Optimal Pricing Effect on Equilibrium Behaviors of Delay-Sensitive Users in Cognitive Radio Networks

This paper studies price-based spectrum access control in cognitive radio networks, which characterizes network operators' service provisions to delay-sensitive secondary users (SUs) via pricing strategies. Based on the two paradigms of shared-use and exclusive-use dynamic spectrum access (DSA), we examine three network scenarios corresponding to three types of secondary markets. In the first monopoly market with one operator using opportunistic shared-use DSA, we study the operator's pricing effect on the equilibrium behaviors of self-optimizing SUs in a queueing system. We provide a queueing delay analysis with the general distributions of the SU service time and PU traffic using the renewal theory. In terms of SUs, we show that there exists a unique Nash equilibrium in a non-cooperative game where SUs are players employing individual optimal strategies. We also provide a sufficient condition and iteraIntive algorithms for equilibrium convergence. In terms of operators, two pricing mechanisms are proposed with different goals: revenue maximization and social welfare maximization. In the second monopoly market, an operator exploiting exclusive-use DSA has many channels that will be allocated separately to each entering SU. We also analyze the pricing effect on the equilibrium behaviors of the SUs and the revenue-optimal and socially-optimal pricing strategies of the operator in this market. In the third duopoly market, we study a price competition between two operators employing shared-use and exclusive-use DSA, respectively, as a two-stage Stackelberg game. Using a backward induction method, we show that there exists a unique equilibrium for this game and investigate the equilibrium convergence.

[1]  Choong Seon Hong,et al.  Finding an Individual Optimal Threshold of Queue Length in Hybrid Overlay/Underlay Spectrum Access in Cognitive Radio Networks , 2012, IEICE Trans. Commun..

[2]  Refael Hassin,et al.  To Queue or Not to Queue: Equilibrium Behavior in Queueing Systems , 2002 .

[3]  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.

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

[5]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[6]  M.M. Buddhikot,et al.  Understanding Dynamic Spectrum Access: Models,Taxonomy and Challenges , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[7]  Ekram Hossain,et al.  Dynamic Spectrum Access and Management in Cognitive Radio Networks: Introduction , 2009 .

[8]  D. K. Hildebrand,et al.  Congestion Tolls for Poisson Queuing Processes , 1975 .

[9]  Ekram Hossain,et al.  Dynamic Spectrum Access and Management in Cognitive Radio Networks , 2009 .

[10]  Dusit Niyato,et al.  Game Theory in Wireless and Communication Networks: Fundamentals of game theory , 2011 .

[11]  Julien Freudiger,et al.  On Wireless Social Community Networks , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[12]  Antonis Economou,et al.  Equilibrium balking strategies in the observable single-server queue with breakdowns and repairs , 2008, Oper. Res. Lett..

[13]  Zhongding Lei,et al.  IEEE 802.22: The first cognitive radio wireless regional area network standard , 2009, IEEE Communications Magazine.

[14]  Shaolei Ren,et al.  User subscription dynamics and revenue maximization in communications markets , 2011, 2011 Proceedings IEEE INFOCOM.

[15]  Choong Seon Hong,et al.  Social Optimization Strategy in Unobserved Queueing Systems in Cognitive Radio Networks , 2012, IEEE Communications Letters.

[16]  Kang G. Shin,et al.  Wi-Fi 2.0: Price and quality competitions of duopoly cognitive radio wireless service providers with time-varying spectrum availability , 2011, 2011 Proceedings IEEE INFOCOM.

[17]  G. Evans,et al.  Learning and expectations in macroeconomics , 2001 .

[18]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[19]  Seyed Alireza Zekavat,et al.  Traffic Pattern Prediction and Performance Investigation for Cognitive Radio Systems , 2008, 2008 IEEE Wireless Communications and Networking Conference.

[20]  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..

[21]  Brian M. Sadler,et al.  Cognitive Medium Access: Constraining Interference Based on Experimental Models , 2008, IEEE Journal on Selected Areas in Communications.

[22]  Ariel Rubinstein,et al.  A Course in Game Theory , 1995 .

[23]  Zhu Han,et al.  Socially Optimal Queuing Control in Cognitive Radio Networks Subject to Service Interruptions: To Queue or Not to Queue? , 2011, IEEE Transactions on Wireless Communications.

[24]  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.

[25]  Lei Yang,et al.  Pricing-based spectrum access control in cognitive radio networks with random access , 2011, 2011 Proceedings IEEE INFOCOM.

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

[27]  P. Naor The Regulation of Queue Size by Levying Tolls , 1969 .

[28]  Dimitri P. Bertsekas,et al.  Data Networks , 1986 .

[29]  Jianwei Huang,et al.  Duopoly Competition in Dynamic Spectrum Leasing and Pricing , 2012, IEEE Transactions on Mobile Computing.

[30]  Qian Zhang,et al.  Stackelberg game for utility-based cooperative cognitiveradio networks , 2009, MobiHoc '09.

[31]  Dimitri P. Bertsekas,et al.  Data networks (2nd ed.) , 1992 .

[32]  Eytan Modiano,et al.  Non-Cooperative Spectrum Access — The Dedicated vs. Free Spectrum Choice , 2011, IEEE Journal on Selected Areas in Communications.

[33]  Walid Saad,et al.  Game Theory in Wireless and Communication Networks: Applications of game theory in communications and networking , 2011 .

[34]  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.

[35]  John N. Tsitsiklis,et al.  Parallel and distributed computation , 1989 .

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

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

[38]  Qian Wang,et al.  On the Viability of Paris Metro Pricing for Communication and Service Networks , 2010, 2010 Proceedings IEEE INFOCOM.

[39]  Mihaela van der Schaar,et al.  Queuing-Based Dynamic Channel Selection for Heterogeneous Multimedia Applications Over Cognitive Radio Networks , 2008, IEEE Transactions on Multimedia.