spectrum trading: market-based architectures for ...

JOURNAL OF INFORMATION POLICY 3 (2013): 485-500.

SPECTRUM TRADING: MARKET-BASED ARCHITECTURES FOR DYNAMIC RADIO FREQUENCY SPECTRUM ACCESS BY CARLOS E. CAICEDO BASTIDAS

The traditional regime of spectrum allocation, in which governments assign frequencies for particular uses, leads to inefficiencies as large portions of available spectrum remain unused. In this article, Dr. Caicedo finds evidence that the scarcity of frequencies is artificial, and argues that technological innovation and new telecommunications business models are being held back as a result. Dr. Caicedo proposes the development of spectrum trading markets, and discusses their economic and technological viability for making spectrum usage more efficient for consumers and wireless service providers.

INTRODUCTION The continuous development of new wireless service provision technologies and uses for wireless radio spectrum has prompted spectrum management agencies and wireless service providers to consider flexible spectrum assignment mechanisms as a means for responding to a growing demand for radio spectrum in the near future.1 Currently, a large part of the usable spectrum is not used efficiently and has low average occupancy values.2 This is mainly due to the use of traditional spectrum allocation and assignment mechanisms that are focused on avoiding interference between users and on the type of use given to spectrum, rather than on the efficient utilization of this resource and the maximization of socio-economic benefits. Thus, the use of rigid spectrum management policies has been a contributor to the creation of an artificial spectrum scarcity that must be solved by new

Assistant Professor and Director of the Center for Convergence and Emerging Network Technologies (CCENT), School of Information Studies, Syracuse University. Federal Communications Commission, Promoting More Efficient Use of Spectrum through Dynamic Spectrum Use Technologies, ET Docket No. 10-237, Nov. 30, 2010, accessed Nov. 13, 2013, http://hraunfoss.fcc.gov/edocs_public/attachmatch/FCC-10-198A1.pdf; Federal Communications Commission, Promoting Efficient Use of Spectrum through Elimination of Barriers to the Development of Secondary Markets, WT Docket No. 00230, July 8, 2004, accessed Nov. 13, 2013, http://hraunfoss.fcc.gov/edocs_public/attachmatch/FCC-04-167A1.pdf; Junjik Bae, Eyal Beigman, Randall Berry, Michael L. Honig, Hongxia Shen, Rakesh Vohra, and Hang Zhou, “Spectrum Markets for Wireless Services,” paper presented at the 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (2008), accessed Nov. 13, 2013, http://www.ece.northwestern.edu/~rberry/Pubs/spectrum_markets.pdf. 2 Mark A. McHenry, “NSF Spectrum Occupancy Measurements Project Summary,” white paper, Shared Spectrum Company (2005). 1

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technical, economic, and regulatory frameworks, to improve spectrum use efficiency in order to support future wireless service provision environments.3 Radio spectrum is a highly regulated resource whose management is usually deferred to a government agency. The management of this resource encompasses all activities related to the allocation and assignment of spectrum along with the enforcement of related regulations. Currently, many spectrum management authorities have elaborated or are elaborating regulations in order to increase the use of market-based mechanisms for spectrum management, thus reducing their emphasis on traditional command and control methods in order to move towards wireless service provision environments that can achieve economically efficient spectrum allocation and assignment.4 The evolution of the regulatory regimes for future wireless service environments is tightly linked with the technical evolution of the capabilities of the infrastructure that supports them. As cognitive radio and software-defined radio technologies continue to evolve and gain acceptance as key technologies for future wireless service provision environments that rely on Dynamic Spectrum Access (DSA) methods, the industry will see new technical and business models that will make use of their capabilities.5 Although spectrum auctions have become a common technique for regulatory agencies to assign spectrum to new users, the spectrum requirements for current and future wireless services would be better served by a dynamic secondary spectrum market environment that allows economically-driven re-assignments of spectrum to be continuously executed. This article presents a set of techno-economic architectures for market-based spectrum management based on spectrum trading interactions, discusses some of the issues related to the implementation of these markets, and points to additional areas of research, standardization, and regulation development that are needed to evolve these markets. Spectrum trading markets are of growing interest to many spectrum management agencies. They are motivated by their desire to increase the use of market-based mechanisms for spectrum management to increase spectrum efficiency. These markets can be implemented with DSA technologies. However, the interactions in the market should take into account, among other things, the geographic reusability and non-perishable characteristics of spectrum, which make its trading different from trading traditional market commodities. The article is structured as follows: the second section explains the basic concepts and benefits of market-based spectrum management with an emphasis on spectrum trading markets, the third section discusses the technical and economic viability of these markets, and the final section discusses

3 Ibid.; Zhao Qing and Brian M. Sadler, “A Survey of Dynamic Spectrum Access: Signal Processing, Networking, and Regulatory Policy,” IEEE Signal Processing Magazine 24, no. 3 (May 2007): 79-89; Executive Office of the President, President’s Council of Advisors on Science and Technology, “Realizing the Full Potential of Government-Held Spectrum to Spur Economic Growth,” Report to the President, July 2012, accessed Nov. 13, 2013, http://www.whitehouse.gov/sites/default/files/microsites/ostp/pcast_spectrum_report_final_july_20_2012.pdf. 4 Federal Communications Commission, Promoting Efficient Use of Spectrum through Elimination of Barriers to the Development of Secondary Markets; Federal Communications Commission, Promoting More Efficient Use of Spectrum through Dynamic Spectrum Use Technologies. 5 Executive Office of the President, President’s Council of Advisors on Science and Technology.

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developments in regulation and standards that will impact market-based approaches to wireless service provision.

MARKET-BASED SPECTRUM MANAGEMENT Traditionally, radio spectrum has been “statically” allocated to wireless service providers (WSPs), with restrictions imposed on the technologies to be used and the services to be provided. However, the lack of flexibility in static spectrum allocation has led to inefficient spectrum utilization and an artificial spectrum scarcity.6 To remove the inefficiencies of traditional spectrum management methods, many spectrum management agencies are implementing the use of market-based mechanisms for spectrum management. 7 Through these mechanisms, spectrum assignments would mainly rely on license transfers or leases over a market designed to support these transactions.8 The growth in the use of wireless communication services, and the need to support innovation in wireless service provision, place increasing demands on radio spectrum resources, which makes the management of spectrum increasingly difficult for regulatory agencies. The traditional command and control model for managing spectrum makes it difficult for spectrum users (wireless service providers in most scenarios) to share or trade spectrum. This limits the efficiency in the use of a band of spectrum by impeding transactions that can place spectrum resources in the hands of those who value them and need them the most at a given moment in time.9 In order to address these issues, flexible spectrum assignment mechanisms have to be put in place to adjust to the evolving wireless landscape while still achieving the best usage of spectrum possible under economic or social welfare considerations and requirements from the public safety, scientific, and national security sectors.10 For economically-driven dynamic spectrum assignment to be optimally effective, a secondary market must exist that allows spectrum users to optimally choose between capital investment and spectrum use on a continuous basis, not just at the time of initial assignment.11 The notion of secondary markets Ibid.; Mark A. McHenry, Peter A. Tenhula, Dan McCloskey, Dennis A. Roberson, and Cynthia S. Hood, “Chicago Spectrum Occupancy Measurements & Analysis and a Long-Term Studies Proposal,” Proceedings of the First International Workshop on Technology and Policy for Accessing Spectrum (2006): Article No. 1. 7 Martin Cave and William Webb, “License to Interfere,” Communications Engineer (Dec. 2003/Jan. 2004): 42-46; Martin Cave and William Webb, “The Unfinished History of Usage Rights for Spectrum,” IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (2011): 41-46. 8 Carlos E. Caicedo and Martin B. H. Weiss, “The Viability of Spectrum Trading Markets,” IEEE Communications Magazine (Mar. 2011): 46-52. 9 Coleman Bazelon, “Licensed or Unlicensed: The Economic Considerations in Incremental Spectrum Allocations,” IEEE Communications Magazine (Mar. 2009): 110-116; Dennis Burgkhardt, Ivan Cosovic, Gunther Auer, and Friedrich K. Jondral, “Reducing the Probability of Network Overload by Spectrum Trading,” paper presented at the CCECE ‘09 Canadian Conference on Electrical and Computer Engineering (2009), accessed Nov. 14, 2013, http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5090155. 10 National Science Foundation, “Final Report of the Workshop on Enhancing Access to the Radio Spectrum,” report, Aug. 2010, accessed Nov. 13, 2013, http://www.nsf.gov/mps/ast/nsf_ears_workshop_2010_final_report.pdf. 11 Carlos E. Caicedo and Martin B. H. Weiss, “An Analysis of Market Structures and Implementation Architectures for Spectrum Trading Markets,” paper presented at the Telecommunications Policy Research Conference, Arlington, VA, Sept. 2008. 6

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is not new; it is the model under which the stock market works and can bring most of the same benefits to the management of spectrum.12 A secondary spectrum market would require considering many different operational factors at the policy, economic, and technical levels. In particular, the market should include mechanisms to prevent anticompetitive behavior, avoid burdening market operations with high transaction costs, promote spectrum use efficiency, and guarantee a sustainable market that can provide benefits to its participants.13 Market-based spectrum assignment mechanisms rely on license transfers or leases which can be established through many different market structures.14 In contrast, opportunistic spectrum access mechanisms rely on methods for adequate spectrum opportunity identification and spectrum access with or without consent from the primary user. The purpose of well-designed opportunistic access mechanisms is to provide sufficient benefits to secondary spectrum users while protecting spectrum licensees (primary users) from interference, with or without compensation from the secondary user to the primary.15 A spectrum market would allow efficient and flexible allocation of spectrum according to demand and create incentives for the development of new types of radio systems.16 In general, spectrum markets would promote a more competitive communications environment, lowering barriers of entry to service provision for new companies/enterprises and facilitating the introduction of new services.17 These markets would facilitate the appearance of non-traditional wireless service providers, some of which could be entities that offer wireless service in limited service areas on a non-permanent basis and with social or economic objectives not exclusively focused on the direct revenue obtained from providing wireless service. An example of this could be shopping mall administration entities creating an incentive for customers to go to their premises and shops by offering free calls and/or special discounts only sent to mobile phones present in the area of the mall.

12 John W. Mayo and Scott Wallsten, “Enabling Efficient Wireless Communications: The Role of Secondary Spectrum Markets,” Information Economics and Policy 22, no. 1 (2010): 61-72. 13 Cave and Webb, “The Unfinished History of Usage Rights for Spectrum;” Martin Cave, “Anti-Competitive Behaviour in Spectrum Markets: Analysis and Response,” Telecommunications Policy 34 (2010): 251-261; Martin Cave, Chris Doyle, and William Webb, Essentials of Modern Spectrum Management (Cambridge: Cambridge University Press, 2007); Carlos E. Caicedo and Martin B. H. Weiss, “Spectrum Trading: An Analysis of Implementation Issues,” IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (2007): 579-584; Ofcom, “Spectrum Trading Consultation,” white paper, Nov. 2003, accessed Nov. 14, 2013, http://www.ofcom.org.uk/consult/condocs/spec_trad/spectrum_trading/. 14 Carlos E. Caicedo and Martin B. H. Weiss, “On the Viability of Spectrum Trading Markets,” paper presented at the Telecommunications Policy Research Conference, Arlington, VA, Sept. 2009; Carlos E. Caicedo Bastidas, Technical Architectures and Economic Conditions for the Viability of Spectrum Trading Markets, doctoral dissertation, University of Pittsburgh (2009). 15 Qing and Sadler. 16 Juncheng Jia and Qian Zhang, “Bandwidth and Price Competitions of Wireless Service Providers in Two-Stage Spectrum Market,” paper presented at the IEEE International Conference on Communications, Beijing (2008); Randall Berry, Michael L. Honig, and Rakesh Vohr, “Spectrum Markets: Motivation, Challenges, and Implications,” IEEE Communications Magazine (Nov. 2010): 146-155; Bae et al. 17 Berry, Honig, and Vohr; Bae et al.

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Because of their benefits, regulatory policy efforts to facilitate spectrum markets are being implemented in several countries.18 However, these efforts still impose regulations that limit the types of trades allowed in the market and the use given to traded frequencies. Wireless service provision in the near future will require a well-integrated regulatory and market operation framework for spectrum markets to be able to flourish and support the dynamism of the wireless communications industry.

Spectrum Trading Spectrum trading (ST) is a market-based spectrum management mechanism in which buyers and sellers determine the assignments of spectrum and its uses; this way ST has the capability of addressing both the allocation and assignment aspects of spectrum use. In its simplest form, ST refers to the temporary or permanent selling of spectrum licenses (spectrum usage rights).19 Trading transactions are initiated voluntarily by a spectrum license holder who wants to sell some of his spectrum and once a buyer is found, and the financial transaction is completed, the new owner obtains the spectrum usage rights.20 Spectrum trading allows a more dynamic, competitive, and efficient wireless services market than is possible under the traditional regimes, in part because businesses have better knowledge than regulators about their spectrum requirements and valuations.21 Figure 1 below illustrates a spectrum trading scenario based on the use of a spectrum exchange. In this scenario, the exchange collects the offers to sell spectrum and the offers to buy spectrum (bids), determines the winning bid (through a continuous double-auction mechanism for example), and transfers the spectrum usage right from the selling license holder to the new owner of the right.22 Other spectrum trading scenarios can have the exchange acting as a band manager just allowing trades in the form of leases on the set of frequencies it manages. 23 In general, the rules and behaviors governing the market structure along with any regulatory policy limitations will influence the technical and economic benefits achievable in a market-based spectrum management environment.24 18 Mayo and Wallsten; Ofcom, Notice of Proposals to Make 900 MHz, 1800 MHz & 2100 MHz Public Wireless Network Licenses Tradable, consultation, Feb. 2, 2011, accessed Nov. 15, 2013, http://stakeholders.ofcom.org.uk/binaries/consultations/trading-900-1800-2100/summary/900-1800-2100.pdf; Rajen Akalu, “Why There Have Been So Few Spectrum Trades in the UK: Lessons for Europe,” Info 12, no. 1 (2009): 10-17; William Webb, “Sell, Sell, Sell!” Communications Engineer (Feb./Mar. 2005): 32-35; Michael J. Marcus, “Europe Contemplates Cognitive Radio Policies,” IEEE Wireless Communications (Feb. 2010): 7; Patrick Xavier and Dimitri Ypsilanti, “Policy Issues in Spectrum Trading,” Info 8, no. 2 (2006): 34-61; S. Olafsson, B. Glover, and M. Nekovee, “Future Management of Spectrum,” BT Technology Journal 25, no. 2 (Apr. 2007): 52-63. 19 Olafsson, Glover, and Nekovee. 20 J. Scott Marcus, Lorenz Nett, and Ulrich Stumpf, “Towards More Flexible Spectrum Regulation,” paper presented at New Initiatives Workshop: The Regulatory Environment for Future Mobile Multimedia Services, International Telecommunication Union, Mainz, Germany, June 2006. 21 Carlos E. Caicedo and Martin B. H. Weiss, “A Spectrum Trading Architecture for WiMAX,” paper presented at the Telecommunications Policy Research Conference, Arlington, VA, Sept. 2007; Caicedo and Weiss, “On the Viability of Spectrum Trading Markets.” 22 Ruben Lee, What is an Exchange?: The Automation, Management, and Regulation of Financial Markets (New York: Oxford University Press, 1998), xvii; Maureen O’Hara, Market Microstructure Theory (Cambridge, MA: Blackwell Publishers, 1995); Larry Harris, Trading & Exchanges: Market Microstructure for Practitioners (New York: Oxford University Press, 2003); Caicedo and Weiss, “Spectrum Trading: An Analysis of Implementation Issues.” 23 Caicedo Bastidas. 24 Caicedo and Weiss, “The Viability of Spectrum Trading Markets.”

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Regulator

of Se tra ll da no bl tic e s e pe ct

Po st in gs

g in er th ga ids n b io f at n o rm i o fo iss In e bm ic u Pr S

ru m

Spectrum Exchange

Trading finalization

Entity in need of spectrum (buyer)

Spectrum license holder (seller)

Figure 1

Spectrum as a traded commodity is different from other commodities given its geographical specificity (which allows for frequency reuse), its non-storable characteristics, and the way that interference can diminish its value if not controlled properly. In general, the objective of spectrum trading and any market-based spectrum assignment mechanism is to maximize the revenue of the entities participating in a trade while enhancing the delivery of wireless services through the acquisition of spectrum resources.25 The realization of these benefits requires a well-designed regulatory framework and a trading infrastructure using technical architectures that can satisfy social welfare goals and support the widest range of trading interactions possible at an acceptable level of economic efficiency.26

The Structure of Spectrum Trading Markets To understand the organization of, and interactions in, a spectrum trading market we need to know what entities participate in such a market. ST markets can be implemented as over-the-counter (OTC) markets or as exchange-based markets.27 We will focus on the exchange-based case as it offers a richer set of market behaviors. A description of the entities that participate in exchange-based ST markets and some of their functions is provided in Table 1 below.

25 Dusit Niyato and Ekram Hossain, “Spectrum Trading in Cognitive Radio Networks: A Market-Equilibrium-Based Approach,” IEEE Wireless Communications (Dec. 2008): 71-80. 26 Caicedo and Weiss, “The Viability of Spectrum Trading Markets;” Caicedo Bastidas. 27 Caicedo and Weiss, “The Viability of Spectrum Trading Markets;” Caicedo and Weiss, “An Analysis of Market Structures and Implementation Architectures for Spectrum Trading Markets.”

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Table 1: Spectrum Trading Market Entities Entity Spectrum license holder (SLH) Spectrum license requestor (SLR) Spectrum exchange Spectrum regulator Market maker

Description Entity that owns a spectrum license that has been acquired either through an auction, spectrum trading, or direct assignment by a regulatory agency and that offers its license for trading to obtain financial compensation. Entity that submits bids for spectrum licenses to the ST market with the intent of acquiring the license. Spectrum license requestors obtain spectrum for their own use or for speculation. An entity that provides and maintains a marketplace or facilities for bringing together buyers and sellers of spectrum, in which spectrum trading transactions can take place. It also publicizes prices and anonymizes trading entities. Government entity that oversees the ST market and defines the regulations for its operation. Entity that facilitates trading. It does not provide services with its inventory. It obtains revenue through the spread between ask and bid prices for spectrum, and holds a spectrum inventory for negotiating and speculating.

It is worth noting that the SLH and SLR entities would typically be wireless service providers, but as spectrum markets lower the barriers of entry to acquire spectrum, the SLHs or SLRs can be business entities that acquire and sell spectrum for private purposes and short time scales (e.g. a concert organizer, a shopping mall launching an event, a neighborhood association hosting a festival, etc.). However, the regulatory framework for an ST market and/or the market participation criteria defined by the spectrum exchange can limit the entities that can participate in the market, based on creditworthiness, technical competency, business attributes, etc. These limitations should be carefully considered in the attempt to block misuse of spectrum resources while still promoting the rise of new businesses and uses for spectrum. Due to its role, the spectrum exchange deserves further discussion. In general, an exchange denotes the idea of a central facility where buyers and sellers can transact. Previous work by the current author identified that the long-term behavior of exchange-based spectrum markets was mainly affected by the technical structure and market operation procedures (functionality) of the exchange.28 From a technical structure standpoint, a spectrum exchange acts as a pooling point (POOL) if its facilities house the communications equipment that enables the delivery of wireless services through spectrum acquired by a buyer in the exchange along with network interconnection capabilities. In contrast, a non-pooling point exchange (NOPOOL) only delivers the authorization for use of spectrum to the buyer that is participating in a spectrum trade. The new owner of spectrum can then configure its wireless transmission/reception devices to make use of the acquired spectrum. From a market functionality perspective, a spectrum exchange can be a band manager (BM) for a given segment of spectrum over a region or have no band manager functionality (NOBM). In scenarios for which the exchange operates as a BM, the entities that need spectrum will send a request for spectrum to the exchange that, if possible, will assign spectrum to the requesting entity in the form 28

Caicedo Bastidas.

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of a timed lease within the band managed by the exchange. BM exchanges can manage the unused spectrum held by a commercial or government entity and establish leases of spectrum with entities that need spectrum in order to generate revenue for the owner of the band and increase the efficiency in the use of spectrum. An example scenario where several wireless service providers bid for spectrum managed by a band manager spectrum exchange is shown in Figure 2 below.

Figure 2

A NOBM exchange will only facilitate the trading of spectrum units (channels or sub-carriers, etc.) among entities in the market without holding any spectrum inventory itself. The traded units will not necessarily be located in a contiguous band of spectrum since the entire spectrum it will handle for trading will come from market participants that use the exchange and make bids and offers for spectrum. In either case, the exchange makes spectrum assignment decisions based on the valuations of spectrum units presented to it by the participants in the market, current market activity (demand) and the objectives of the policies governing the technical and economic operation of the exchange. The proposed spectrum exchange classification generates four types of spectrum exchanges that can be used to implement an ST market. Their characteristics are listed in Table 2 below.29

29 Carlos E. Caicedo Bastidas, Garret Vanhoy, Haris I. Volos, and Tamal Bose, “An Initial Approach Towards Quality of Service Based Spectrum Trading,” paper presented at the IEEE Aerospace Conference, Big Sky, MT, Mar. 2013; Caicedo and Weiss, “The Viability of Spectrum Trading Markets.”

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Table 2: Spectrum Exchange Classification Exchange Type Type I (POOL_BM)

Type II (POOL_NOBM)

Type III (NOPOOL_BM)

Type IV (NOPOOL_NOBM)

Characteristics Pooling point + band manager functionality Use of traded spectrum is enabled and configured through equipment/infrastructure owned by the exchange. All tradable spectrum is held by the exchange. All tradable spectrum returns to or is given by the exchange. Pooling point only, no band manager functionality Use of traded spectrum is enabled and configured through equipment/infrastructure owned by the exchange. Different segments of spectrum can be activated and configured through the equipment/infrastructure of the exchange. No spectrum inventory is held by the exchange. Non-pooling point + band manager functionality All tradable spectrum is held by the exchange. All tradable spectrum returns to or is given by the exchange. Exchange grants authorizations for use of spectrum (no equipment configuration is done by the exchange). Non-pooling point, no band manager functionality Exchange grants authorizations for use of spectrum (no equipment configuration is done by the exchange). No spectrum inventory is held by the exchange.

TECHNO-ECONOMIC VIABILITY OF SPECTRUM TRADING MARKETS As mentioned previously, spectrum as a traded commodity is different from other commodities given its geographical specificity, its non-storable characteristics, and the way that interference can diminish its value if not controlled properly. Thus, the determination of viability of spectrum trading markets is based on the interplay between several aspects of market behavior and technical market structure, among which are:

Market Sustainability The sustainability of an ST market is characterized by the amount of trading activity and the mechanisms to efficiently handle exceptional market behavior situations such as trading periods with no buyers, periods with no sellers, major spectrum unit price changes, etc. Spectrum Exchange Operation Parameters Spectrum exchange type: As listed in Table 2 above, each spectrum exchange type has different technical structures and functional procedures to manage spectrum resources. Trade matching policy: The logic for matching requests to buy and requests to sell spectrum will have an impact on the willingness of business entities (e.g. wireless service providers) to participate in the market. Among the items to be considered are: mechanisms used to match

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trades (e.g. continuous double actions or other), type of trade supported (lease or permanent transfer), and support for interference mitigation. Trade matching fees: Any fees claimed by the exchange for enabling spectrum trading will impose a cost on transactions carried out in the market. Time resolution: The closer the spectrum exchange is to being able to make spectrum trades in real time, the more attractive the use of the ST market will be for WSPs that can use the market to solve short term spectrum/capacity shortages and to get spectrum at the best price when needed. Quality guarantees: Supporting trades that can comply with quality characteristics (e.g. interference level present in a spectrum unit) is important for determining which services can be supported on a specific spectrum unit, but it implies that the exchange must have an infrastructure that allows it to determine the quality of spectrum units. Wireless Service Area Parameters Amount of spectrum available for trading: The amount of spectrum units available for trading over a wireless service area can change over time and determine the variability of the spectrum units’ price swings. Number of spectrum user entities participating in the market: The number of potential spectrum user entities competing for spectrum resources in the market will impact the amount of trading activity present in it. Number of base stations in service area: WSPs that participate in the market will potentially use the spectrum they acquire in the ST market to provide services via their transmission equipment (base stations). The active use of each spectrum unit on the transmission/reception equipment of the WSP will affect the interference levels and quality of channels on neighboring service areas in which the exchange or other spectrum user entities may want to reuse a given spectrum unit. Given the large number of parameters (technical and economic) that affect spectrum trading markets, the study of the viability of these markets and the behaviors of their participants can be difficult to analyze with conventional statistical and analytical tools.30 Thus, these markets require the use of modeling techniques that can adequately handle the interactions between their technical and economic parameters. This study uses Agent-Based Computational Economics (ACE) theory in combination with concepts from wireless systems engineering for the analysis.31 ST market viability can be determined mainly by market sustainability and liquidity factors.32 Market sustainability can be characterized by the amount of trading activity and severity of market behavior Caicedo and Weiss, “The Viability of Spectrum Trading Markets.” Agent-Based Computational Economics is “the computational study of economic processes modeled as dynamic systems of interacting agents.” See Leigh Tesfatsion, “Agent-Based Computational Economics: A Constructive Approach to Economic Theory,” in Handbook of Computational Economics, vol. 2, ed. Leigh Tesfatsion and Kenneth L. Judd (Oxford, UK: Elsevier, 2006), 831-880. 32 Caicedo and Weiss, “The Viability of Spectrum Trading Markets.” 30 31

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anomalies (trading periods with no buyers, no sellers, etc.) present in a spectrum trading scenario. Market liquidity characteristics can be characterized by economic scenario indicators such as the bidask spread.33 The ST market modeling work of the present author used this framework for viability determination using ACE tools. 34 The scenarios modeled via ACE varied in terms of spectrum exchange architecture (BM vs. NOBM), number of WSPs, amount of spectrum units available for trading, and traffic demand patterns. The results obtained indicated that if the amount of spectrum available for trading is near the point where the participants in the market are able, on average, to satisfy their spectrum demands, the markets would be very stable irrespective of the exchange operation type. However, NOBM scenarios were more tolerant to having up to 50% oversupply or undersupply of the spectrum needed to satisfy general average requirements than BM exchange-based markets. Also, the results indicated that markets with more than six active participants would be viable if an adequate amount of spectrum was available for trading, as mentioned previously. The scenarios analyzed assumed that the spectrum requests and offers in the market were mainly characterized by the number of spectrum units (channels, sub-carriers, etc.) that need to be sold or bought, but not on their quality characteristics.

Dealing with Variable Spectrum Characteristics In a wireless service area, all segments of spectrum are not the same due to noise, fading, and other phenomena that can affect a range of frequencies at a given moment in time and location in space. In particular, interference is the major limiting factor in the performance of wireless systems that employ mechanisms for frequency reuse.35 The value of a unit of spectrum (i.e. channel, sub-carrier, etc.) depends on the level of interference present in it, and it will limit the usability of that unit for the purposes of providing a wireless service under the technical limits of the transmitter and/or receiver equipment that will make use of that unit within a wireless service area. To support spectrum trading markets in which quality constraints on the spectrum units can be met and specified as part of a trade, a spectrum sensor network infrastructure is required. This infrastructure would avoid possible errors in the classification of the quality of each spectrum unit to which other sensing approaches are susceptible.36 Sensor measurements can be stored by the exchange for historical analysis of spectrum demand and quality variation. The storage of these measurements would also help in the enforcement of spectrum use by assisting in the detection of anomalies in spectrum use. An example scenario of a quality-aware spectrum trading infrastructure is depicted in Figure 3 below.

O’Hara. Caicedo and Weiss, “The Viability of Spectrum Trading Markets.” 35 Theodore S. Rappaport, Wireless Communications: Principles and Practice (Upper Saddle River, NJ: Prentice Hall, 1996). 36 Martin B.H. Weiss, Simon Delaere, and William H. Lehr, “Sensing as a Service: An Exploration into Practical Implementations of DSA,” IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (2010): 1-8; Caicedo Bastidas, Yanhoy, Volos, and Bose. 33 34

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Figure 3

In addition to the viability parameters mentioned previously for non-quality-aware ST environments, the viability of markets in which quality constraints must be met would also depend on the technical and economic (cost) characteristics of the sensor infrastructure required to provide the measurements of channel quality at a level of confidence expected by the market participants. In particular, the number of spectrum sensors needed to provide the interference level measurements at a degree of confidence that the exchange can use to make its spectrum assignment decisions, the costs of the spectrum sensor infrastructure, and the levels of RF interference that can be tolerated over the wireless service area to enable trades will all be factors that impact the viability of the market.

REGULATORY AND STANDARDIZATION TRENDS FOR SPECTRUM MARKETS For secondary spectrum markets to flourish, such as those based on spectrum trading, an adequate regulatory framework must exist to allow the market to function and perform as efficiently as possible while complying with economic, technical, and social goals. In general, the spectrum management authorities that are implementing market-based spectrum management approaches are structuring new regulatory frameworks around certain guidelines and principles such as: (a) eliminating barriers to the development of secondary markets for spectrum; (b) eliminating unnecessary regulations and administrative requirements for spectrum transfers between business entities; (c) adoption of rules and processes to facilitate transferability of spectrum usage rights; and (d) definition of protection mechanisms for the adequate use of spectrum resources acquired by a business entity. However, from a technical point of view, the full exploitation of market-based spectrum management mechanisms requires the use of dynamic spectrum access technology in as many elements of the wireless service provision infrastructure as possible. Given the wide range of communication scenarios in which there may be conflicting goals for the use of spectrum (e.g. public safety vs. profit-based

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services), future wireless service provision environments with dynamic spectrum access capabilities will be need to be based on radio devices that can make use of and process spectrum access policies to facilitate and control the dynamic assignment of spectrum resources. Standardization groups such as the IEEE Dynamic Spectrum Access Networks Standardization Committee (DySPAN-SC) 1900.5 working group are currently working to develop a policy description language and system architecture that can be used in scenarios for which interoperability and coordination among devices from different vendors using dynamic spectrum access is required, specifically to avoid interference between spectrum users. Policy mediated spectrum access would allow for very dynamic spectrum use in which socially conscious (government-based) considerations for the use of spectrum – such as having it available for public safety use, national security situations, etc. – can be supported along with commercial uses of spectrum resources more focused on optimizing service coverage, optimizing service revenue generation, providing broadband services, and lowering the costs of service provision.

CONCLUSION The growth and importance of wireless services has prompted spectrum management authorities to evolve new models and mechanisms for managing spectrum resources. Market-based models have been incorporated by many regulators worldwide with varying degrees of flexibility in the allowance of spectrum trading interactions. These markets will be able to handle different technical limits for each trade as DSA technology evolves. Given the large number of parameters (technical and economic) that affect spectrum markets, the study of the viability of these markets and the behaviors of their participants still deserves further research and should incorporate the effects of regulatory frameworks in the evolution of the specific implementation of a market. In general, the use of marketbased methods for spectrum management should eliminate the artificial spectrum scarcity created by legacy regulatory frameworks but will require closer and interdisciplinary interactions between the wireless communications engineering community, regulators, policymakers, and economists in order to drive the development of the necessary innovations, regulations, technical standards, and market structures that lead to viable future wireless service provision environments.

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