Journals Proceedings

Abstract

The simultaneous transmissions of multiple users on a channel interfere with each other and it becomes pivotal to devise a mechanism to obtain some form of separation. In a cognitive radio ad hoc network (CRAHN), the users compete to acquire best suitable bandwidth from already scarce spectrum, resulting in a fierce competition. The nodes may not observe desirable etiquettes in selecting channels and waveforms that result in chaos, which degrades the Quality of Service for the entire network. In order to inhibit the nodes while maintaining their autonomous behavior, there is a need of intelligent mechanism to inculcate the nodes in the network. A game theoretic framework is proposed to achieve convergence in selecting sub-channels and waveforms for transmissions. The proposed model is an eigen-iterative framework, in which signature sequences and sub-channels keep on updating after every cycle. Eigenvectors corresponding to the minimum eigenvalue of correlation matrix is used to maximize the utility and ultimately reduce the interference. The simulation results show fast convergence and stable network with Nash equilibrium at a desirable point.