The Future ofMobile Communications

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An Open Access Wireless Market

Supporting Public Safety, Universal Service, and Competition

Peter CramtonLinda Doyle

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Summary• The cellular market is extremely inefficient, with a small number of

carriers dictating supply and pricing.• Implementing an Open Access Wireless Market (OAWM) will allow

supply and demand to determine prices by time and location, with the following consequences:– It will Increase innovation, generate new use cases, and diversify traffic patterns

– It will eliminate the barriers to entry

• This will transform the industry by increasing network utilization, reducing the price of data per GB and increasing data consumption dramatically.

• Rivada is actively working on implementation opportunities globally.

From monopoly to vibrant competition

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Monopoly• Original “Ma Bell” telecommunications

Oligopoly

• Spectrum auctions• Mobile communications

Competition

• Open Access Wireless Market (OAWM)• Wholesale-only provider eliminates the conflict of interest in the carrier retail / wholesale market• Neutral network with transparent, non-discriminatory pricing to MVNOs and wholesale consumer• Time and location pricing enhances network efficiency and promotes low-cost entry

Mobile networks

Open access network

(ISO)

Proprietary network 1

(MNO1)

Proprietary network 2

(MNO2)

Service providersMobile virtual

network operator (MVNO)

MNO1

MNO2

Users/devicesA B C D E F G

Retail market

Wholesale market

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Same market model as electricitysuccessfully operating for two decades

The Mobile market today is highly concentrated & retail centric Network Operators

$189 B $50 B $25 B

$56 B

$213 B

Retail Market

Spectrum Network

Wholesale

Retail

Vertical Integration

Licensed Spectrum

Spectrum

Wholesale Market

Mobile market tomorrow will be more diversified

Neutral Wholesale

Excess Capacity

Additional Capacity in Constrained Markets

Frictionless AccessTransparent PricesNet Neutrality Repeal

Spectrum Network

Wholesale

Retail

Vertical Integration

Licensed Spectrum

Wholesale

OAWM

$542 B

$84 B

$3.0 B

$1.5 B

$16 B

$98 B

$711 B

$168 B

$56 B

$873 B

$519 B

$636 B

$95 B

$58 B

$370 B

$52 B

Spectrum Network

Wholesale

Shared Spectrum

Excess CapacitySpectrum Holders

$23 B

$324 B

Network Operators Retail MarketSpectrum

Wholesale Market

$189 B $50 B $25 B

$213 B

MVNO & wholesale evolving

Wholesale • Wholesale-only provider eliminates the conflict

of interest in the carrier retail / wholesale market

Neutral• Neutral network with transparent, non-

discriminatory pricing to MVNOs and wholesale consumers

Time and Location pricing• Time and location pricing enhances network

efficiency and promotes entry

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M2M M2M Adopters

— Aeris— Kore/Wyless— Numerex— Spireon— Geotab— UPS

— Fitbit— UBI— Zubie— Auto OEMs— Gemalto— Trimble

Existing MNO’s— T-Mobile— Sprint— Verizon

Domestic MNOs— AT&T— Regional Carriers— Rural Carriers

International MNOs— Deutsche Telekom— Vodafone— Telefonica

— China Mobile— Orange— KDDI

Wholesale

— Virgin Mobile— Credo— Ting

Traditional MVNOs— ACN— Ready Mobile— TracFone

Tech Companies / Innovators

— Google— Apple— FreedomPop— Republic— Dell

— Amazon— Netflix— IBM— Hewlett-Packard— Microsoft

Cable Operators/Rural Carriers

— Comcast— Cox— Charter— iWireless

— SouthernLinc— C-Spire— Cellular One— US Cellular

LifeLine

— TracFone— Q Link— Total Call— Boomerang— Budget PrePay

— iWireless— Safelink— TruConnect— Tag Mobile— Ready Wireless

There are many interested parties and more to come

• Diversifying the wireless ecosystem

• Innovating business models

• Diversifying the traffic patterns

Range of potential customers is wide & varied

National Needs

Neutral wholesale network reduces the tension between competition and efficiency

Efficiency

Competition

1 MNO

2 MNO

3 MNO4 MNO

Independent operation

Passive Infrastructure Sharinge.g. Tower sharing

Network Sharinge.g. MORAN or MOCN

Universal ServiceCompetitionPublic SafetyData explosion

Right Conditions

Global StandardsTechnological FlexibilityDemand HeterogeneityScarcity

Policy Innovations

Spectrum AccessInfrastructure AccessNo InfluenceISO

Business Innovations

Neutral Wholesale

Time and Location Pricing

The FUTURE

More Value Chain Agents

More Value Chain Agents

Neutral Wholesale

+ OAWM

The Current Model

• Market size is a determinant of profitability

• Smaller network operators cannot compete due to economies of scale

Demand aggregation allows neutral host to enjoy economies of scale previously available only to dominant operators

Wholesale market represents less than 10% of entire global market

0.00% 10.00% 20.00% 30.00% 40.00%

Argentina

Mexico

Poland

Colombia

Chile

Italy

Japan

Spain

Korea

France

United States

Austria

United Kingdom

Denmark

Germany

Netherlands

Market Share - %

The Current Model

• Inherent conflict of interest between seller (carrier) and buyer (MVNO)

• Buyers are competing with their own suppliers

• This hinders competition and keeps MVNOs small

MVNO Share of Market by Country

Operators are traditionally poor at maximizing value of assets

The Current Model

• Networks are built to meet peak demand

• Network utilization is low

• Spectrum utilization is low

• Investment diminished

Spectrum Usage in 2016

Source: http://dfmonitor.eu/networkeconomics/

Network Utilization in 2016

The Current Model

• There is a big mismatch between data needs and pricing

• Data needs and value vary by time and location

• Data prices are constant

Operators charge same price despite huge swings in demand

Manhattan – early morning Manhattan - evening

0

5

10

15

0%

20%

40%

60%

80%

1 3 5 7 9 11 13 15 17 19 21 23

Average Utilization: 35%

Net

wor

k U

tiliza

tion

Pric

e $

/ GB

Average Price

Hourly Price

Applying open access has dramatic impact on asset usage and revenue

The open access model

• A neutral time and location based market will drive increased utilization

• Prices reflect the value of data at every time and location

• Average prices decrease significantly

• Average utilization increases due to low prices

Manhattan – early morning Manhattan - Evening

0

5

10

15

0%

20%

40%

60%

80%

1 3 5 7 9 11 13 15 17 19 21 23Hour of day

Average Utilization: 65%

Average Utilization: 35%

Net

wor

k U

tiliza

tion

Pric

e $

/ GB

Average Price

Hourly Price

0

2

4

6

8

10

12

14

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Location, location, locationThe open access model

• Prices reflect the value of data at every time and location

• Local Prices reflect local data needs

• Utilization increases everywhere

Manhattan 6pm

Pric

e $

/ GB

Washington DC 6am

Operator traffic patternsAnonymized data consumption on a national carrier network

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

1% 10% 19% 28% 37% 46% 55% 64% 73% 82% 91% 100%

0.00%

1.00%

2.00%

3.00%

4.00%

5.00%

6.00%

7.00%

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Location Percentile

Hour of day

% o

f dat

a co

nsum

ptio

n%

of d

ata

cons

umpt

ion • Data consumption by hour of day

• The network is better utilized in the evening (Netflix Effect) but a lot of capacity is wasted in the early morning.

• The network is broken down into 100 buckets, each with an equal number of sites ordered by usage. The usage in the busiest bucket is 1,700 times greater than the least used bucket.

• Data consumption is highly concentrated in a few buckets, producing low utilization in many areas without much traffic

Open access will have a dramaticeffect on date use and price

The open access model

• Coverage Design for a National Network on the 700 MHz band

• Current Model:• Price per GB will drop from $7.1 to $2.3• Consumption will rise from 4 GB to 22 GB

• Key economic assumptions:• Price elasticity: 1.3• Elasticity of substitution: 0.3

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35% 45% 55% 65% 75%

GB per Month

Price per GB

GB/Month/Sub $/GB

4 GB/Month/Sub – Current Model

7.1 $/ GB – Current Model

Target Utilization

2.3 $/ GB – Rivada Model

22 GB/Month/Sub – Rivada Model

0.001.002.003.004.005.006.007.008.009.00

35% 45% 55% 65% 75%

An increase in network utilization has a material impact on revenue & enterprise value

The Rivada Model

• Better utilization means more revenue• Existing assets are utilized better• New investments have better

returns

• When compared with a traditional retail-centric network, the Neutral Wholesale Model with the OAWM can increase revenue and enterprise value

• Increasing utilization from 35% to 65%, increases:

• Revenue by 31%• Enterprise value by 45%

0.00

5.00

10.00

15.00

20.00

25.00

35% 45% 55% 65% 75%

$ B

Revenue

$ BEnterprise Value

18% 25%31% 37%

58%45%

31%15%

Network Utilization

Network Utilization

Characteristics of open access Spectrum Sharing

• Feasible only for marginal quantities of spectrum

• Vertical sharing between drastically different uses

• Military vs Commercial• Mobile communications vs Point-to-

Point

• Horizontal sharing between similar users• Redundant and idle investments

• Extremely difficult to manage• Interference• Incentives

• Market for wireless capacity, not spectrum• Capacity (throughput) is generated from both

spectrum and network assets• Based on best practices from existing time and

locational markets. Core tenets are efficiency, transparency, simplicity and fairness

• All users have access to the same technology

• Feasible for large quantities of spectrum across frequency bands

• Compatible with traditional bilateral wholesale contracts

• Simple to manage:• Interference is managed at the network level• Transparent, market-driven pricing aligns incentives

• See whitepaper at: OpenAccessWireless.com

Open access facilitates a more efficient way of allocating spectrum

Current license modelLicenses are auctioned to the highest bidder• Bids reflect the value of:

• Using the spectrum• Rents from monopolistic competition• Rents from blocking entry

• Consumer prices ($/GB) are high• Inferior services

• Slow deployment• Constrained coverage

• Barriers to entry are high• Few service providers• Few users

• Incentivizes spectrum hoarding

• Spectrum is paid recurrently:• Price reflects the fair market value value of using

the spectrum• Innovations get accounted in the price

• Nominal barriers to entry:• Local and fast deployment is possible• Innovation flourishes – new uses of data• Competitive prices

Open access is a perfect merger remedy Based on experience:

• Similar to recent 4-to-3 merger remedies in Germany and Ireland, but much more responsive to changing market

• Similar to electricity merger remedy: auction portion of generation as “Virtual Power Plants” e.g. EDF 2001-2012

• Set aside a portion of capacity to the open access market

• Assignment and prices determined to maximize gains from trade in open competitive process

• Assignment and prices respond to changing market

• Market evolves with environment

• Merged entity receives competitive market value for network resource, and ongoing interest in success of service providers

Product design

• Product should be directly valued by consumer• Network throughput at particular location and time interval and latency• A market for throughput and latency not spectrum• Energy (MWh) in an electricity market

• Aggregation in both time and location to simplify and improve liquidity

• Example: Particular cell over one hour (GB/h)

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Price($/GB)

Quantity(GB/h)

P*

Q*

Demand

Supply

Winning buyers

Winning sellers

Clearing price

Quantity traded

All markets use single-price auction

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Hourly area A

Hourly area B

Hourly area J

…

Hour 7 Hour 15 Hour 3

On peak Off peak

DemandLow Medium HighMonthly area M

Multiple opportunities to trade:Yearly, monthly, hourly

25Yearly aggregates monthly aggregates hourly in time and location

5 GB5 GB

5 GB 10 GB

10 GB5 GB

5 GB 5GB

5 GB5 GB

15 GB 15 GB

10 GB10 GB

5 GB 5 GB

5 GB5 GB

5 GB 5 GB

5 GB10 GB

5 GB 5 GB

Yearly auction = buy 165 GB per hour, for every peak hour in the year, in the yearly area

Service provider estimates demand and stages purchase in three markets

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4 GB4 GB

4 GB 9 GB

9 GB4 GB

4 GB 7GB

7 GB4GB

17 GB 17 GB

12 GB12 GB

7 GB 7GB

8 GB8 GB

8 GB 8 GB

8 GB12 GB

7 GB 8 GB

Monthly auction = sell 8 GB per hour, for every peak hour in the month, in the red area

Monthly auction = buy 15 GB per hour, for every peak hour in the month, in the green area

Yearly auction = buy 165 GB per hour, for every peak hour in the year, in the yearly area

Monthly auction = buy 20 GB per hour, for every peak hour in the month, for the blue area

Refine estimate and make adjustment in monthly market

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8 GB

Hour Change Net

07 Buy 3 GB 11 GB

08 Sell 2 GB 6 GB

… … …

17 Buy 1 GB 9 GB

Hourly area H Peak hour product

Finalize estimate one hour ahead and make final adjustment to demand

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Yearlyauction

Monthly auctions

Hour ahead

auction

Hourly realization

Buy 8 GBin each hour

April:Sell 1 GB7 GB net

April 5, hour 15: Buy 3 GB10 GB net

April 5, hour 15: -1 GB deviation9 GB demand

Example

Sequence of auctions

• Three opportunities to trade• Reduces risk of service provider• Facilitates planning of service provider• Provides price transparency• Mitigates market power

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Prototype auction platform

• To illustrate market• Demonstrate proof of concept

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Auction design

• Uniform-price auction for each product• Preferences expressed as piecewise-linear strictly-decreasing demand

curves• Consistent with underlying preferences• Unique clearing prices and quantities

• Yearly and monthly auctions: simultaneous ascending clock

• Hourly auction: sealed bid

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Sample demand for bidderManhattan (peak) monthly

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Addressing hourly deviations between actual and purchased demand

• Neither system operator nor service provider can control demand perfectly to assure quantity consumed = quantity won

• Deviations are inevitable• Final settlement should motivate service providers to limit deviations

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Hourly settlement for deviations• 𝑝𝑝ℎ𝑘𝑘 = price in hour h in area k that balances as-bid demand with estimated supply• 𝑞𝑞𝑖𝑖ℎ𝑘𝑘 = total quantity bought by bidder i in hour h in hourly area k

(includes yearly, monthly, and hourly net purchases)• 𝑄𝑄𝑖𝑖ℎ𝑘𝑘 = actual quantity consumed by bidder i in hour h in hourly area k• 𝐷𝐷𝑖𝑖ℎ𝑘𝑘 = 𝑄𝑄𝑖𝑖ℎ𝑘𝑘 − 𝑞𝑞𝑖𝑖ℎ𝑘𝑘 = deviation between actual quantity consumed and quantity

bought• Tolerance = percentage tolerance band (e.g., 10%);

no penalty if deviation is within Tolerance• Penalty Factor = a factor that is applied to square deviations above Tolerance• Adjustment for deviations in the real-time market is𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑖𝑖ℎ𝑘𝑘 = 𝑝𝑝ℎ𝑘𝑘 × 𝐷𝐷𝑖𝑖ℎ𝑘𝑘 + 𝑃𝑃𝐴𝐴𝐴𝐴𝑃𝑃𝑃𝑃𝐴𝐴𝑃𝑃𝑖𝑖ℎ𝑘𝑘 where

• 𝑃𝑃𝐴𝐴𝐴𝐴𝑃𝑃𝑃𝑃𝐴𝐴𝑃𝑃𝑖𝑖ℎ𝑘𝑘 = �0 𝑖𝑖𝑖𝑖 𝐷𝐷𝑖𝑖𝑖𝑖𝑖

𝑞𝑞𝑖𝑖𝑖𝑖𝑖≤ 𝑇𝑇𝑇𝑇𝑃𝑃𝐴𝐴𝑇𝑇𝑃𝑃𝐴𝐴𝑇𝑇𝐴𝐴

𝑃𝑃𝐴𝐴𝐴𝐴𝑃𝑃𝑃𝑃𝐴𝐴𝑃𝑃 𝐹𝐹𝑃𝑃𝑇𝑇𝐴𝐴𝑇𝑇𝑇𝑇 × 𝑝𝑝ℎ𝑘𝑘 × 𝐷𝐷𝑖𝑖ℎ𝑘𝑘2 𝑖𝑖𝑖𝑖 𝐷𝐷𝑖𝑖𝑖𝑖𝑖𝑞𝑞𝑖𝑖𝑖𝑖𝑖

> 𝑇𝑇𝑇𝑇𝑃𝑃𝐴𝐴𝑇𝑇𝑃𝑃𝐴𝐴𝑇𝑇𝐴𝐴

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Standard efficient settlement if deviation is within Tolerance;penalty based on squared deviation outside of Tolerance to induce best estimate and control of demand to match winnings

Likely implementations• Mexico (competition)

• 90 MHz of 700 MHz set aside for open access• RFP to select implementer in 28 Sep 2016

• United States (public safety)• 20 MHz of 700 MHz set aside + $7 billion• RFP to select implementer in November 2016

• European Union (merger remedy)e.g. UK: Three & O2• Proposed mergers leading from 4 to 3 carriers• Merged entity allocates portion of network to open access

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