Research On Beamforming For Doublr-IRS Aided Congnitive Radio

With the rapid growth of mobile users and wireless devices,new wireless applications emerge one after another.At present,the demand for radio resource bandwidth and energy in communication networks is increasing day by day.Therefore,spectrum efficiency and energy efficiency are becoming two important standards for designing future wireless networks.Intelligent reflector surface(IRS),also known as reconfigurable intelligent surface,is a promising method to improve the energy efficiency of wireless communication system by intelligently reconfiguring the channel environment in recent years.It can intelligently configure the amplitude and phase of the incident signal in real time,and then reflect it to the designated receiver,so as to enhance the signal and suppress the interference.Cognitive Radio(CR)is an effective technology to improve the spectrum efficiency of wireless communication.It allows secondary users(SU)to share the spectrum with primary users(PU),that is,SU uses the spectrum authorized for PU to communicate without causing significant interference to PU.The combination of smart reflector and cognitive radio network is expected to achieve highquality wireless communication.Aiming at the problem that the traditional IRS adopts random phase to improve the network performance,in this paper,two IRS are introduced into the downlink MISO CR system,the passive beamforming optimization of IRS is studied.The main work of this paper is as follows:(1)This paper build a dual IRS-assisted multi-input single-output CR network communication model.The model includes two parts: primary network and secondary network.In the secondary network,the Cognitive Base Station(CBS)uses the spectrum allocated to the primary users,and establishes communication with the single-antenna secondary users with the help of an IRS.In the main network,a multi-antenna Primary Base Station(PBS)provides services for multiple single-antenna primary users through another IRS.(2)Based on the above network model,this paper studies the optimization problem of user’s achievable rate,and proposes an optimization scheme based on active and passive beamforming.In this scheme,the transmit power constraint of the base station and the interference tolerance constraint of the secondary network on PU are considered,and the sum of the achievable rates of all users is maximized by jointly optimizing the transmit beamforming of the base station and the phase shift matrix of IRS.In this paper,an iterative algorithm based on Semi-Definite Relaxation(SDR)and alternate optimization idea is used to solve the optimization problem.Firstly,the optimization problem is decomposed into two subproblems by using the idea of alternating optimization,and then the non-convex optimization problem is transformed into a convex optimization problem by using SDR algorithm and related lemma in each sub-problem and solved.The simulation results show that this scheme is superior to the scheme of randomly generating IRS phase in improving the reachable rate of users.(3)This paper studies the energy efficiency of the system,and proposes an energy efficiency optimization scheme based on active and passive beamforming.This scheme maximizes the energy efficiency of the system by jointly optimizing the transmit beamforming of the base station and the phase shift matrix of the IRS.While constructing the optimization problem,two constraints,the maximum transmission power of the base station and the interference threshold of the secondary network to PU are considered.Similarly,the scheme adopts the idea of alternate optimization,and decomposes the original problem into two suboptimization problems to solve the non-convex problem.For the first sub-problem,Dinkelbach algorithm is used to transform the problem formula,and then SDR algorithm is used to relax the rank-one constraint.For the second sub-problem,SDR algorithm and related lemma are used to transform and solve it.The simulation results show that the proposed optimization scheme can obviously improve the energy efficiency of the system,and is superior to other schemes that randomly generate IRS phases.