The interference constraints of genetic spectrum assignment model in cognitive radio networks are analyzed in this paper. An improved genetic spectrum assignment model is proposed. The population of genetic algorithm is divided into two sets, the feasible spectrum assignment strategies and the randomly updated spectrum assignment strategies. The penalty function is added to the utility function to achieve the spectrum assignment strategy that satisfies the interference constraints and has better fitness. The proposed method is applicable in both the genetic spectrum assignment model and the quantum genetic spectrum assignment mode. It can ensure the randomness of partial chromosomes in the population to some extent, and reduce the computational complexity caused by the constraints-free procedure after the update of population. Simulation results show that the proposed method can achieve better performance than the conventional genetic spectrum assignment model and quantum genetic spectrum assignment model.