Topology control approach based on radio irregularity using game theory for cognitive wireless networks

A novel topology control approach for cognitive wireless networks is proposed in this paper. It includes sensing, decision-making and acting process. Sensing process is to collect necessary local information which will be used in the decision-making stage. Decision-making process uses game theory to decide the best moving positions of nodes. A local utility function is designed for each node in this stage. It takes conditions of radio irregularity and radio regularity into account. Each node makes decision distributed and selfishly. The Nash Equilibrium in game theory is also discussed. Acting process is to construct a new topology. Our approach aims at increasing the coverage area of all nodes and keeping the whole network connected at the same time. In order to verify our approach, two groups of experiments based on radio regularity and radio irregularity are designed. In each experiment, there are two scenarios based on different node numbers. What is more, the convergence of our approach is described. Experiment results show that the proposed method is effective, reliable and stable.

[1]  S. Samtani,et al.  Efficient node distribution techniques in mobile ad hoc networks using game theory , 2009, MILCOM 2009 - 2009 IEEE Military Communications Conference.

[2]  Carolina Fortuna,et al.  Trends in the development of communication networks: Cognitive networks , 2009, Comput. Networks.

[3]  Allen B. MacKenzie,et al.  Effect of Selfish Node Behavior on Efficient Topology Design , 2008, IEEE Transactions on Mobile Computing.

[4]  Gustavo Alonso,et al.  Understanding Radio Irregularity in Wireless Networks , 2008, 2008 5th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks.

[5]  Allen B. MacKenzie,et al.  Using game theory to analyze wireless ad hoc networks , 2005, IEEE Communications Surveys & Tutorials.

[6]  Allen B. MacKenzie,et al.  The price of ignorance: distributed topology control in cognitive networks , 2010, IEEE Transactions on Wireless Communications.

[7]  Gang Zhou,et al.  Models and solutions for radio irregularity in wireless sensor networks , 2006, TOSN.

[8]  F. Richard Yu,et al.  Prediction-Based Topology Control and Routing in Cognitive Radio Mobile Ad Hoc Networks , 2010, 2010 INFOCOM IEEE Conference on Computer Communications Workshops.

[9]  Allen B. MacKenzie,et al.  Joint Power and Channel Minimization in Topology Control: A Cognitive Network Approach , 2007, 2007 IEEE International Conference on Communications.

[10]  Yuebin Bai,et al.  Link availability prediction with radio irregularity coverage for mobile multi-hop networks , 2010, IEEE Communications Letters.

[11]  Madhav V. Marathe,et al.  Critical Design Decisions for Cognitive Networks , 2007, 2007 IEEE International Conference on Communications.

[12]  V. Georgiev Using Game Theory to Analyze Wireless Ad Hoc Networks . ” , 2008 .

[13]  Tao Chen,et al.  CogMesh: A Cluster-Based Cognitive Radio Network , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.