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SPECTRUM MARKETS

MSIT Week 10

Michael Honig Department of EECS

Northwestern University

March 2014

Spectrum Markets

Policy Economics Engineering

Rakesh Vohra, Kellogg MEDS

Randall Berry, Michael Honig, EECS

2

High Profile Issue 3

Why Spectrum Markets?

¨  New policies are needed for spectrum allocation. ¤ Markets are natural policy candidates.

¨  Markets for spectrum pose unique challenges/questions. ¤ Definition of property rights, interference externalities ¤ Efficiency, incentives, wireless system design

¨  Interplay between economics and engineering issues

4

Background Spectrum Sharing Models Market structures How should spectrum be managed?

Outline 5

Limited Supply of Spectrum

good for cellular (300 MHz to 3 GHz)

6

Increasing Demand

Spark-gap transmitter

(Tesla, 1893)

7

Spectrum “Crunch” P

etab

ytes

per

mon

th

8

Regulation Prior to 1927: Open to All

Earliest uses of wireless for ship-to-ship, ship-to-shore communications.

Broadcast radio begins in 1921. Licenses issued by the Department of Commerce.

9

Two Landmark Cases

Hoover vs Intercity Radio, 1923 United States vs Zenith Radio, 1926

Herbert Hoover, US Sec. of Commerce

Department of Commerce has no authority to regulate licenses.

è Broadcasting boom: 200 new stations appeared in < 6 months. Interference created “chaotic” radio environment (tragedy of the commons).

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Spectrum Property Rights: A False Start

¨  Congress subsequently passed legislation prohibiting spectrum property rights

¨  Licenses issued for 90 days.

¨  Tribune vs Oak Leaves Broadcasting, 1926 ¤ Property right allowed based

on “homesteading” ¤  Interfering stations could be fined.

11

Regulation since 1927: “Command and Control”

¨  Federal Radio Commission (FRC) established in 1927.

¨  Federal Communications Commission (FCC)

established in 1934.

¨  Maintains authority to ¤ Grant / renew / deny licenses for spectrum use. ¤ Assign applications to particular frequencies. ¤  Police content and use

“Wise old man approach to spectrum allocation”

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The Spectrum Paradox

¨ Spectrum is a scarce resource ¨ Spectrum is underutilized

13

Spectrum is a Scarce Resource

“beachfront property” Nearly $20B netted for 700 MHz auctions in 2008.

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Spectrum is Underutilized

Spectrum measurements in New York City and Chicago conducted by Shared Spectrum Co.

15

An Economist’s Proposal

Ronald Coase, 1991 Nobel Laureate in Economics

Introduce spectrum property rights, sell to highest bidders, do not restrict use.

R. Coase, “The federal communications commission,” J. Law and Economics, pp. 1–40, 1959.

Coase’s “Theorem”: In the absence of transaction costs, spectrum owners will trade rights so that the outcome allocates spectrum to best use.

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Role of government should be to minimize transaction costs.


17




Spectrum auctions finally introduced in the 1990s. Restrictions on use remain.



18

A Governor’s Proposal

Rod Blagojevich Former governor of Illinois

Introduce property rights for senate seat, sell to highest bidder.

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A Governor’s Proposal

Rod Blagojevich Former governor of Illinois

Introduce property rights for senate seat, sell to highest bidder.

Found guilty of violating federal laws…

20

Exclusive use (liberal licenses) Commons Hierarchical (cognitive radio)

Spectrum Sharing Models 21

Spectrum Property Right: Liberal License

¨  Spectrum is publicly owned, but licensed for exclusive use

¨  Liberal use rules ¤ Does not dictate technology

(cellular, WiFi commons, satellite,…)

¨  Allows spectrum trading ¤ Can re-allocate spectrum on large scales. ¤ Can define/trade spectrum contracts on finer scales

22

Spectrum Commons

¨  State-regulated (unlicensed) ¤ Spectrum owned by government ¤  Etiquette rules part of industry standard (802.11)

¨  Privately owned (licensed) ¤  Licensee sets rules, polices band ¤ Revenue from selling approved equipment

¨  Open access ¨  Requires etiquette rules

for sharing

23

Engineering Approach to Spectrum Crunch

¨  Add intelligence to mobile devices ¤  Frequency agility ¤ Wideband sensing ¤  Interference avoidance ¤ Adaptive quality of service

(context aware)

¨  Enables spectrum scavenging Cognitive Radio

Mitola and Maguire (1999)

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Hierarchical

¨  Primary and secondary users ¨  Secondary users must not

disrupt primary users ¨  Relies on cognitive radio

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Hierarchical

¨  State-regulated ¤ Spectrum owned by government ¤ Use rules for secondary users part of standard (802.22)

¨  Private contracts with “spectrum scavengers”

¤  Interference levels/payments set by mutual agreement



26

Hierarchical: Technologies

¨  Underlay: low-power, spread spectrum for secondary users

¨  Overlay: exploit white spaces left by primary users



27

Current Allocations

¨  Mix of: ¤  restricted use bands (e.g., broadcast TV) ¤  liberalized licenses (cellular) ¤  state-regulated commons (WiFi)

¨  Active trading of liberalized licenses among commercial service providers

¨  US policy trends have favored assignments of unlicensed spectrum over liberalized licenses

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Why Unlicensed Spectrum?

¨  Pushed by DARPA

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Why Unlicensed Spectrum?

¨  Pushed by DARPA ¤ Military needs distributed, dynamic methods for

spectrum sharing across military units

¨  Also by Microsoft, Google, Apple ¤  Facilitates 3rd-party software applications

¨  Success of WiFi

30

IEEE Spectrum Magazine, March 2004

Bold Predictions… 31

January 2014

Arguments for Unlicensed Spectrum

¨  Encourages innovation (WiFi, Bluetooth, etc.). ¨  Reduces barriers to entry. ¨  Has created at least as much value as licensed.

Huawei, Rolling Meadows

32

See [Benkler, 2012], [Eilat, Milgrom, Levin, 2011]

January 2014

Counter-arguments

¨  Technologies developed for unlicensed spectrum could be developed for licensed use as well.

¨  WiFi uses a simple, distributed interference management scheme inappropriate for applications requiring high spectral efficiency.


Unlicensed spectrum encourages innovation (WiFi, Bluetooth, etc.)

33

January 2014

Counter-arguments

¨  This may lead to a tragedy of the commons due to excessive interference.

¨  Unlicensed erects barriers to investment along with technologies and applications that may generate the highest social value.


Unlicensed spectrum lowers barriers to entry.

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January 2014

Value of Unlicensed


Unlicensed spectrum has created at least as much value as licensed.

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[According to FCC Commissioner Jessica Rosenworcel], “recent economic studies that add up the broader impact of unlicensed spectrum on the economy estimate its annual value at more than $140 billion.” FCC's Rosenworcel looks to 5 GHz band, 600 MHz guard bands for unlicensed wireless - FierceWireless

January 2014

Counter-arguments

¨  The value of spectrum must be separated from the value of the application it supports.

¨  The total value must be distinguished from the marginal value. ¨  Value depends on congestion and interference management.


Unlicensed spectrum has created at least as much value as licensed.

36

January 2014

How to assess spectrum value?

¨  Evaluate as an opportunity cost: If spectrum X were not available, then what would be the cost of serving those applications?

¨  Evaluate marginal value: If additional spectrum δX were allocated to application A, then how much additional demand could be supported?

¨  Evaluate congestion cost: How much is congestion reduced by adding spectrum or investing in interference management?


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The Case for Liberal Licenses

ITA, San Diego February 2014

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¨  Advocates: ¤ Encourages investment

(cellular), efficient use ¤ Does not constrain technology,

rules for spectrum sharing n Cellular, WiFi, Satellite,

broadcast… ¤ Facilitates trading

[Hazlett, 2010]

¨  Detractors: ¤ Has led to oligopoly

Spectrum Supply Curve

Spectrum price ($/Hz)

supply

demand

Qua

ntity

of s

pect

rum

(Hz)

As the spectrum price goes to zero: –  The supply decreases due to the decrease in spectral efficiency. –  The demand increases due to introduction of new services.

Equilibrium price

39

Commons vs Market


market transaction costs < cost of interference è Set up spectrum market

Qua

ntity

of s

pect

rum

(Hz)

Spectrum market Commons

supply

demand

p*

40

Commons vs Market


cost of interference < market transactions costs è Use commons model

Qua

ntity

of s

pect

rum

(Hz)

Spectrum market Commons

supply

demand

p*

41

Bit pipe Spot markets Local transactions

Market Structures 42

“Bit Pipe” Model

¨  “Wholesale” contract with cellular provider

Kindle

43


¨  “Wholesale” contract with cellular provider ¨  Mobile Virtual Network Operators (MVNO’s)

¤ Resells mobile services (e.g., Virgin Mobile)

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¨  “Wholesale” contract with cellular provider ¨  Mobile Virtual Network Operators (MVNO’s)

¤ Resells mobile services (e.g., Virgin Mobile)

¨  Emerging model for wholesale cellular provider ¤ Open broadband network ¤ No retail services ¤ Wide coverage

45

“Bit Pipe” Model: Properties

¨  Wide-area coverage, high mobility ¨  Interference management ¨  Quality of Service guarantees ¨  Facilitates new wide-area wireless services ¨  Well-matched to lower frequency assignments

46

Spectrum Spot Market

Licensees A, B, C, …

Spectrum Broker

Service providers (Acme Wireless)

Service requests

¨  Immediate access, rapid (automated) transactions ¨  Low transaction costs ¨  Facilitates local services ¨  No need to build out large footprint

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Wireless Spot Market

Owners A, B, C, …

Spectrum Broker


Service requests

¨  Spectrum can be bundled with equipment ¨  Broker allocates spectrum and technology

(e.g., cellular/commons) ¨  Spot market for bits

48

Market Mechanisms

¨  Sets prices, attempts to clear market

¨  Auction mechanism: collects bids; determines allocation

¨  Can be automated (“spectrum server”)

Owners A, B, C, …

Spectrum Broker


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Spectrum Contracts

Owners A, B, C, …

Spectrum Broker


¨  Contracts can be arranged across: ¤  Frequency (spread spectrum, underlay) ¤  Locations (mesh networking) ¤  Time (time-of-day, futures, scavenging)

¨  Variable QoS guarantees (statistical)

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Interference Management

Owners A, B, C, …

Spectrum Broker


¨  Spectrum assets predefined by owners ¤  Service providers must comply with power limits,

interference constraints ¨  Spectrum assets partitioned, assigned by broker

to satisfy service requests

51

Commercial broadband access Clean slate

How should spectrum be managed? 52

Spectrum Management: Observations

¨  Coverage is easy ¨  Interference

management is difficult

Low Freqs. (< 1 GHz)

High Freqs. (> 3 GHz)

¨  Coverage is difficult ¨  Interference

management is easy

Frequency à

53

Spectrum Management: High-Level

¨  Wide-area coverage ¨  Coordinated

interference management

¨  Expensive infrastructure



¨  Local coverage ¨  Distributed

interference management (random access)

¨  Inexpensive

Frequency à

54

Shrinking Cells


Frequency à


¨  Macro-cells ¨  Coordinated



¨  Femto-cells/WiFi ¨  Distributed


¨  Inexpensive

55

Spectrum Sharing Models

¨  Exclusive use (licensed) ¤  Encourages investment

in infrastructure

¨  “Bit Pipe” (e.g., Light Squared)



¨  Commons ¨  Public

(unlicensed)

¨  Private (licensed)

Frequency à

56

Spectrum Management: High-Level

¨  Macro-cells ¨  Coordinated



Bit Pipe (< 1 GHz)

¨  Femto-cells/WiFi ¨  Distributed


¨  Inexpensive

Frequency à

Commons (> 3 GHz)

Dynamic Spectrum Markets?

¨  Micro-cells ¨  Light interference

management

¨  Spectrum servers

¨  Rapid transactions

57

What about Cognitive Radio?

¨  Enables spectrum scavenging ¤ Sense/exploit white spaces

¨  Could be applied to licensed or unlicensed spectrum ¤  Focus has been on unlicensed

access for secondary users

58

Where does cognitive radio fit?

Bit Pipe (< 1 GHz)

Frequency à

Commons (> 3 GHz)

¨  Coordinated interference management


¨  Distributed interference management (random access)

¨  Inexpensive

59


Bit Pipe (< 1 GHz)

Frequency à

Commons (> 3 GHz)



¨  Distributed interference management (random access)

¨  Inexpensive

60


Bit Pipe (< 1 GHz)

Frequency à

Commons (> 3 GHz)



Need only simple dynamic channel assignment. Sensing, scavenging is probably unnecessary.

61


Bit Pipe (< 1 GHz)

Frequency à

Commons (> 3 GHz)



Dynamic Spectrum Markets

Scavenging spectrum across multiple service providers via a spot market may be useful, but…

62


Bit Pipe (< 1 GHz)

Frequency à

Commons (> 3 GHz)



Dynamic Spectrum Markets

Scavenging spectrum across multiple service providers via a spot market may be useful, but… ! SPs would control available spectrum ! “cognitive” means “frequency-agile”

63

Spectrum Management: Two Views

¨  Spectrum is abundant ¤  It is just poorly managed

¨  Spectrum will remain scarce ¤ Applications will be generated to use new spectrum ¤ Shift to cheaper, spectrally inefficient technologies

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Transition to Spectrum Abundance

¨  Tradeoff between spectrum efficiency and power efficiency ¤  Shift emphasis towards low-power, inexpensive wideband

signaling techniques

¨  Efficiency becomes limited by transaction costs ¤  Spot markets with distributed interference management ¤  Transparent (standardized?) mechanism (pricing/auction) ¤ Wireless devices: frequency/technology agile, compatible

with spot market mechanism

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Many Remaining Challenges

Policy Economics

Engineering

Interference management Incentives, efficiency Market design

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Many Remaining Challenges

Policy Economics

Engineering

Interference management Incentives, efficiency Market design

Transition to spectrum markets??

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