| Reconfigurable intelligent surface(RIS)has received great attention because of its potential to enhance the capacity and coverage of wireless network through intelligent reconfiguration of the wireless communication environment,which is considered as one of the promising technologies of the sixth generation mobile networks(6G).In order to enable RIS to be effectively applied in real life scenes,there is some primary problem to be solved,which is how to adjust the amplitude and phase of incident signals quickly and accurately in real time according to the location of mobile users and the channel state information(CSI),so that the system capacity is significantly improved.Therefore,this thesis mainly studies the joint optimization of the passive and active beamforming of RIS and the powered devices such as base stations(BSs),access points(APs)and so on.Firstly,the joint beamforming optimization for the single user communication in the millimeter wave multiple input multiple output(MIMO)system assisted by RIS is studied.The access point(AP)active beamforming design and RIS passive reflection matrix were optimized to maximize the system spectral efficiency.The RIS passive reflection matrix design problem is derived into a non-convex quadratically constrained quadratic programs(QCQP)problem,and then a low complexity successive closed form(SCF)algorithm is proposed,which converts the non-convex constant modulus constraints to solving a quadratic programming sequence with convex equation constraints.In order to measure the performance by employing the SCF algorithm,the optimal branch-and-bound(Bn B)algorithm is compared.After convex relaxation of the problem,the search space is divided to solve the subproblem according to the rules until convergence.Simulation results show that the SCF algorithm has low complexity and high spectral efficiency whether RIS phase shift is continuous or discrete.Secondly,the joint beamforming optimization of distributed RIS assisted multi-user millimeter wave wireless communication system is addressed.The BS beamforming and RIS reflection phase shift were jointly optimized to maximize the user-weighted sum rate.In the underlying system model,the optimization problem of the maximum user-weighted sum rate is formulated and derived.And then considering the product manifold in conjunction with the manifold optimization algorithm,the parallel iterative solution of BS beamforming and RIS reflection coefficient is proposed as product manifold optimization(PMO)algorithm.Moreover the complexity of the proposed PMO algorithm and that of the alternating manifold optimization(AMO)algorithm are analyzed respectively.Lastly,the simulation results show that the performance of the proposed PMO algorithm is better than that of the existing AMO algorithm in terms of the various numbers of BS antennas,users,and RIS reflection elements,even under the various maximum transmitting power of BS and discrete RIS phase shift.Finally,the joint beamforming optimization of STAR-RIS(simultaneously transmitting and reflecting RIS)assisted multi-user wireless communication system is researched.In the underlying system model,the BS beamforming matrix and STAR-RIS transmitting and reflecting beamforming are jointly optimized to minimize the BS transmitting power when the quality of service(Qo S)communication requirement of users are satisfied.In order to solve this non-convex problem,the successive convex approximation(SCA)algorithm based on punishment is employed to solve iteratively until achieving convergence.Then,the complexity of the algorithm is analyzed,and convergence of iteration solution is verified by the simulation.The BS transmitting power of the STAR-RIS system compared with the other two benchmark schemes is studied from three perspectives: the number of STAR-RIS components,the number of BS antenna and the user Qo S requirement.The simulation results verify the effectiveness of STAR-RIS,which has certain performance advantages over the conventional RIS assisted communication systems. |
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