Research Of Beamforming Algorithm For Intelligent Reflecting Surface Aided MIMO Communication Systems

With the Fifth Generation(5G)of mobile communication technology gradually mature and commercialization,the development of Beyond 5G(B5G)/Sixth Generation(6G)of mobile communication technology research has become the focus of domestic and foreign research institutes and ICT enterprises.Through the in-depth analysis of the existing problems of 5G technology and the in-depth exploration of B5G/6G application requirements,it is not difficult to find that B5G/6G urgently needs new technologies to improve the spectrum and energy efficiency of wireless communication without significantly increasing the cost of network deployment,so as to meet the future application requirements and achieve sustainable network evolution in a real sense.At the same time,a wireless communication enabling technology called Intelligence Reflecting Surface(IRS)has been proposed recently.IRS can be programmed to control the reflected phase and direction of electromagnetic waves incident on its surface intelligently.In addition,IRS has the characteristics of low cost,thin weight,low loss,low complexity and strong deployability.Therefore,it is a very competitive and promising technology in improving the spectrum and energy efficiency of wireless communication systems,enhancing the security of wireless communication and reducing the cost of system deployment.It is also seen as one of the key candidate technologies of B5G/6G.Research on the IRS enabling wireless communication technology is just getting started.The paper focuses on joint resource allocation for IRS-assisted Multi-Input Multi-Output(MIMO)wireless communication system.Especially,joint resource allocation for IRS-assisted MIMO wireless physical layer security communication and MIMO-based cognitive radio system are figured out.The main contents are summarized as follows:(1)Research the joint resource allocation for IRS-assisted MIMO wireless physical layer security communication system,that is,an Access Point(AP)with multi-antenna has secure communication requirements with multi-antenna enabled authorized users.Moreover,there is a multi-antenna enabled eavesdropping node in the network trying to eavesdrop confidential communication.First,based on the IRS continuous reflection coefficient model and the AP maximum transmit power constraint,we jointly optimize the AP transmit covariance matrix and IRS reflection coefficient to maximize the system's secrecy communication rate.Since the optimization problem is non-convex and the decision variables are coupled with each other,a sub-optimal algorithm based on Alternate Optimization(AO)is proposed: given IRS reflection coefficients,continuous convex approximation method is adopted to optimize AP transmit covariance matrix;given AP transmit covariance matrix,alternate optimization method is used again to optimize the reflection coefficient of a single IRS when reflection coefficient of other IRS elements is fixed.Subsequently,the proposed algorithm is extended to the problem with IRS discrete reflection coefficient model in the same scene.Finally,numerical simulation verifies the convergence of the proposed algorithm and the reachability of the system.(2)Research the joint resource allocation for IRS-assisted MIMO cognitive radio system,in which a secondary access point(SAP)communicates with multiple secondary users(SUs)without affecting multiple primary users(PUs)in the primary network and all nodes are equipped with multiple antennas.Our design objective is to maximize the achievable weighted sum rate(WSR)of SUs subject to the total transmit power constraint at the SAP and the interference constraints at PUs,by jointly optimizing the transmit precoding at the SAP and the reflecting coefficients at the IRS.To deal with the complex objective function,the problem is reformulated by employing the well-known weighted minimum mean-square error(WMMSE)method and an AO-based algorithm is proposed.Furthermore,a special scenario with only one PU is considered and AO algorithm is adopted again.It is worth mentioning that the proposed algorithm has a much lower computational complexity than the above algorithm without the performance loss.Finally,some numerical simulations have been provided to demonstrate that the proposed algorithm outperforms other benchmark schemes.