Optimization Design For Intelligent Reflecting Surface Aided Wireless Communication System

With the development of communication technology,Intelligent Reflecting Surface(IRS),as a promising technology,has been widely studied in recent years.Intelligent Reflecting Surface can reflect the incident signal,change the signal propagation environment,suppress the interference between users,and improve the performance of the communication system by intelligently adjusting the reflection elements.The academic research shows that IRS assists wireless communication which can effectively improve the achievable rates and reduce energy consumption through reasonable parameter design.IRS is one of the key technologies to promote the development of 6G in the future.This thesis mainly studies the wireless communication scenario of IRS-assisted multi-user communication,and proposes two corresponding optimization algorithms for IRS-assisted multi-user communication and Simultaneous Transmitting and Reflecting Intelligent Reflecting Surface(STAR-IRS)assisted downlink-user communication.The main work of this thesis is as follows:Firstly,the IRS-assisted downlink communication scenario is considered to jointly optimize the beamforming at the base station,the reflection phase and location of the Intelligent Reflecting Surface,to guarantee the fairness of wireless communications,we need to maximize the minimum rates of users.This thesis proposes an optimization algorithm based on alternating optimization,which decomposes the original problem into two sub-problems,and solves them through alternating optimization and Successive Convex Approximation(SCA)algorithm respectively.The simulation results show that the proposed algorithm can effectively improve the rates of users and also prove that optimizing the location of Intelligent Reflecting Surface can further improve the system performance.Secondly,considering the problem of STAR-IRS assisted downlink communication,STAR-IRS works on mode selection protocol.The problem of maximizing user rates is studied by jointly optimizing the beamforming vector,reflection phase and the number of allocation of reflection elements in STAR-IRS.This thesis proposes an alternating optimization algorithm to solve this problem,which decomposes the original problem into three sub-problems,and uses semi-positive definite programming and first order search algorithms to solve the problem.The simulation results show that the proposed algorithm can effectively improve the user rates,and verify that STAR-IRS can improve the user rates in full-space coverage in wireless communication systems.