Improved bandwidth allocation in Cognitive Radio Networks based on game theory

In this paper, an improved method for bandwidth allocation in a Cognitive Radio Network based on game theory is presented. In this work, utility has been modified by inserting weights to the three terms, received power, interference to other links and interference from other links. Inserting weights enables us to treat different CRN scenarios separately and appropriately as per the requirement of the administrator. Moreover, a suitable performance index for a CRN that considers throughput and interference to other links has been introduced and is used to evaluate different schemes. Being able to segregate and individually treat the different utility terms has aided to analyze and understand the CRN better and at a deeper level, which will be helpful for further research work.

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

[2]  Yong Huat Chew,et al.  Capacity and throughput for transmission over flat fading channels employing SNR-priority-based channel allocation scheme , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[3]  Rui Yang,et al.  Non-cooperative spectrum allocation based on game theory in cognitive radio networks , 2010, 2010 IEEE Fifth International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA).

[4]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[5]  Brian L. Mark,et al.  Collaborative Opportunistic Spectrum Access in the Presence of Multiple Transmitters , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[6]  Simon Haykin,et al.  Robust Transmit Power Control for Cognitive Radio , 2009, Proceedings of the IEEE.

[7]  Brunilde Sanso,et al.  A performance comparison of cognitive versus traditional radio networks , 2010, 2010 IEEE Globecom Workshops.

[8]  Hong Ji,et al.  Dynamic Channel and Power Allocation in Cognitive Radio Networks Supporting Heterogeneous Services , 2010, 2010 IEEE Global Telecommunications Conference GLOBECOM 2010.

[9]  Zhen Yang,et al.  Power Allocation Using Non-Cooperative Game Theoretic Analysis in Cognitive Radio Networks , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).

[10]  Hüseyin Arslan,et al.  A survey of spectrum sensing algorithms for cognitive radio applications , 2009, IEEE Communications Surveys & Tutorials.

[11]  Shuguang Cui,et al.  Price-Based Spectrum Management in Cognitive Radio Networks , 2007, IEEE Journal of Selected Topics in Signal Processing.

[12]  Hamid Aghvami,et al.  Cognitive Radio game for secondary spectrum access problem , 2009, IEEE Transactions on Wireless Communications.

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

[14]  Henry Leung,et al.  A game theoretic approach for resource allocation in Cognitive Wireless Sensor Networks , 2011, 2011 IEEE International Conference on Systems, Man, and Cybernetics.