Research On Beamforming Of Intelligent Reflecting Surface-assisted Cognitive Radio Network

With the wide application of wireless communication networks and intelligent mobile devices,the future wireless networks put forward higher requirements for spectrum efficiency and communication cost.At the same time,the demand for radio spectrum resources is also increasing rapidly.Cognitive radio(CR)technology,as a useful measure to improve spectrum efficiency,is a technology to improve radio spectrum utilization by allowing unauthorized secondary users to share spectrum with authorized primary users.However,on the one hand,due to the conflict of performance improvement between primary users and secondary users in cognitive network,it is very meaningful to study a reasonable resource allocation scheme;on the other hand,due to the openness and high dynamics of cognitive network,the problem of secure communication of the system can not be ignored.Therefore,it is urgent to formulate a secure communication strategy of cognitive network.In recent years,as a very promising green communication technology,intelligent reflecting surface(IRS)has the advantages that it can effectively realize the directional reflection of incident electromagnetic waves by designing the phase shift of reflection unit,enhance the received signal power of legitimate users and suppress the received signal strength of illegal users,so as to intelligently reconfigure the radio propagation environment.Therefore,by deploying IRS in cognitive radio network,it can not only bring a more favorable resource allocation scheme for cognitive radio communication system,but also enhance the security of communication system.This thesis studies the beamforming design and physical layer secure transmission scheme of IRS-assisted cognitive network.(1)Beamforming design of IRS-assisted cognitive network.In this scenario,when there are obstacles resulting in the failure of communication between the base station and the secondary users in the secondary network,the IRS is deployed to reflect the signal sent by the base station,so as to establish the communication link between the base station and the users.In the research,a method of jointly optimizing the transmit beamforming of secondary base station and the reflection phase shift matrix of IRS is proposed to maximize the spectral efficiency of secondary users.Firstly,aiming at the high non convexity of the objective optimization problem,an iterative algorithm based on alternating optimization is proposed to decompose the original problem into corresponding sub optimization problems;secondly,aiming at the non-convex sub optimization problems,the semidefinite relaxation(SDR)technology and the successive convex approximation(SCA)method are proposed to obtain the solution of the sub optimization problems.The experimental simulation results show that the proposed joint optimization algorithm significantly improves the spectral efficiency of secondary users.(2)Secure communication strategy of IRS-assisted cognitive network.This scenario studies the legitimate communication between the base station and the user in the secondary network in the presence of eavesdropper.This thesis uses the friendly jammer cooperating with the IRS to enhance the secure communication performance of the cognitive network.By jointly optimizing the transmit beamforming of the secondary base station and the friendly jammer and the reflection phase shift matrix of the intelligent reflector,the security rate of the secondary user is maximized.Meanwhile,the interference power of the secondary network to the primary user is limited.For the non-convex objective optimization problem,SDR and SCA methods are used to solve the non-convex optimization problem,and an iterative algorithm based on alternating optimization is proposed to obtain the optimal solution of the objective optimization problem.The experimental simulation results show that the performance of the proposed secure communication scheme is significantly better than other baseline schemes.