Duopoly Competition in Dynamic Spectrum Leasing and Pricing

This paper presents a comprehensive analytical study of two competitive secondary operators' investment (i.e., spectrum leasing) and pricing strategies, taking into account operators' heterogeneity in leasing costs and users' heterogeneity in transmission power and channel conditions. We model the interactions between operators and users as a three-stage dynamic game, where operators simultaneously make spectrum leasing decisions in Stage I, and pricing decisions in Stage II, and then users make purchase decisions in Stage III. Using backward induction, we are able to completely characterize the dynamic game's equilibria. We show that both operators' investment and pricing equilibrium decisions process interesting threshold properties. For example, when the two operators' leasing costs are close, both operators will lease positive spectrum. Otherwise, one operator will choose not to lease and the other operator becomes the monopolist. For pricing, a positive pure strategy equilibrium exists only when the total spectrum investment of both operators is less than a threshold. Moreover, two operators always choose the same equilibrium price despite their heterogeneity in leasing costs. Each user fairly achieves the same service quality in terms of signal-to-noise ratio (SNR) at the equilibrium, and the obtained predictable payoff is linear in its transmission power and channel gain. We also compare the duopoly equilibrium with the coordinated case where two operators cooperate to maximize their total profit. We show that the maximum loss of total profit due to operators' competition is no larger than 25 percent. The users, however, always benefit from operators' competition in terms of their payoffs. We show that most of these insights are robust in the general SNR regime.

[1]  Patrick Maillé,et al.  Analysis of Price Competition in a Slotted Resource Allocation Game , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[2]  E. Maskin,et al.  The Existence of Equilibrium in Discontinuous Economic Games, I: Theory , 1986 .

[3]  Shamik Sengupta,et al.  An economic framework for dynamic spectrum access and service pricing , 2009, IEEE/ACM Trans. Netw..

[4]  Dilip Abreu On the Theory of Infinitely Repeated Games with Discounting , 1988 .

[5]  Daniël Wedema Games And Information An Introduction To Game Theory 3rd Edition , 2011 .

[6]  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.

[7]  Panganamala Ramana Kumar,et al.  RHEINISCH-WESTFÄLISCHE TECHNISCHE HOCHSCHULE AACHEN , 2001 .

[8]  Jianwei Huang,et al.  Competition with Dynamic Spectrum Leasing , 2010, 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN).

[9]  Xinbing Wang,et al.  Spectrum Sharing in Cognitive Radio Networks—An Auction-Based Approach , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[10]  Brian M. Sadler,et al.  Dynamic Spectrum Access: Signal Processing, Networking, and Regulatory Policy , 2006, ArXiv.

[11]  N. Mandayam,et al.  Demand responsive pricing and competitive spectrum allocation via a spectrum server , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[12]  Rajeev Agrawal,et al.  Joint scheduling and resource allocation in uplink OFDM systems for broadband wireless access networks , 2009, IEEE Journal on Selected Areas in Communications.

[13]  Sudharman K. Jayaweera,et al.  Dynamic spectrum leasing in cognitive radio networks via primary-secondary user power control games , 2009, IEEE Transactions on Wireless Communications.

[14]  Shuqin Li,et al.  Revenue Maximization for Communication Networks with Usage-Based Pricing , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[15]  Michael L. Honig,et al.  Sequential Bandwidth and Power Auctions for Distributed Spectrum Sharing , 2008, IEEE Journal on Selected Areas in Communications.

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

[17]  Noga Alon,et al.  A Fast and Simple Randomized Parallel Algorithm for the Maximal Independent Set Problem , 1985, J. Algorithms.

[18]  Jianwei Huang,et al.  Competition of wireless providers for atomic users: Equilibrium and social optimality , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).

[19]  D. Koller,et al.  Finding mixed strategies with small supports in extensive form games , 1996 .

[20]  Robin Mason,et al.  Internet service classes under competition , 2000, IEEE Journal on Selected Areas in Communications.

[21]  John M. Chapin,et al.  Time-limited leases in radio systems [Topics in Radio Communications] , 2007, IEEE Communications Magazine.

[22]  Rajarathnam Chandramouli,et al.  Price dynamics in competitive agile spectrum access markets , 2007, IEEE Journal on Selected Areas in Communications.

[23]  Hüseyin Arslan,et al.  Sidelobe suppression in OFDM-based spectrum sharing systems using adaptive symbol transition , 2008, IEEE Communications Letters.

[24]  Jianwei Huang,et al.  Cognitive Mobile Virtual Network Operator: Investment and Pricing with Supply Uncertainty , 2009, 2010 Proceedings IEEE INFOCOM.

[25]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.

[26]  Rajeev Agrawal,et al.  Downlink scheduling and resource allocation for OFDM systems , 2009, IEEE Transactions on Wireless Communications.

[27]  Zhu Han,et al.  Dynamic spectrum access in IEEE 802.22- based cognitive wireless networks: a game theoretic model for competitive spectrum bidding and pricing , 2009, IEEE Wireless Communications.

[28]  Alexander Schrijver,et al.  Theory of linear and integer programming , 1986, Wiley-Interscience series in discrete mathematics and optimization.

[29]  Michael L. Honig,et al.  Auction-Based Spectrum Sharing , 2006, Mob. Networks Appl..

[30]  R. Srikant,et al.  Economics of Network Pricing With Multiple ISPs , 2006, IEEE/ACM Transactions on Networking.

[31]  Michael Luby,et al.  A simple parallel algorithm for the maximal independent set problem , 1985, STOC '85.

[32]  William Lehr,et al.  Time-Limited Leases in Radio Systems , 2007 .

[33]  Ingo Wegener,et al.  Evolutionary Algorithms and the Maximum Matching Problem , 2003, STACS.

[34]  Frank Kelly,et al.  Charging and rate control for elastic traffic , 1997, Eur. Trans. Telecommun..

[35]  Costas Courcoubetis,et al.  Pricing Communication Networks , 2003 .

[36]  XiaoHua Xu,et al.  TODA: Truthful Online Double Auction for Spectrum Allocation in Wireless Networks , 2010, 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN).

[37]  Qian Zhang,et al.  Competitions and dynamics of duopoly wireless service providers in dynamic spectrum market , 2008, MobiHoc '08.

[38]  Umberto Spagnolini,et al.  Spectrum Leasing to Cooperating Secondary Ad Hoc Networks , 2008, IEEE Journal on Selected Areas in Communications.

[39]  Saswati Sarkar,et al.  Spectrum pricing games with bandwidth uncertainty and spatial reuse in cognitive radio networks , 2010, MobiHoc '10.

[40]  M. Chatterjee,et al.  An Economic Framework for Dynamic Spectrum Access and Service Pricing , 2009, IEEE/ACM Transactions on Networking.