Cooperative Resource Allocation for Primary and Secondary Users with Adjustable Priorities in Cognitive Radio Networks

The ability of cognitive radio to sense the spectrum and adapt its parameters in response to the dynamic environment makes it an ideal candidate for resource allocation of spectrum in wireless networks, especially co-existing and emergency networks. In the two latter networks, the secondary users should sense the spectrum and adapt their parameters such that they can use these resources without causing a degradation or interference to the performance of the primary/licensed users. Therefore, in this paper, a decentralized game theoretic approach for resource allocation of the primary and secondary users in a cognitive radio networks is proposed. In this work, the priorities of the networks are incorporated in the utility and potential functions which are in turn used for resource allocation. It is demonstrated analytically by using the potential and utility functions and through simulation studies that a unique NE exists for the combined game with primary users (PU) and secondary users (SU), and the combined game converges to the NE.

[1]  K. J. Ray Liu,et al.  Game theory for cognitive radio networks: An overview , 2010, Comput. Networks.

[2]  L. Shapley,et al.  REGULAR ARTICLEPotential Games , 1996 .

[3]  William H. Sandholm,et al.  ON THE GLOBAL CONVERGENCE OF STOCHASTIC FICTITIOUS PLAY , 2002 .

[4]  Tianming Li,et al.  A novel primary-secondary user power control game for cognitive radios with linear receivers , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[5]  Mohsen Guizani,et al.  A Cooperation Strategy Based on Nash Bargaining Solution in Cooperative Relay Networks , 2008, IEEE Transactions on Vehicular Technology.

[6]  Joseph Mitola,et al.  Cognitive Radio An Integrated Agent Architecture for Software Defined Radio , 2000 .

[7]  Chi Wan Sung,et al.  A generalized framework for distributed power control in wireless networks , 2005, IEEE Trans. Inf. Theory.

[8]  H. Vincent Poor,et al.  Energy-efficient resource allocation in wireless networks with quality-of-service constraints , 2007, IEEE Transactions on Communications.

[9]  Dharma P. Agrawal,et al.  Channel capacity maximization in cooperative cognitive radio networks using game theory , 2009, MOCO.

[10]  Cem U. Saraydar,et al.  Efficient power control via pricing in wireless data networks , 2002, IEEE Trans. Commun..

[11]  R. Michael Buehrer,et al.  WSN15-4: A Game-Theoretic Framework for Interference Avoidance in Ad hoc Networks , 2006, IEEE Globecom 2006.

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

[13]  Sankaran M. Menon "SoC and Multi-Core Debug: Are Design for Debug (DFD) features that are put in reuse cores sufficient for Silicon Debug?" , 2006 .

[14]  Christian Ibars,et al.  Distributed Cooperation among Cognitive Radios with Complete and Incomplete Information , 2009, EURASIP J. Adv. Signal Process..

[15]  William Stallings,et al.  Wireless Communications & Networks , 2002 .