Optimization Of Fair Rate Of Users In IRS Assisted Multi-carrier NOMA System

With the development of wireless mobile communication today,users’ needs have gradually changed from voice communication to multiple information exchanges.In the future,mobile communication will undoubtedly be more abundant.Non-orthogonal multiple access(NOMA)technology and intelligent reflecting surface(IRS)technology have emerged to meet the rising demand for data exchange by increasing the capacity of communication systems in different ways.NOMA technology can improve spectrum utilization by reusing the same frequency band by sending the superimposed signals of multiple users at the transmitting end and then using the Serial Interference Cancellation technology at the receiving end to separate the signals of different users,and resultantly increases the system capacity.By introducing new links and adjusting them,the IRS technology can superimpose and strengthen valuable signals at the receiving end and make the interference cancel each other to weaken,thereby improving the system capacity.In addition to enhancing the capacity of communication systems,guaranteeing fairness among users is also a basic requirement in wireless communication.Therefore,this thesis applies these two technologies to a multi-carrier system and studies how to optimize the fair rate of all users in the system.Since the number of users multiplexing the same resource block in the NOMA system is limited and different grouping methods have different effects on the system performance,how to group users is especially important.Existing research on user grouping strategies in NOMA systems has generally designed grouping schemes based on the channel gains of users on different subcarriers.Since IRS can change the communication environment,the channel gain of users will also change under different settings of the IRS,so it is impossible to simply allocate resources and group users through channel gain after the introduction of IRS technology.Therefore,designing a reasonable and efficient resource allocation and user grouping scheme is necessary.Therefore,this thesis investigates how to optimize the user’s fair rate in an IRS-assisted multi-carrier NOMA downlink system.The specific research contents are as follows:1.Firstly,this thesis investigates how to jointly optimize the IRS reflection coefficient,base station beamforming coefficient,and power allocation to improve the fair rate of all users,given the way of resource allocation and user grouping.The part adopts alternate optimization,Semidefinite Relaxation,Successive Convex Approximation,and Gaussian randomization methods to solve the optimization problem.Secondly,this thesis proposes a resource allocation and user grouping scheme based on the Signal to Interference-plus-noise Ratio(SINR)at the receiving end.The simulation results show that the system performance has been improved after the introduction of IRS and NOMA technology,and the proposed SINR-based resource allocation and user grouping scheme at the receiver side also perform well.Compared with other schemes,the user’s fair rate of the proposed SINR-based resource allocation and user grouping scheme is 0.5%～4.3% higher.2.this thesis developed based on the first part to improve the fair rate of users further.This part proposes two redistribution schemes.One is the redistribution scheme based on the hill-climbing algorithm;the other is the reallocation scheme based on the SINR at the receiver side.The simulation analysis shows us that the redistribution process is vital for the IRS-assisted multi-carrier NOMA downlink system.Although the receiver-side SINR-based redistribution scheme cannot guarantee an increase in performance after each redistribution,it has the higher overall performance.Compared with the redistribution scheme based on the hill-climbing algorithm,It has opportunity to jump to another local optimum with higher performance.Compared with other schemes,the user’s fair rate of the proposed SINR-based redistribution scheme is 0.7%～5.1% higher.In addition,compared with the random redistribution scheme,the receiver-side SINR-based redistribution scheme has a higher utilization rate of computational resources.