Cognitive radio networks: Game modeling and self-organization using stochastic learning

Chen-Hao Lin, Li-Chuan Tseng, ChingYao Huang
2013 2013 IEEE 24th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)  
Due to the high demand of spectrum utilization, cognitive radio (CR) network has been a promising solution to the problem of spectrum scarcity by using dynamic spectrum access technique. The CR networks is applied to the original network (or primary network) without modifying the original network. In this paper, we studied one of the CR network architectures, CR network access architecture, where the CR base stations (CRBSs) demand spectrum resources from the primary network and distribute them
more » ... and distribute them to the CR users. We applied an economical Cournot Game model to the system where the CRBSs are the players and compete for better performance in this game. In order to optimize the game, we proposed a stochastic learning (SL) based scheme for the CRBSs to adjust the demand amount of resources based only on the action-reward history, which means there is no need for a centralized controller. We proved that the SL-based algorithm leads the system to converge toward a Nash Equilibrium (NE) point. Numerical results correspond to the proof. The results also show that the system performs well in terms of the total utility comparing with other schemes.
doi:10.1109/pimrc.2013.6666662 dblp:conf/pimrc/LinTH13 fatcat:xsum4obu45gfbguyecbroz4gmm