We consider a cognitive wireless network in which users adopt a spectrum sharing strategy based on cooperation\nconstraints. The majority of cognitive radio schemes bifurcate the role of players as either cooperative or\nnon-cooperative. In this work, however, we modify this strategy to one in which players are hybrid, i.e., both\ncooperative and non-cooperative. Using a Stackelberg game strategy, we evaluate the improvement in performance\nof a cognitive radio network with these hybrid cognitive players using an M/D/1 queuing model. We use a novel\ngame strategy (which we call altruism) to ââ?¬Å?policeââ?¬Â a wireless network by monitoring the network and finding the\nnon-cooperative players. Upon introduction of this new player, we present and test a series of predictive algorithms\nthat shows improvements in wireless channel utilization over traditional collision-detection algorithms. Our results\ndemonstrate the viability of using this strategy to inform and create more efficient cognitive radio networks. Next, we\nstudy a Stackelberg competition with the primary license holder as the leader and investigate the impact of multiple\nleaders by modeling the wireless channel as an M/D/1 queue. We find that in the Stackelberg game, the leader can\nimprove its utility by influencing followersââ?¬â?¢ decisions using its advertised cost function and the number of followers\naccepted in the network. The gain in utility monotonically increases until the network is saturated. The Stackelberg\ngame formulation shows the existence of a unique Nash equilibrium using an appropriate cost function. The\nequilibrium maximizes the total utility of the network and allows spectrum sharing between primary and secondary\ncognitive users.
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