Spectrum Allocation Based on Game Theory in Cognitive Radio Networks

This paper proposes a new spectrum allocation scheme based on detection probability of cognitive users. This new scheme takes a look at a cognitive radio network system composed of one primary system with several cognitive users which is combined with game theory to compensate the detection cost through detection probability. Nash Equilibrium (NE) was used to determine the cost based on the detection probability. Outcomes data revealed that in the utility function of the game, NE was stable through price adjustment. The findings shows that NE is related to the detection probability and the higher the detection probability, the more spectrum resources are in dynamic allocation and thus the higher the quality communication services for the user will gained, thus the detection cost influences the quality of the system. Finally a comparison was made between NE and Pareto Optimality to look at the necessity and conditions of possible conversion from NE to Pareto Optimality.

[1]  Ning Han,et al.  Spectral correlation based signal detection method for spectrum sensing in IEEE 802.22 WRAN systems , 2006, 2006 8th International Conference Advanced Communication Technology.

[2]  Cristina Comaniciu,et al.  Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[3]  Xuezhi Tan,et al.  Cooperative Algorithm for Cognitive Radio Networks Which is Based on Adaptive Election , 2006, TENCON 2006 - 2006 IEEE Region 10 Conference.

[4]  K. J. Ray Liu,et al.  Belief-Assisted Pricing for Dynamic Spectrum Allocation in Wireless Networks with Selfish Users , 2006, 2006 3rd Annual IEEE Communications Society on Sensor and Ad Hoc Communications and Networks.

[5]  Tan Xuezhi,et al.  Dynamic Spectrum Allocation in Cognitive Radio: Auction and Equilibrium , 2009, 2009 International Forum on Information Technology and Applications.

[6]  Wei Wang,et al.  List-coloring based channel allocation for open-spectrum wireless networks , 2005, VTC-2005-Fall. 2005 IEEE 62nd Vehicular Technology Conference, 2005..

[7]  Shuguang Cui,et al.  Price-Based Spectrum Management in Cognitive Radio Networks , 2008, IEEE J. Sel. Top. Signal Process..

[8]  Michael L. Honig,et al.  Auction mechanisms for distributed spectrum sharing , 2004 .

[9]  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.

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

[11]  Dusit Niyato,et al.  Competitive spectrum sharing in cognitive radio networks: a dynamic game approach , 2008, IEEE Transactions on Wireless Communications.