Improving Liquidity in Secondary Spectrum Markets: Virtualizing Spectrum for Fungibility

Pricing mechanisms in the form of auctions have been the main method for spectrum assignment in the United States for over 20 years. The spectrum auctions carried out by the federal communications commission constitute a primary market for spectrum and have been affected by lack of flexibility which has resulted in inefficiencies in spectrum assignment, especially in environments where spectrum is considered scarce. In recent years, we have observed significant efforts to increase efficiency in spectrum assignment and use. Among those efforts is the design and adoption of secondary markets. Secondary markets have the potential to address inefficiencies arising in primary markets over time or those that occur through features of auction mechanisms by enabling spectrum to be assigned to users who value it the most. Furthermore, liquid secondary markets have enabled the explicit management of risk in other markets, such as agriculture and commodities, through futures and options trading. In this paper, we advance the study of liquidity in secondary markets that was begun in our previous work. We explore: 1) the reasons that may have hindered the emergence of liquid secondary markets for radio spectrum and 2) what we might change to promote secondary markets. With these objectives in mind, we study various configurations for the design of secondary markets, which account for the physical constraints inherent to electromagnetic spectrum. In addition, we study technical alternatives that would permit us to develop an appropriate, tradeable, and spectrum-related commodity. The results of our analysis show that lack of fungibility has an adverse impact on secondary market liquidity. To address this outcome, we propose virtualization of spectrum resources into fungible chunks and show that this improves market liquidity by yielding viable market outcomes in all the scenarios we tested.

[1]  C E Caicedo,et al.  The viability of spectrum trading markets , 2011, IEEE Communications Magazine.

[2]  Martin B. H. Weiss,et al.  Enforcement in Dynamic Spectrum Access Systems , 2012 .

[3]  Sumit Roy,et al.  Market Mechanisms for Dynamic Spectrum Access (DSA) , 2018, IEEE Transactions on Wireless Communications.

[4]  Irene Macaluso,et al.  Exclusive sharing & virtualization of the cellular network , 2011, 2011 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[5]  A. D. Vany,et al.  A Property System for Market Allocation of the Electromagnetic Spectrum: A Legal-Economic-Engineering Study , 1969 .

[6]  Linda Doyle,et al.  When is electromagnetic spectrum fungible? , 2012, 2012 IEEE International Symposium on Dynamic Spectrum Access Networks.

[7]  Haitao Zheng,et al.  A General Framework for Wireless Spectrum Auctions , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[8]  Dusit Niyato,et al.  Competitive Pricing for Spectrum Sharing in Cognitive Radio Networks: Dynamic Game, Inefficiency of Nash Equilibrium, and Collusion , 2008, IEEE Journal on Selected Areas in Communications.

[9]  Benoit Morel,et al.  Risk and decision analysis of dynamic spectrum access , 2017 .

[10]  William Rand,et al.  An Introduction to Agent-Based Modeling: Modeling Natural, Social, and Engineered Complex Systems with NetLogo , 2015 .

[11]  M. Marcus,et al.  Real time spectrum markets and interruptible spectrum: new concepts of spectrum use enabled by cognitive radio , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[12]  P. Cramton,et al.  Open access wireless markets , 2017 .

[13]  Sassan Ahmadi LTE-Advanced: A Practical Systems Approach to Understanding 3GPP LTE Releases 10 and 11 Radio Access Technologies , 2013 .

[14]  H. Tan,et al.  WHO GETS IT AND WHY , 2007 .

[15]  Subhash Suri,et al.  Towards real-time dynamic spectrum auctions , 2008, Comput. Networks.

[16]  Zhu Han,et al.  Dynamics of Multiple-Seller and Multiple-Buyer Spectrum Trading in Cognitive Radio Networks: A Game-Theoretic Modeling Approach , 2009, IEEE Transactions on Mobile Computing.

[17]  Martin B. H. Weiss,et al.  Socio-technical considerations for Spectrum Access System (SAS) design , 2015, 2015 IEEE International Symposium on Dynamic Spectrum Access Networks (DySPAN).

[18]  M. Weiss,et al.  How Do Limitations in Spectrum Fungibility Impact Spectrum Trading , 2013 .

[19]  Jianwei Huang,et al.  Investment and Pricing with Spectrum Uncertainty: A Cognitive Operator's Perspective , 2009, IEEE Transactions on Mobile Computing.

[20]  Jon M. Peha,et al.  Real-Time Secondary Markets for Spectrum , 2003 .

[21]  Andreas Timm-Giel,et al.  LTE mobile network virtualization , 2011, Mob. Networks Appl..

[22]  M. D. McGinnis,et al.  An Introduction to IAD and the Language of the Ostrom Workshop: A Simple Guide to a Complex Framework for the Analysis of Institutions and Their Development , 2011 .

[23]  Shamik Sengupta,et al.  Designing Auction Mechanisms for Dynamic Spectrum Access , 2008, Mob. Networks Appl..

[24]  I. Baldine,et al.  Network Virtualization: Technologies, Perspectives, and Frontiers , 2013, Journal of Lightwave Technology.

[25]  C. Enrique,et al.  TECHNICAL ARCHITECTURES AND ECONOMIC CONDITIONS FOR VIABLE SPECTRUM TRADING MARKETS , 2009 .

[26]  Yuguang Fang,et al.  Data and Spectrum Trading Policies in a Trusted Cognitive Dynamic Network Architecture , 2018, IEEE/ACM Transactions on Networking.

[27]  Marcela Gomez,et al.  Secondary spectrum markets: from "naked" spectrum to virtualized commodities , 2017 .

[28]  John W. Mayo,et al.  Enabling efficient wireless communications: The role of secondary spectrum markets , 2010, Inf. Econ. Policy.

[29]  Ronald H. Coase,et al.  The Federal Communications Commission , 1959, The Journal of Law and Economics.

[30]  Linda Doyle,et al.  Cellular clouds , 2013 .

[31]  Dusit Niyato,et al.  Spectrum trading in cognitive radio networks: A market-equilibrium-based approach , 2008, IEEE Wirel. Commun..

[32]  Xia Zhou,et al.  TRUST: A General Framework for Truthful Double Spectrum Auctions , 2009, IEEE INFOCOM 2009.

[33]  Luiz A. DaSilva,et al.  Spectrum Without Bounds, Networks Without Borders , 2014, Proceedings of the IEEE.

[34]  Martin B. H. Weiss,et al.  Trading Wireless Capacity Through Spectrum Virtualization Using LTE-A , 2014 .

[35]  J. Perloff Microeconomics: Theory and Applications With Calculus , 2007 .

[36]  E. Ostrom Background on the Institutional Analysis and Development Framework , 2011 .

[37]  Zongpeng Li,et al.  Strategyproof auctions for balancing social welfare and fairness in secondary spectrum markets , 2011, 2011 Proceedings IEEE INFOCOM.

[38]  Linda Doyle,et al.  Matching Markets for Spectrum Sharing , 2017 .

[39]  Liu Cui,et al.  Dimensions of cooperative spectrum sharing: Rights and enforcement , 2014, 2014 IEEE International Symposium on Dynamic Spectrum Access Networks (DYSPAN).

[40]  Xia Zhou,et al.  eBay in the Sky: strategy-proof wireless spectrum auctions , 2008, MobiCom '08.

[41]  Robert J. Matheson,et al.  The Technical Basis for Spectrum Rights: Policies to Enhance Market Efficiency , 2011 .

[42]  Kang G. Shin,et al.  Exploiting Spectrum Heterogeneity in Dynamic Spectrum Market , 2012, IEEE Transactions on Mobile Computing.