In price-based cognitive radio networks,the Primary user(PU) can allow the Secondary users(SUs) to access by pricing if their interference power is under the Interference power constraint(IPC). The interaction between the PU and the SUs is modeled as a Stackelberg game with the consideration of the Quality of service(Qo S) of the SUs. The revenue maximization problem of PU is expressed as an equivalent convex optimization problem if the minimum Signal-to-interference and noise ratio(SINR) constraints for the SUs are greater than or equal to 0d B. An optimal pricing algorithm is proposed based on this equivalent convex optimization problem. Simulation results show that the proposed pricing algorithm outperforms the non-uniform pricing algorithm in terms of the revenue of the PU, the sum rate of SUs and the number of admitted SUs. The price-based cognitive radio networks, the Primary user (PU) can allow the Secondary users (SUs) to access by pricing if their interference power is under the interference power constraint (IPC). The interaction between the PU and the SUs is modeled as a Stackelberg game with the consideration of the Quality of Service (Qo S) of the SUs. The revenue maximization problem of PU is expressed as an equivalent convex optimization problem if the minimum Signal-to-interference and noise ratio (SINR) constraints for the SUs are greater than or equal to 0d B. An optimal pricing algorithm is proposed based on this equivalent convex optimization problem. sum rate of SUs and the number of admitted SUs.