction
1. Identify the operator who has the best quality in the below table
2. Go to http://opensignal.com/coverage-maps/ type Yangon into search block and on NetworkRank choose Advanced view and toggle
between Telenor, Ooredoo and MPT coverage. How big a %tage difference is there between Download speeds for No. 1, 2 and 3.
3. Who appears to have the best coverage in Yangon? Move to Mandalay or another region and repeat exercise.
The Table below provides an overview of financial results of Telenor and Ooredoo.
4. Compare Telenor &
Ooredoo performance
and identify the
strongest operator.
Explain why?
5. How many customers
would the weaker
operator need to arrive
at the same revenue of
the strongest?
ARPU = Average Revenue Per User
and comprises a blended figure
considering all services.

Data-centric price plans (1 of 2).
The Un-carrier price plan:
• Choose between 2, 6, 10 GB & Unlimited 4G Data plan.
You get beside your chosen data plan:
- 1 Phone.
- Unlimited Voice.
- Unlimited SMS.
- Unlimited data but at reduced speed beyond limit.
- Binge On: unlimited video on most popular streaming
services (Netflix, HBO, Hulu, etc..) … capped at 480p.
- Music Freedom: unlimited music streaming.
- Data Stash: rolls up-to 20 GB of unused 4G data forward.
- No recurring service contract.
$50/mo $80/mo $95/mo
One-off Price = $US 0
Monthly Price = P X GB
+ US$ 42.5 (fixed monthly fee)
Fixed monthly fee of US$ 42.5 covers all
the above beside the data plan.
Note: Unlimited ~ 14 GB @ 3.75 US$/GB
Unlimited average
consumption
US$ 42.5 takes care of all stuff not
covered by the variable 4G data pricing
Group Study

Data-centric price-plans (2 of 2).
handset_price
+ Customer Management Recurring Fee
+ PSMS (sms)
+ Pvoice(minutes)
+ Proaming_insurance(r.data, r.minutes, r.sms, r.geography)
+ Phandset_recovery_fee(terminal type)
Pvolume = 0.86 US$/GB × DataLimit < ∞
Pvolume < Punlimited = P∞ (i.e., unit price → 0)
Pspeed = 0 (in this example).
Source: http://techneconomyblog.com/2015/02/03/mobile-data-centric-price-plans-an-illustration-of-the-de-composed/
Illustration:
£ 26 or US$ 37.5
(for normal handsets)
= 0.86 US$/GB × DataLimit
Group Study

Target cost & design to cost.
Illustration
Revenue = $5.0 per Giga Byte (GB) unit sold (Marketing Wish)
Margin > 30% → Earn >$1.5 per $5.0
Target Cost < (1 – 30%) × $5.0 = $3.5 per GB (maximum)
The CFO View
Technology view:
Once off site investment $168,000 written of over 7 years ~ $2,000 per month.
Spectrum $500 per month per site
Site Lease $300 per month per site
Energy (+fuel) $500 per month per site
Transmission $200 per month per site
Operations $500 per month per site
Tech Cost per Site $4,000 per month → ~ $12,000 per month including all corporate cost.
3 sectors each of 2×10 MHz servicing with 3G
→ Capacity: 10 h traffic × 3600 s/h × 10 MHz × 1.4 Mbps/MHz/sector × 3 sectors × 1/8 Byte/bit
→ Capacity: 189,000 Mega-Byte per Day or ~ 4,000 GB per month
Bottom-up we get that minimum cost per GB is $3.0 per GB (i.e., $12,000/4,000 GB).
Group Study

Spectrum
Frequency in Hz
Carrier
Frequency
Channel
Bandwidth

72
The 3G traffic jam!
 3G capacity and quality crunch.
 Slow down migration from 2G3G,
migrate to LTE instead.
 New spectrum demand.
 Re-farming existing 900/1800 MHz
spectrum if possible (in time).
Empty 2G roads - in time?
 5 MHz in 3G will only take up ca. 1 MHz in
LTE.
 LTE mitigates the 3G capacity crunch.
 Re-farmed 2G spectrum too late for
mi ga ng the 3G capacity crunch →
migration to LTE a better option.

73
Spectrum management essential.
 Lots of Hz per customer … high speed!
 Alternative to fixed (xDSL) broadband.
 Higher speed than 3G/HSPA+.
Happy startup … plenty of quality.
 Geometrical growth in demand.
 Start-up quality difficult to maintain.
 Hz per customer drops dramatically.
 Demand for (much) more spectrum
 And many more capacity sites.
Tougher future … growth limitations.

Frequency spectrum – basics (1 of 3).
Frequency in Hz
Illustration (idealized)
Carrier Frequency
Fc
Channel
Bandwidth
B
Bandwidth Examples:
GSM 200 kHz
UMTS 5 MHz
LTE 1.25 – 20 MHz
With Bandwidth aggregation
(i.e., adding up bands)
substantially larger effective
bandwidth can be achieved.
Carrier Frequency examples:
GSM 900 MHz, 1800 MHz
UMTS 2100 MHz (900 MHz)
LTE 700MHz, 900 MHz, 1800 MHz, etc..

Road analogy of frequency & bandwidth.
Channel
Bandwidth
Width
of the Road~ The wider the road the more cars
can I support simultaneously
BChannel = WRoad
Coverage Length of
Carrier Frequency
L  1 / Fc
~
Length of the road
with a given Width
How long a distance
can I support a given
traffic volume of cars
How long a range can I
support a given traffic
demand of data
The wider the channel bandwidth
the more data traffic can I support

Frequency spectrum – basics (2 of 3).
Paired spectrum.
Frequency in Hz
Frequency Division Duplex (FDD) - Illustration (idealized)
Carrier Frequency
FUplink
Channel
Bandwidth
BUL
Carrier Frequency
FDownlink
Channel
Bandwidth
BDL (can be > BUL)
Duplex
Separation
Channel
Spacing
or
Amplitude
Uplink:
from User to Network
Downlink:
from Network to User

Uplink
Out of City
Downlink
Into of City
Road analogy of FDD.
Frequency division duplex.

Frequency spectrum – basics (3 of 3).
Un-paired spectrum.
Frequency in Hz
Time Division Duplex (TDD) - Illustration (idealized)
Carrier Frequency
FTDD
Channel
Bandwidth
BTDD
Guard period
Downlink
Uplink
Time
From User to Network
From Network to User
 Whether to use TDD or FDD depends primarily on spectrum availability.
 Both paired (FDD) & un-paired (TDD) technologies have benefits & disadvantages.

Downlink
Into of City
Road analogy of TDD.
Time division duplex.
Uplink
Out of City
360
seconds
120
seconds
Same road for
Inbound (DL)
as well as
Outbound (UL)
traffic

29-15 MHz @ 900
25-35 MHz @ 1,800
Typical 210 MHz – 215 MHz
For in-country merged operators can be 220 MHz - 225 MHz
Cellular frequency spectrum overview.
1 HSPA= HSDPA + HSUPA, 2 Including 10MHz for E-GSM, 3 Values of Spectral Efficiency tends to change a lot depending on antenna
technology and actual field data, 4 Typical value.
GSM / GPRS / EDGE UMTS R99 HSDPA
(Improved DL)
HSPA1
(Improved DL & UL)
LTE
0.032 – 0.128 0.064 – 0.384 0.384 - 4
2.5 (Avg.) to
14.4peak
30 (Avg.) to
170peak+
(450, 850,) 900,
1,800, (1,900) MHz
(AWS: 700, 1,400, 1,700,) 2,100 MHz,
2,600 MHz UMTS extension band (though also LTE candidate)
All Freq. UHF band &
700 – 2,600 MHz.
Min. 220 MHz
(target)
2352 MHz @ 900
2x75 MHz @ 1,800
260 MHz @ 2,100 and 270 MHz @ 2,600
AWS: 245 MHz @ 1,700
2n20 MHz
(n=1,2,3…)
Downlink Throughput (Mbps)
0.11 – 0.454 0.51 0.80 1.44 1.5 to 10
Downlink Spectrum Efficiency3 (Mbps per MHz)
Dominated by legacy infrastructure suppliers: Nokia Networks, Ericsson, Huawei, ZTE.
Note: FDD: Frequency Division Duplex Cellular Systems (i.e., operates in two separate frequency
bands; 1 for Downlink & 1 for Uplink).
Illustration only.

Coverage fundamentals
Frequency & length of traveling wave.
E.g., A male voice* reaches up-to double the distance of a female voice*
purely based on its lower frequency range (all else being equal).
(*) Male voice frequency 85 – 180 Hz vs Female voice frequency 165 – 255 Hz.
The effective reach
of a given wireless technology
is inverse related to
the carrier frequency.
E.g., lower frequencies cover
more length (& area) than high
frequencies.
The loss of signal power
over a given distance
is inverse related to the
square of the carrier frequency.

Spectrum benchmarking – coverage.
900 MHz
DL power
Coverage area
UL power (typical limitation for coverage)
Illustration
×9 ×6 ×4.5 ×1
900 MHz – 800 MHz (digital dividend)
2.6
GHZ
2.6 GHz
Available bandwidth for LTE
LargeVery small
LowHigh
190 MHz
2.1 GHz 1.8 GHz
2×60 MHz 2×75 MHz 2×35 MHz 2×30 MHz

Quiz
1. What carrier frequencies are the most valuable for coverage?
a) Low frequencies (<2100 MHz).
b) High frequencies (>1800 MHz).
c) Carrier Frequency itself is not valuable, bandwidth is the valuable property.
2. Which statements below are correct? (could be more than one!)
a) FDD divides the frequency spectrum up in individual codes.
b) FDD stands for Forestry Defence Department.
c) FDD divides a frequency spectrum into two bandwidth parts, with a frequency
separation between uplink use and downlink use.
d) TDD stands for Time Division Duplex.
e) In China TDD is the most popular implementation of LTE.
f) FDD is better than TDD.

Frequency link budget.
Transmit Tx
(path) Loss L ≤ 1
g × Tx
Receive Rx = L × g × Tx
Gain g ≥ 1
Convention:
in dB whereLink Budget

Spectrum efficiency.
How many bits per second can I transport per Hz of bandwidth.
Frequency in Hz
Illustration (idealized)
Channel
Bandwidth
B in Hz
Spectrum Efficiency =
Information rate (bits per
second) that can be support
by a given technology and
available bandwidth in Hz
In general, the higher spectral efficiency the better technology!

Road analogy of spectral efficiency.
Width
of the Road
WRoad
5 cars per second
Per
Width of Road
Old Road
10 cars per second
Per
Width of Road
Safe
distance
Width
of the Road
WRoad
New Road Next Generation Road
21 cars per second
Per
Width of Road
Width
of the Road
WRoad
Technology
Improvement
Technology
Improvement

Capacity fundamentals.
Unit Capacity = Bandwidth in MHz × Spectral Efficiency (in
Mbps
MHz − capacity unit
)
Dimension of Unit Capacity is Mbps/capacity-unit
B
Available BW in MHz per unit Spectral Efficiency in Mbps/MHz/ unit
N
Number of units

T-Mobile UK
& Orange TD-TV
Examples of frequencies & bandwidth.
TDD & FDD.
UL
(75 MHz)
DLUL
(35MHz)
DL
UL
(70 MHz)
TDD
(50 MHz)
DL
900 MHz 1,800 MHz
2,500 MHz
UL
(60 MHz)
DL
2,100 MHz
TDD part TDD
2,300 – 2,400+ MHz
part TDD / part FDD
This band provides interesting backhaul P2P options in some
Greenfield scenarios
3,400 – 3,800+ MHz
China: SD-CDMA alloc.
UL DL
400 MHz
DL UL
700 MHz
TDD
T
D
D
(20 MHz) (15 MHz)
(20 MHz)
Airway in China
TDD
BSNL in India

City coverage benchmarking.
For dense cities beside coverage being relative insensitive to frequency the effective cell range
decreases with increasing population density..
NYC
Den Haag
Houston
Leeds
LA
Chicago
Berlin
Hamburg
London
N
2
33
A
r 
A: Covered (hexagonal) Area
N: Number of cell sites
Houston
1
1 TMUS GSM spectrum at 1,900 MHz, and their 3G in the AWS1700 band.
0.20
0.40
0.60
0.80
1.00
0 2,000 4,000 6,000 8,000 10,000
City Pop Density (pop/km2)
GSM900
GSM1800
UMTS2100
Effective Cell Radius in km (City Coverage Characteristics)

Coverage (1 of 2)
Low-frequencies (<1,800 MHz) provides excellent coverage options while higher
frequencies with more available bandwidth gives higher speed performance.
Typical Cell Range (km)
0.01
1
10
100
1,000
LTE450
HSPA 2100
UMTS 2100
GSM900
GSM1800
GPRS
EDGE
LTE 2100
LTE 2600
Femto-cells/3.6GHz
WiFi
Note: Illustrational purpose only real cell sites can vary greatly as well as can the actual performance
Voice
10 km
0.1
Economical very attractive for sub-urban
to rural & deep indoor coverage
Economical attractive for urban
areas & capacity demand
indoor
Site throughput in Mbps vs cell range in km

Coverage (2 of 2)
Frequency and bandwidth determines the technical as well as economical
performance of a given access technology.
Typical Site Range (km)
Voice
0.1
1
10
100
1,000
High
Frequency Low
Frequency
High
Bandwidth
Low
Bandwidth
Below
900 MHz
Above
1,800 MHz
Below
10 MHz
Above
20 MHz
Site Throughput in Mbps (equivalent user capacity)

Capacity fundamentals.
CAPACITY Ci = BANDWIDTH Bi
MHz
× EFFICIENCY ηi
Mbps per MHz per Cell
× CELLS Ni
#
Business as Usual New spectrum New technologies New macro
×
Innovation Re-farming Improvements Small-cells
×
Radical Spectrum sharing Spectrum sharing Site sharing
Note: Sub−script i referes to a relevant cellular clutter area; thus the Total Capacity Ci
( )
= Bi×Ei×Ni
i(Areas)
VERY COSTLY
(VERY) COSTLY
EFFICIENT
(VERY) COSTLY
COMPLEX + EFFICIENT
COMPLEX BUT EFFICIENT, QoE CHALLENGE
BaU (COSTLY)
BaU (COSTLY)
B
× $ / MHz-pop
(e.g., 1 – 2 $/MHz-pop)
η
Modernization
Terminal subsidies
N
Cell splits / overlay
New Sites
Within technology up-to 20% gain
upto ceiling.
Between technologies x2-3 gain
Can be a signifiant capacity multiplier
and result in new site avoidance.
In urban areas can be
difficult to achieve
more density (new
sites).

93
ConnectivitySpectrum is the growth engine.
CAPACITY Ci = BANDWIDTH Bi
MHz
× EFFICIENCY Ei
Mbps per MHz per Cell
× CELLS Ni
#
GSM
Ctot ≈ 40k
n x 0.2 MHz (TRX)
(n: 6 – 15)
~ 0.52 (GSM)
0.14 – 0.33 (EDGE)
80k – 100k
(Utilization ≈ 50+%)
Frequencies
Total Bandwidth
900 & 1800 MHz
Ca. 110 MHz
UMTS
Ctot ≈ 600k (×15 GSM)
n x 5 MHz (carrier)
(n: 2 – 4)
0.5 – 1.2 (average)
up-to 17 (peak)
80k -100k
(Utilization* ≈ 70+%)
Frequencies
Total Bandwidth
2100 (900) MHz
60 (95) MHz
LTE
Ctot ≈ 4,500k (×8 UMTS)
n x 5 MHz (carrier)
(n: 6 – 10+)
1.5 – 2.0 (average)
Up-to 30 (peak)
80k – 100k
(Utilization* ≈ 90+%)
Frequencies
Total Bandwidth
700 -900MHz, 1.8GHz, 2.5GHz
210+ MHz
Note: Above only FDD spectrum is considered. Bandwidth are represented by DL part (i.e., total BW = 2x(DL or UL for symmetric bands).
(*) pending on terminal type and application a single customer can in theory cause the a given cell to be highly utilized in terms of bandwidth resources.
LTE is supported over a very wide frequency range
from 450 MHz up to 3.6 GHz

Spectrum is a very valuable asset.
UK 2.1GHz ca. 35 Bn US$
NL 2.1GHz ca. 2 Bn US$
DE 2.1GHz ca. 38 Bn US$
IN 2.3GHz ca. 5.5 Bn US$
US 700 MHz ca. 20 Bn US$
Telenor paid $500M
for 2×5 + 2×10 MHz
Blended average of
$0.31/MHz/pop

UMTS Euphoria 2000.
- In March 2000 Mobile industry paid ca. 35 Billion
US$ for 3G spectrum (record).
- Almost $5 per MHz per pop.
- ×3 the total UK mobile revenue in 2000.
- ×8 the total UK mobile Ebitda in 2000 (estimate).
- On-top they would need to invest at least 20
Billion US$ in 3G network infrastructure.
- They would need minimum 8 – 10 Billion US$ FCF
per year (over 10 years) to reach an NPV 0.
- ×12 the total UK mobile FCF in 2000 (estimate).
- At least 15+ years to breakeven on cash.
- The internal business cases (at the time) would
have had to be very optimistic to finance what
was paid for the spectrum.
- Value should have far exceed the 35 Billion
US$ paid for spectrum including
deployment investments.
- In July 2000 Mobile industry paid ca. 2.0 Billion US$
for 3G spectrum.
- Ca. $2 per MHz per pop.
- Approx. the total NL mobile revenue in 2000.
- ×2.5 the total NL mobile Ebitda in 2000 (estimate).
- On-top they would need to invest at least 1.5 Billion
US$ in 3G network infrastructure.
- They would need minimum 0.5 Billion US$ FCF per
year (over 10 years) to reach an NPV 0.
- Approx. the total NL mobile FCF in 2000 (estimate).
- The internal business cases (at the time) was
optimistic but not as aggressive as in UK.
- Value should have far exceed the 2 Billion
US$ paid for spectrum including deployment
investments.
Telenor paid $500M
for 2×5 + 2×10 MHz
$0.31/MHz/pop (1/6 NL)
GDP per Capita is 30× lower

Quiz
1. A Technology using 900 MHz covers an area
a) Worse than for a frequency of 1800 MHz?
b) Better than for a frequency of 1800 MHz?
c) Too little information to answer question?
2. Which of the following set of parameters are important for providing cellular network
capacity?
a) Frequency, Number of rainy days, Number of Sites.
b) Number of Sites, Bandwidth and Number of Customers.
c) Number of Sites, Number of bits per second per Hz available from deployed technology and
Available Spectral Bandwidth.
3. My LTE customers demand 100 Giga bit per second (Gbps) in downlink. I
have 2 x 10 MHz available for LTE with an effective  of 2 bps/Hz/unit. How
many units do I need to support the demand?
a) 500 capacity units.
b) 250 capacity units.
c) 5,000 capacity units.

Facebook Drone Coverage
The Basic Economics
“The Drone Coverage Network is an exponential technology in the sense that it has the ability to
Disrupt existing terrestrial-based cellular coverage networks
by a factor of 10 or more on TCO and deployment-time.”
“Facebook’s ambition is to built 10,000 Acquila drones which could more than easily
cover all land based surface area.”

Coverage solutions.
Caution: drawing is not to scale!
Nano-satellite
FB Aquila Drone
Terrestrial
Cellular Tower
30 – 70 meter
10 – 50 km
< 2000 km
DataQuality
Cell Center
Drone Coverage
Terrestrial
Coverage
Distance from center
Practically
10 km range FB estimate ~ 80 km
Note: FB Aquila envision Laser
connectivity to house holds (beyond
fiber connectivity) although
mentioned but not described
wireless coverage as well.
=
GEO ~36,000
km
10 Gbps
Laser beam

Facebook Drone Coverage Network vs
standard MNO Cellular Network Coverage.
Drone Network Coverage is
10× more Capex Efficient.
10× more Opex Efficient.
Typically more than 10× faster deployment.
Highly scalable capacity provision & options.
Support all frequency ranges up-to mm-wave; thus also
standard cellular/wireless frequencies 700 MHz to 5 GHz.

Facebook Drone Coverage – Aquila.
Drone /
Unmanned Arial Vehicle (UAV)
10 – 50 km
Stratosphere
Wingspan 42m
<450kg
Up-to 80 km
< 20 thousand km2
• Envisioned as a constellation of 3 drones circling in
the stratosphere providing covered to an area of up
to 20 thousand km2.
• Up-time up-to 3 month (solar powered).
• Laser backhaul with 10 Gbps connectivity.
• Myanmar Example:
• Myanmar surface area is 676,578 km2 and we would thus
require ca. 30 Facebook drone constellations (i.e., 3
drones).
• Providing max WiFi speeds across coverage area.
• Cellular network providing up-to 80% geographical
coverage may require up-to 10,000 cellular sites, between
1.5 to 2.0 Billion US$ in Capex and easily several hundred
millions of US$ in annual Opex.
• Providing max speed in vicinity of tower and
increasing poor quality out to cell edge with 128 kbps
- 256kbps.
Unlicensed WiFi
or Cellular Freqs.*
10 Gbps
Laser backhaul
(*) Should Facebook acquire cellular frequencies or cm/mm-wave
frequencies this would likewise be straightforward to deploy via a
Drone-based coverage network.
Wiki Note: global pop per HH is ~3.5, world surface area 510 Million km2
of which ca. 150 million km2 is land area of which ca. 75 million km2 is
habitable. 3% is an upper limit estimate of earth surface area covered by
urban development, i.e., 15.3 Million km2.
Note: FB Aquila environs Laser connectivity to house holds
although mentioned but not described wireless coverage as
well.

1
0
2
102
Towards Next-Generation Telco Technologies
and Business Models.
Converged Access Internet of Things
Internet of Industries
Connected Vehicles
Converged Apps Vehicular Autonomy
E2E Latency < 1 ms
Very High Redundancy.
Medium BW requirements
E2E Latency ~ 1 - 50 ms
Very high availability
Elastic BW requirements
E2E Latency ~ 50+ ms
Privacy & Security protection
Extreme elastic BW requirements
Ultra-high Availability
Very high security required
Elastic E2E Latency requirements
FTTx + LTE  5G
Ultra-Efficiency requirements
Cloud & Virtualization
Seamlessness across all platforms
e.g., Fixed, Mobile & other screens
Ultra-Personalization
Industry
4.0IoA
IoT

Internet-of-Things (IoT).
A craze of very big numbers of small things connected.
- 4.3 Trillion US Dollar Market by 2024*.
- 2.4× that of the Mobile Industry Revenue.
- 27 Billion IoT units installed by 2024*.
- 4 × that of unique mobile users.
- Up-to 1 million IoT units per km2.
- An urban macro cellular site might have
to serve up 3 million IoT units.
IoT Requirements:
- (ultra) low device cost.
- (ultra) low power consumption.
- Near-zero maintenance.
- Very long battery lifetimes.
- Versatile connectivity.
- Elastic latency ( 1 ms to seconds).
- Elastic Bandwidth ( bps to Mbps).
- Massive scalability  106 per km2(*) https://machinaresearch.com/news/the-global-iot-market-opportunity-will-
reach-usd43-trillion-by-2024/

Quiz (1 of 2)
• By 2024 27 Billion Global IOT connections are expected.
• World population is expected to be 8 Billion with ca. 3.5 people per household (HH).
• Planet Earth total surface area is 510 Million km2.
• Land area is ca. 150 Million km2
• Ca. 75 Million km2 is habitable.
• Max. 15 Million km2 is covered by urban development.
1. How many IOT connections do you have per HH and per km2 considering the total surface
area of Planet Earth.
2. How many IOT connections do you have per km2 considering only land area.
3. How many IOT connections do you have per km2 considering only urban development.
4. Does the amount of IOT devices per Household seem realistic? Compare with the expected
number of mobile devices per HH?
5. Assume that a typical urban cell site area of is ca. 3 km2 how many IoT connections do you
get that a cell site would be required to support?

Quiz (2 of 2)
• By 2024 27 Billion Global IOT connections are expected.
• On average an active IOT connection will use 140 Bytes (approx. size of SMS).
• On average an IOT is active 60 times per minute (60x24x7x365:-).
1. How many Mega Bytes will an IOT connection consume per day?
2. How many Mega Bytes will an IOT connection consume per month?
1. Compare that to the global average smartphone data consumption 2015 (ca. 1,200 MB).
3. How many Giga Bytes will an IOT connection consume per year?
4. What is the total amount of Exa Bytes (i.e., Billion Giga Byte) consumed by of all IOT
connections?
5. If by 2024 the total data consumption excluding IOT is in the order of 400 Exa Bytes (i.e.,
400 Billion Giga Bytes), what would the proportion of IOT data consumption be if included
in the total data consumption?

Global IoT growth projections.
2014 – 2024.
~ 2 IoT Connections
per 3 people
~2.5 IoT connections
per Household
~13 IoT connections
per Household
Note: global pop per HH is ~3.5, world surface area 510 Million km2 of which ca. 150 million km2 is land area of which ca. 75 million km2 is habitable. 3% is an upper
limit estimate of earth surface area covered by u