Resource allocation has always been one of the main challenges in the design of wireless cellular networks. Suitable resource allocation, more specifically that includes suitable base station selection and bandwidth allocation can play an effective role in interference mitigation and users’ quality of service requirement satisfaction. In this paper, a game theoretic approach is proposed to solve the BS selection problem in two-tier wireless femtocell networks. We formulate the competitive behavior of users as evolutionary game theory. We calculate the probability of a user choosing a BS, compute the cell load of each BS, and analyze the demand rejection probability of the user associated with the BS. The proposed approach maximizes network throughput as well as meeting the QoS requirements of the users. Finally, we propose a decentralized learning algorithm based on EXP3 algorithm to achieve the evolutionary equilibrium as the solution of the game. Simulation results show that the proposed approach achieves a desirable performance and guarantees users’ QoS requirements.