Abstract
Game Theory (GT) is a natural paradigm to study and analyze wireless networks where players compete for the same resources. The importance of studying the coexistence between macro- and femtocells from a game theoretical perspective is multi-fold: First, by modeling the dynamic spectrum sharing among network players as games, the behaviors and actions of players can be analyzed in a formalized structure, by which the theoretical achievements in GT can be fully utilized. Second, GT equips us with various optimality criteria for the spectrum sharing problems, which are of key importance when it comes to analyzing the equilibrium of the game. Third, the application of GT enables us to derive efficient distributed algorithms for femtocell networks relying only on partial information. Without a doubt, the theory of learning in games is instrumental in allowing players to choose the right strategies and gradually learn from their environment until convergence.
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