A game theoretic distributed dynamic channel allocation scheme with transmission option

Game theory is a useful tool that can be used to study the distributed resource allocation problem, since each node in the network tries to maximize his own payoff and hence a need to resolve their conflicting interests. In this paper, we introduce utility functions so that the strategy set of each node allows no transmission. We incorporate the effect of interference a node is causing to the surroundings into its utility function so that those nodes which are not so favorable for transmission should sacrifice for the welfare of the network. Although non-cooperative game model is used, modifying the utility function in an effective way causes the overall impact to have some degree of ldquocooperationrdquo or ldquoself-awarenessrdquo among nodes. Our studies show that if utility function is properly chosen, a best-response allocation strategy does exist for each user. An algorithm which performs iterative update among nodes until Nash equilibrium convergence is proposed. Finally, we present our numerical results for our channel allocation game.

[1]  Cristina Comaniciu,et al.  A Game Theoretic Approach to Interference Management in Cognitive Networks , 2007 .

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

[3]  Robert P. Gilles,et al.  On the Role of Game Theory in the Analysis of Software Radio Networks , 2002 .

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

[5]  Byeong Gi Lee,et al.  Distributed Resource Allocation through Noncooperative Game Approach in Multi-cell OFDMA Systems , 2006, 2006 IEEE International Conference on Communications.

[6]  Jeffrey H. Reed,et al.  Convergence of cognitive radio networks , 2004, 2004 IEEE Wireless Communications and Networking Conference (IEEE Cat. No.04TH8733).

[7]  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..

[8]  Zhu Han,et al.  Power minimization for multi-cell OFDM networks using distributed non-cooperative game approach , 2004, IEEE Global Telecommunications Conference, 2004. GLOBECOM '04..

[9]  Roger B. Myerson,et al.  Game theory - Analysis of Conflict , 1991 .

[10]  David J. Goodman,et al.  Power control for wireless data based on utility and pricing , 1998, Ninth IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (Cat. No.98TH8361).