SPECTRUM MARKETS Michael Honig Department of EECS Northwestern University March 2013 MSIT Week 10
Spectrum Markets 2 Engineering Policy Economics Randall Berry, Michael Honig, EECS Rakesh Vohra, Kellogg MEDS
3 High Profile Issue
Why Spectrum Markets? 4 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
5 Outline Background Spectrum Sharing Models Market structures How should spectrum be managed?
Limited Supply of Spectrum 6 good for cellular (300 MHz to 3 GHz)
Increasing Demand 7 Spark-gap transmitter (Tesla, 1893)
Spectrum Crunch 8 Petabytes per month
Regulation Prior to 1927: Open to All 9 Earliest uses of wireless for ship-to-ship, ship-to-shore communications. Broadcast radio begins in 1921. Licenses issued by the Department of Commerce.
Two Landmark Cases 10 Hoover vs Intercity Radio, 1923 United States vs Zenith Radio, 1926 Department of Commerce has no authority to regulate licenses. è Broadcasting boom: 200 new stations appeared in < 6 months. Herbert Hoover, US Sec. of Commerce Interference created chaotic radio environment (tragedy of the commons).
Spectrum Property Rights: A False Start 11 Tribune vs Oak Leaves Broadcasting, 1926 Property right allowed based on homesteading Interfering stations could be fined. Congress subsequently passed legislation prohibiting spectrum property rights Licenses issued for 90 days.
Regulation since 1927: Command and Control 12 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
The Spectrum Paradox 13 Spectrum is a scarce resource Spectrum is underutilized
Spectrum is a Scarce Resource 14 Nearly $20B netted for 700 MHz auctions in 2008. beachfront property
Spectrum is Underutilized 15 Spectrum measurements in New York City and Chicago conducted by Shared Spectrum Co.
An Economist s Proposal 16 Ronald Coase, 1991 Nobel Laureate in Economics R. Coase, The federal communications commission, J. Law and Economics, pp. 1 40, 1959. Introduce spectrum property rights, sell to highest bidders, do not restrict use. Coase s Theorem : In the absence of transaction costs, spectrum owners will trade rights so that the outcome allocates spectrum to best use.
An Economist s Proposal 17 Ronald Coase, 1991 Nobel Laureate in Economics R. Coase, The federal communications commission, J. Law and Economics, pp. 1 40, 1959. Introduce spectrum property rights, sell to highest bidders, do not restrict use. Coase s Theorem : In the absence of transaction costs, spectrum owners will trade rights so that the outcome allocates spectrum to best use. Role of government should be to minimize transaction costs.
An Economist s Proposal 18 Ronald Coase, 1991 Nobel Laureate in Economics R. Coase, The federal communications commission, J. Law and Economics, pp. 1 40, 1959. Introduce spectrum property rights, sell to highest bidders, do not restrict use. Coase s Theorem : In the absence of transaction costs, spectrum owners will trade rights so that the outcome allocates spectrum to best use. Spectrum auctions finally introduced in the 1990s. Restrictions on use remain.
A Governor s Proposal 19 Introduce property rights for senate seat, sell to highest bidder. Rod Blagojevich Former governor of Illinois
A Governor s Proposal 20 Introduce property rights for senate seat, sell to highest bidder. Found guilty of violating federal laws Rod Blagojevich Former governor of Illinois
21 Spectrum Sharing Models Exclusive use (liberal licenses) Commons Hierarchical (cognitive radio)
Spectrum Property Right: Liberal License 22 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
Spectrum Commons 23 Open access Requires etiquette rules for sharing 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
Engineering Approach to Spectrum Crunch 24 Add intelligence to mobile devices Frequency agility Wideband sensing Interference avoidance Adaptive quality of service (context aware) Cognitive Radio Mitola and Maguire (1999) Enables spectrum scavenging
Hierarchical 25 Primary and secondary users Secondary users must not disrupt primary users Relies on cognitive radio
Hierarchical 26 Primary and secondary users Secondary users must not disrupt primary users Relies on cognitive radio 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
Hierarchical: Technologies 27 Primary and secondary users Secondary users must not disrupt primary users Relies on cognitive radio Underlay: low-power, spread spectrum for secondary users Overlay: exploit white spaces left by primary users
Current Allocations 28 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 About 10 billion MHz-pops annually since 2003 [Mayo & Wallsten `10] US policy trends have favored assignments of unlicensed spectrum over liberalized licenses 955 MHz unlicensed vs 422 MHz licensed in the US (2008)
Why Unlicensed Spectrum? 29 Pushed by DARPA
Why Unlicensed Spectrum? 30 Pushed by DARPA Military needs distributed, dynamic methods for spectrum sharing across military units Also by Microsoft, Google, Apple Facilitates 3 rd -party software applications Success of WiFi Interference not a major issue for local coverage, light loads
Bold Predictions 31 IEEE Spectrum Magazine, March 2004
Engineering Issues 32 Difficult to guarantee Quality of Service Limits applications Problems with secondary user model Sensing problematic, constraints compromises utility WiFi does not scale; inappropriate for wide-area data in urban settings
Economic Issues 33 No means for reallocating spectrum to applications with higher utility e.g., wide-area data with coordinated interference management No direct means to move incumbent applications to another band/wireline service e.g., wireless mics, broadcast TV Congestion effects may adversely affect competition among licensed service providers
The Case for Liberal Licenses 34 Facilitate coordinated interference management. Provide incentive for investment in infrastructure. Allow competition among different technologies: Cellular WiFi commons Light interference management Allow spectrum trading, scavenging: Can re-allocate spectrum on large scales. Can define/trade spectrum contracts on finer scales.
35 Background and Motivation History Spectrum sharing models Motivation for spectrum markets
Do We Need Spectrum Markets? 36 A more fundamental question: Is spectrum scarce or abundant? Spectrum is abundant à use Commons Model
Do We Need Spectrum Markets? 37 A more fundamental question: Is spectrum scarce or abundant? Spectrum is abundant à use Commons Model Spectrum is scarce: Commons model à tragedy of the commons NU, April 2009
Do We Need Spectrum Markets? 38 A more fundamental question: Is spectrum scarce or abundant? For short-range communications (< 50 meters), spectrum is abundant (>3 GHz) è commons is appropriate What about for longer-range communications? Ultimately a technical question
Rate Calculation 39 Extensive spectrum sharing Roughly 1 GHz between 150 MHz and 3 GHz Cellular Infrastructure System Assumptions No intra-cell interference (time-division multiplexing) Limited inter-cell interference. All users are active all the time.
Rate Calculation: Assumptions 40 User at cell boundary (worst-case) Standard large-scale propagation model Uniform power over frequency Shannon rate with 6 db margin Frequency reuse optimized over each 1 MHz band
Achievable Rate per User 41 Rate per user (Mbps) Cell radius = 200 m 300 m 400 m 500 m Dense urban area Worst-case rate is about 2 Mbps with cell radius of 200 m user density (Kusers/km 2 )
Is Spectrum Scarce or Abundant? 42 2 Mbps per user seems like a lot, but recall the assumptions: 1 GHz of shared bandwidth, no fading Infrastructure of access points (200 m radius) Optimized frequency reuse Spectrally efficient modulation Also, less expensive spectrum encourages lower-cost, spectrally inefficient systems.
Spectrum Supply Curve 43 Quantity of spectrum (Hz) Equilibrium price supply demand Spectrum price ($/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.
Commons vs Market 44 Quantity of spectrum (Hz) Commons Spectrum market supply demand p* Spectrum price ($/Hz) market transaction costs < cost of interference è Set up spectrum market
Commons vs Market 45 Quantity of spectrum (Hz) Commons Spectrum market supply demand p* Spectrum price ($/Hz) cost of interference < market transactions costs è Use commons model
46 Market Structures Bit pipe Spot markets Local transactions
Bit Pipe Model 47 Wholesale contract with cellular provider Kindle
Bit Pipe Model 48 Wholesale contract with cellular provider Mobile Virtual Network Operators (MVNO s) Resells mobile services (e.g., Virgin Mobile)
Bit Pipe Model 49 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
Bit Pipe Model: Properties 50 Wide-area coverage, high mobility Interference management Quality of Service guarantees Facilitates new wide-area wireless services Well-matched to lower frequency assignments
Spectrum Spot Market 51 Spectrum Broker Service requests Service providers (Acme Wireless) Licensees A, B, C, Immediate access, rapid (automated) transactions Low transaction costs Facilitates local services No need to build out large footprint
Wireless Spot Market 52 Spectrum Broker Service requests Service providers (Acme Wireless) Owners A, B, C, Spectrum can be bundled with equipment Broker allocates spectrum and technology (e.g., cellular/commons) Spot market for bits
Market Mechanisms 53 Spectrum Broker Sets prices, attempts to clear market Auction mechanism: collects bids; determines allocation Can be automated ( spectrum server ) Service providers (Acme Wireless) Owners A, B, C,
Spectrum Contracts 54 Spectrum Broker Service providers (Acme Wireless) Owners A, B, C, Contracts can be arranged across: Frequency (spread spectrum, underlay) Locations (mesh networking) Time (time-of-day, futures, scavenging) Variable QoS guarantees (statistical)
Interference Management 55 Spectrum Broker Service providers (Acme Wireless) Owners A, B, C, Spectrum assets predefined by owners Service providers must comply with power limits, interference constraints Spectrum assets partitioned, assigned by broker to satisfy service requests
Commons versus Market 56 Quantity of spectrum (Hz) Commons Spectrum market supply demand p* Spectrum price ($/Hz) Commons/market boundary depends on associated costs.
Commons versus Market 57 Quantity of spectrum (Hz) Commons Spectrum market supply demand p* Spectrum price ($/Hz) Can we shift the boundary to the right with distributed interference management schemes?
Local Transactions 58 Routers use the same channel, cause little interference
Local Transactions 59 Would cause excessive interference.
Deterence Price 60 $ $ Pay new user to not setup access point in exchange for sharing capacity.
Usage Price 61 $ $ Set up community of access points, charge fee for sharing capacity (Fonera).
TV White Space 62 FCC recently announced rules for use as unlicensed commons Devices must check data base to see if spectrum is available before using. Advocates: lowers entry barriers for new services Detractors: tragedy of the commons
Observations 63 Lower frequencies than WiFi è longer propagation better coverage more interference Incumbents will compete with services in TV white space.
Observations 64 Lower frequencies than WiFi è longer propagation better coverage more interference Incumbents will compete with services in TV white space. How will additional white space affect service providers and consumers?
Scenario 65 SP 1 SP 2 SP 3 frequency Incumbent service providers (SPs) have exclusive licensed bands.
Scenario 66 commons SP 1 SP 2 SP 3 frequency Incumbent service providers (SPs) have exclusive licensed bands. All incumbents and new entrants have access to commons (unlicensed band). How does this additional spectrum affect total welfare? Analyze using framework for competition in congested markets [Acemoglu, Ozdaglar `07]
Model: Summary 67 commons SP 1 SP 2 SP 3 frequency Each SP competes for pool of customers by announcing prices for licensed and unlicensed services. Customers choose SP based on Total price = Announced price + Congestion cost
Results: Summary 68 commons SP 1 SP 2 SP 3 frequency The equilibrium price of commons spectrum is zero. (Total price = congestion cost) Adding unlicensed spectrum can decrease total welfare (consumer + SP revenue). Happens over a substantial range of unlicensed bandwidth.
Why does total welfare decrease? 69 Adding the commons takes away customers from an SP, lowers congestion cost for remaining customers. The SP increases its revenue by raising its announced price: Extracts additional surplus from its remaining customers Increases congestion in the commons (zero welfare) For a single incumbent consumer welfare increases with bandwidth.
Observations 70 Decrease in total welfare is analogous to Braess s paradox in transportation networks. To avoid, must restrict or charge for entry to commons. Possible enhancements of model: More general demand/latency functions Investment costs Deployment geometry
71 How should spectrum be managed? Commercial broadband access Clean slate
Spectrum Management: Observations 72 Low Freqs. (< 1 GHz) High Freqs. (> 3 GHz) Frequency à Coverage is easy Interference management is difficult Coverage is difficult Interference management is easy
Spectrum Management: High-Level 73 Low Freqs. (< 1 GHz) High Freqs. (> 3 GHz) Frequency à Wide-area coverage Coordinated interference management Expensive infrastructure Local coverage Distributed interference management (random access) Inexpensive
Shrinking Cells 74 Low Freqs. (< 1 GHz) High Freqs. (> 3 GHz) Frequency à Macro-cells Coordinated interference management Expensive infrastructure Femto-cells/WiFi Distributed interference management (random access) Inexpensive
Spectrum Sharing Models 75 Low Freqs. (< 1 GHz) High Freqs. (> 3 GHz) Frequency à Exclusive use (licensed) Encourages investment in infrastructure Bit Pipe (e.g., Light Squared) Commons Public (unlicensed) Private (licensed)
Spectrum Management: High-Level 76 Bit Pipe (< 1 GHz) Macro-cells Coordinated interference management Expensive infrastructure Dynamic Spectrum Markets? Frequency à Micro-cells Light interference management Spectrum servers Rapid transactions Commons (> 3 GHz) Femto-cells/WiFi Distributed interference management (random access) Inexpensive
What about Cognitive Radio? 77 Enables spectrum scavenging Sense/exploit white spaces Could be applied to licensed or unlicensed spectrum Focus has been on unlicensed access for secondary users
Where does cognitive radio fit? 78 Bit Pipe (< 1 GHz) Coordinated interference management Expensive infrastructure Frequency à Commons (> 3 GHz) Distributed interference management (random access) Inexpensive
Where does cognitive radio fit? 79 Bit Pipe (< 1 GHz) Coordinated interference management Expensive infrastructure Frequency à Commons (> 3 GHz) Distributed interference management (random access) Inexpensive
Where does cognitive radio fit? 80 Bit Pipe (< 1 GHz) Coordinated interference management Expensive infrastructure Frequency à Commons (> 3 GHz) Need only simple dynamic channel assignment. Sensing, scavenging is probably unnecessary.
Where does cognitive radio fit? 81 Bit Pipe (< 1 GHz) Dynamic Spectrum Markets Commons (> 3 GHz) Coordinated interference management Expensive infrastructure Frequency à Scavenging spectrum across multiple service providers via a spot market may be useful, but
Where does cognitive radio fit? 82 Bit Pipe (< 1 GHz) Dynamic Spectrum Markets Commons (> 3 GHz) Coordinated interference management Expensive infrastructure Frequency à Scavenging spectrum across multiple service providers via a spot market may be useful, but à SPs would control available spectrum à cognitive means frequency-agile
Spectrum Management: Two Views 83 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
Transition to Spectrum Abundance 84 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
Many Remaining Challenges 85 Economics Policy Engineering Incentives, efficiency Market design Interference management
Many Remaining Challenges 86 Economics Policy Transition to spectrum markets?? Engineering Incentives, efficiency Market design Interference management