Fair power control using game theory with pricing scheme in cognitive radio networks

This paper proposes a payment-based power control scheme using non-cooperative game with a novel pricing function in cognitive radio networks (CRNs). The proposed algorithm considers the fairness of power control among second users (SUs) where the value of per SU' signal to noise ratio (SINR) or distance between SU and SU station is used as reference for punishment price setting. Due to the effect of uncertainty fading environment, the system is unable to get the link gain coefficient to control SUs' transmission power accurately, so the quality of service (QoS) requirements of SUs may not be guaranteed, and the existence of Nash equilibrium (NE) is not ensured. Therefore, an alternative iterative scheme with sliding model is presented for the non-cooperative power control game algorithm. Simulation results show that the pricing policy using SUs' SINR as price punishment reference can improve total throughput, ensure fairness and reduce total transmission power in CRNs.

[1]  A. Viterbi CDMA: Principles of Spread Spectrum Communication , 1995 .

[2]  Zhu Han,et al.  Noncooperative power-control game and throughput game over wireless networks , 2005, IEEE Transactions on Communications.

[3]  Jie Yang,et al.  An efficient SIR-first adaptive power control method in cognitive radio network , 2012, 2012 IEEE Global High Tech Congress on Electronics.

[4]  Nasir Ghani,et al.  Game-Theoretic Approach for Primary-Secondary User Power Control Under Fast Flat Fading Channels , 2011, IEEE Communications Letters.

[5]  Jian Chen,et al.  Efficient swarm intelligent algorithm for power control game in cognitive radio networks , 2013, IET Commun..

[6]  Chen He,et al.  A Novel Price-Based Power Control Algorithm in Cognitive Radio Networks , 2013, IEEE Communications Letters.

[7]  Narayan B. Mandayam,et al.  Pricing and power control for joint network-centric and user-centric radio resource management , 2004, IEEE Transactions on Communications.

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

[9]  Michael L. Honig,et al.  Distributed interference compensation for wireless networks , 2006, IEEE Journal on Selected Areas in Communications.

[10]  Xinbing Wang,et al.  Pricing for Uplink Power Control in Cognitive Radio Networks , 2010, IEEE Transactions on Vehicular Technology.

[11]  Yuhui Shi,et al.  Power control algorithm in cognitive radio system based on modified Shuffled Frog Leaping Algorithm , 2012 .

[12]  Min Dong,et al.  Maximizing Lifetime in Relay Cooperation Through Energy-Aware Power Allocation , 2010, IEEE Transactions on Signal Processing.

[13]  Jia Yue,et al.  Power Control Algorithm Based on SNR Cost Function in Cognitive Radio System , 2012, 2012 IEEE 18th International Conference on Parallel and Distributed Systems.

[14]  Narayan B. Mandayam,et al.  Joint network-centric and user-centric radio resource management in a multicell system , 2005, IEEE Transactions on Communications.

[15]  Rachid El Azouzi,et al.  Introducing hierarchy in energy games , 2009, IEEE Transactions on Wireless Communications.

[16]  Yuan Wu,et al.  Joint Pricing and Power Allocation for Dynamic Spectrum Access Networks with Stackelberg Game Model , 2011, IEEE Transactions on Wireless Communications.

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

[18]  Li Wang,et al.  A New Game Algorithm for Power Control in Cognitive Radio Networks , 2011, IEEE Transactions on Vehicular Technology.

[19]  Geoffrey Ye Li,et al.  Cognitive radio networking and communications: an overview , 2011, IEEE Transactions on Vehicular Technology.

[20]  Sanjay Jha,et al.  Robust Power Allocation for MIMO Beamforming under Time Varying Channel Conditions , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).

[21]  V. Utkin Variable structure systems with sliding modes , 1977 .

[22]  Samson Lasaulce,et al.  A Repeated Game Formulation of Energy-Efficient Decentralized Power Control , 2010, IEEE Transactions on Wireless Communications.

[23]  David J. Goodman,et al.  Power control for wireless data , 2000, IEEE Wirel. Commun..

[24]  Qing Zhao,et al.  Decentralized dynamic spectrum access for cognitive radios: cooperative design of a non-cooperative game , 2009, IEEE Transactions on Communications.

[25]  Ness B. Shroff,et al.  Utility-based power control in cellular wireless systems , 2001, Proceedings IEEE INFOCOM 2001. Conference on Computer Communications. Twentieth Annual Joint Conference of the IEEE Computer and Communications Society (Cat. No.01CH37213).

[26]  Stefano Buzzi,et al.  A Game-Theoretic Approach to Energy-Efficient Power Control and Receiver Design in Cognitive CDMA Wireless Networks , 2011, IEEE Journal of Selected Topics in Signal Processing.

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