Femtocell has been considered as a key promising technology to improve the capacity of a cellular system. However, the femtocells deployed inside a macrocell coverage are potentially suffered from excessive interference. This paper proposes a novel radio resource optimization in closed access femtocell networks based on bat algorithm. Bat algorithm is inspired by the behavior of bats in their echolocation process. While the original bat algorithm is designed to solve the complex optimization problem in continuous search space, the proposed modified bat algorithm extends the search optimization in a discrete search space which is suitable for radio resource allocation problem. The simulation results verify the convergence of the proposed optimization scheme to the global optimal solution and reveal that the proposed scheme based on modified bat algorithm facilitates the improvement of the femtocell network capacity.

In a spectrum sharing system, lower-priority users are allowed to spatially reuse the spectrum allocated to higher-priority users as long as they do not disrupt communications of the latter. Therefore, to improve spectrum utilization, an important requirement for the former users is to manage the interference and ensure that the latter users can maintain reliable communications. In the present paper, a game theoretic framework of joint channel selection and power allocation for spectrum sharing in distributed cognitive radio networks is proposed. First, a utility function that captures the cooperative behavior to manage the interference and the satisfaction level to improve the throughput of the lower-priority users is defined. Next, based on the defined utility function, the proposed framework can be formulated as a potential game; thus, it is guaranteed to converge to a Nash equilibrium when the best response dynamic is performed. Simulation results show the convergence of the proposed potential game and reveal that performance improvements in terms of network throughput of the lower-priority users and outage probability of the higher-priority users can be achieved by the introduction of an adaptive coefficient adjustment scheme in the proposed utility function at the expense of the convergence to the Nash equilibrium.