| The increasing scarcity of spectrum resources and energy consumption problems have severely restricted the development of wireless communication systems,which have received wide attention from industry and academia in recent years.Cognitive radio networks provide an important way to alleviate the spectrum scarcity problem by enabling the coexistence of primary and cognitive networks through spectrum sharing.However,the premise of cognitive radio network operation is to ensure the transmission quality of the primary network,which inevitably affects the performance of the cognitive network.Intelligent Reflecting Surface(IRS)is considered as a key technology to enhance network performance because of its ability to intelligently control the propagation environment of radio with low power consumption and easy deployment.In order to improve the spectral efficiency and energy efficiency of the network,this paper introduces the IRS into the cognitive radio network,and focuses on the spectral efficiency and energy efficiency optimization of the IRS-assisted cognitive radio network.The main contributions and innovations are as follows:(1)Spectral efficiency optimization of IRS-assisted cognitive radio networksTo address the problem of difficult spectral efficiency improvement of IRS-assisted cognitive radio networks,a framework for the spectral efficiency maximization problem is developed.Based on this,a joint optimization scheme for the transmit power of cognitive base stations and phase shift matrix of IRS is proposed using the Alternative Optimization(AO)and Successive Convex Approximation(SCA)methods.The simulation results illustrate that the introduction of IRS can significantly improve the spectral efficiency of the cognitive radio network,and also confirm that increasing the number of IRS elements can further improve the spectral efficiency of the network.(2)Energy efficiency optimization of IRS-assisted cognitive radio networksFacing the demand for energy efficiency improvement of IRS-assisted cognitive radio networks,a framework for the energy efficiency maximization problem is developed.To address the challenge that the energy efficiency maximization problem is coupled with variables and the optimization problem is a fractional optimization problem,an energy efficiency optimization scheme is proposed to jointly optimize the transmit power of cognitive base stations and phase shift matrix of IRS using alternative optimization and Dinkelbach’s method.Simulations reveal a trade-off between spectral efficiency and energy efficiency,and confirm that the introduction of IRS can also improve the energy efficiency of cognitive radio networks. |
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