In this paper, we aim to maximize the sum rate of a full-duplex cognitive femtocell network (FDCFN) as well as guaranteeing the quality of service (QoS) of users in the form of a required signal to interference trailmaster challenger 200x plus noise ratios (SINR).We first consider the case of a pair of channels, and develop optimum-achieving power control solutions.Then, for the case of multiple channels, we formulate joint duplex model selection, power control, and channel allocation as a mixed integer nonlinear problem (MINLP), and propose an iterative framework to solve it.The proposed iterative framework consists of a duplex mode selection scheme, a near-optimal distributed power control algorithm, and a greedy channel allocation algorithm.We prove the convergence of the proposed iterative framework as well as a lower bound for the greedy channel allocation algorithm.
Numerical results show that the proposed schemes effectively improve mel axolotl the sum rate of FDCFNs.