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Issue No.12 - Dec. (2012 vol.11)
pp: 2020-2032
Alexander W. Min , Intel Labs, Hillsboro
Xinyu Zhang , The University of Michigan, Ann Arbor
Jaehyuk Choi , Kyungwon University, Seongnam
Kang G. Shin , The University of Michigan, Ann Arbor
The dynamic spectrum market (DSM) is a key economic vehicle for realizing the opportunistic spectrum access that will mitigate the anticipated spectrum-scarcity problem. DSM allows legacy spectrum owners to lease their channels to unlicensed spectrum consumers (or secondary users) in order to increase their revenue and improve spectrum utilization. In DSM, determining the optimal spectrum leasing price is an important yet challenging problem that requires a comprehensive understanding of market participants' interests and interactions. In this paper, we study spectrum pricing competition in a duopoly DSM, where two wireless service providers (WSPs) lease spectrum access rights, and secondary users (SUs) purchase the spectrum use to maximize their utility. We identify two essential, but previously overlooked, properties of DSM: 1) heterogeneous spectrum resources at WSPs and 2) spectrum sharing among SUs. We demonstrate the impact of spectrum heterogeneity via an in-depth measurement study using a software-defined radio (SDR) testbed. We then study the impacts of spectrum heterogeneity on WSPs' optimal pricing and SUs' WSP selection strategies using a systematic three-step approach. First, we study how spectrum sharing among SUs subscribed to the same WSP affects the SUs' achievable utility. Then, we derive the SUs' optimal WSP selection strategy that maximizes their payoff, given the heterogeneous spectrum propagation characteristics and prices. We analyze how individual SU preferences affect market evolution and prove the market convergence to a mean-field limit, even though SUs make local decisions. Finally, given the market evolution, we formulate the WSPs' pricing strategies in a duopoly DSM as a noncooperative game and identify its Nash equilibrium points. We find that the equilibrium price and its uniqueness depend on the SUs' geographical density and spectrum propagation characteristics. Our analytical framework reveals the impact of spectrum heterogeneity in a real-world DSM, and can be used as a guideline for the WSPs' pricing strategies.
Pricing, Interference, Radio spectrum management, Signal to noise ratio, Receivers, Frequency measurement, Wireless communication, spectrum pricing, Cognitive radios, dynamic spectrum market, game theory, spectrum heterogeneity
Alexander W. Min, Xinyu Zhang, Jaehyuk Choi, Kang G. Shin, "Exploiting Spectrum Heterogeneity in Dynamic Spectrum Market", IEEE Transactions on Mobile Computing, vol.11, no. 12, pp. 2020-2032, Dec. 2012, doi:10.1109/TMC.2011.229
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