Non-Cooperative Spectrum Access — The Dedicated vs. Free Spectrum Choice

We consider a dynamic spectrum access system in which Secondary Users (SUs) choose to either acquire dedicated spectrum or to use spectrum-holes (white spaces) which belong to Primary Users (PUs). The trade-off incorporated in this decision is between immediate yet costly transmission and free but delayed transmission (a consequence of both the possible appearance of PUs and sharing the spectrum holes with multiple SUs). We first consider a system with a single PU band, in which the SU decisions are fixed. Employing queueing-theoretic methods, we obtain explicit expressions for the expected delays associated with using the PU band. Based on that, we then consider self-interested SUs and study the interaction between them as a non-cooperative game. We prove the existence and uniqueness of a symmetric Nash equilibrium, and characterize the equilibrium behavior explicitly. Using our equilibrium results, we show how to maximize revenue from renting dedicated bands to SUs and briefly discuss the extension of our model to multiple PUs. Finally, since spectrum sensing can be resource-consuming, we characterize the gains provided by this capability.

[1]  Joseph Mitola.  Cognitive Radio for Flexible Mobile Multimedia Communications , 2001, Mob. Networks Appl..

[2]  Ian F. Akyildiz,et al.  CRAHNs: Cognitive radio ad hoc networks , 2009, Ad Hoc Networks.

[3]  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..

[4]  Ishai Menache,et al.  Efficient Rate-Constrained Nash Equilibrium in Collision Channels with State Information , 2008, IEEE INFOCOM 2008 - The 27th Conference on Computer Communications.

[5]  J. J. Garcia-Luna-Aceves,et al.  A scalable model for channel access protocols in multihop ad hoc networks , 2004, MobiCom '04.

[6]  Refael Hassin,et al.  Strategic Behavior and Social Optimization in Markovian Vacation Queues , 2011, Oper. Res..

[7]  H. Vincent Poor,et al.  Energy-Efficient Resource Allocation in Wireless Networks , 2007, IEEE Signal Processing Magazine.

[8]  Zhi Ding,et al.  Opportunistic spectrum access in cognitive radio networks , 2008, IJCNN.

[9]  Flaminio Borgonovo,et al.  Throughput and Delay Bounds for Cognitive Transmissions , 2008, Med-Hoc-Net.

[10]  Norman Abramson,et al.  The Throughput of Packet Broadcasting Channels , 1977, IEEE Trans. Commun..

[11]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

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

[13]  Asuman E. Ozdaglar,et al.  Network Games: Theory, Models, and Dynamics , 2011, Network Games: Theory, Models, and Dynamics.

[14]  Ben Y. Zhao,et al.  Utilization and fairness in spectrum assignment for opportunistic spectrum access , 2006, Mob. Networks Appl..

[15]  Avishai Mandelbaum,et al.  Designing a Call Center with Impatient Customers , 2002, Manuf. Serv. Oper. Manag..

[16]  Linda Doyle,et al.  GUEST EDITORIAL - COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS , 2007 .

[17]  Eytan Modiano,et al.  Non-Cooperative Spectrum Access - The Dedicated vs. Free Spectrum Choice , 2012, IEEE J. Sel. Areas Commun..

[18]  Eitan Altman,et al.  Non-cooperative spectrum access in cognitive radio networks: A game theoretical model , 2011, Comput. Networks.

[19]  Antonis Economou,et al.  Equilibrium customer strategies in a single server Markovian queue with setup times , 2007, Queueing Syst. Theory Appl..

[20]  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.

[21]  Ananthram Swami,et al.  A Decision-Theoretic Framework for Opportunistic Spectrum Access , 2007, IEEE Wireless Communications.

[22]  Steven H. Strogatz,et al.  Nonlinear Dynamics and Chaos , 2024 .

[23]  Lijun Chen,et al.  Random Access Game and Medium Access Control Design , 2010, IEEE/ACM Transactions on Networking.

[24]  G ShinKang,et al.  Cognitive radios for dynamic spectrum access , 2010 .

[25]  Ping Zhu,et al.  Scheduling Model for Cognitive Radio , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

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

[27]  Ananthram Swami,et al.  Decentralized cognitive MAC for opportunistic spectrum access in ad hoc networks: A POMDP framework , 2007, IEEE Journal on Selected Areas in Communications.

[28]  Refael Hassin,et al.  Strategic behavior and social optimization in Markovian vacation queues: The case of heterogeneous customers , 2012, Eur. J. Oper. Res..

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

[30]  Carlos Mosquera,et al.  Dynamic Spectrum Leasing: A New Paradigm for Spectrum Sharing in Cognitive Radio Networks , 2010, IEEE Transactions on Vehicular Technology.

[31]  Brian M. Sadler,et al.  Optimal Dynamic Spectrum Access via Periodic Channel Sensing , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[32]  Haitao Zheng,et al.  Collaboration and fairness in opportunistic spectrum access , 2005, IEEE International Conference on Communications, 2005. ICC 2005. 2005.

[33]  Brian M. Sadler,et al.  COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Access in the Time Domain: Modeling and Exploiting White Space , 2007, IEEE Communications Magazine.

[34]  Vanu G. Bose,et al.  Software Radios for Wireless Networking , 1998, INFOCOM.

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

[36]  R.A. Berry,et al.  Spectrum sharing with distributed interference compensation , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

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

[38]  B. Avi-Itzhak,et al.  A Many-Server Queue with Service Interruptions , 1968, Oper. Res..

[39]  Dietrich Braess,et al.  Über ein Paradoxon aus der Verkehrsplanung , 1968, Unternehmensforschung.

[40]  A. Mas-Colell,et al.  Microeconomic Theory , 1995 .

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

[42]  L. Christie,et al.  Queuing with Preemptive Priorities or with Breakdown , 1958 .

[43]  Peter J. B. King,et al.  Multiserver Systems Subject to Breakdowns: An Empirical Study , 1983, IEEE Transactions on Computers.

[44]  A. Girotra,et al.  Performance Analysis of the IEEE 802 . 11 Distributed Coordination Function , 2005 .

[45]  Zhong Fan,et al.  Noncooperative Equilibrium Solutions for Spectrum Access in Distributed Cognitive Radio Networks , 2008, 2008 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[46]  Chengshu Li,et al.  Opportunistic spectrum access in cognitive radio networks , 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

[47]  Adam Wolisz,et al.  COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Frequency Hopping Communities for Efficient IEEE 802.22 Operation , 2007, IEEE Communications Magazine.