Maximum throughput design of wireless powered communication network with IRS-NOMA based on user clustering

A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in order to ensure that the hybrid access point(H-AP)can correctly decode user information via successive interference cancellation(SIC)technology,the information transmit power of user needs to satisfy a certain threshold,so as to meet the corresponding SIC constraints.Therefore,when the number of users who transfer information simultaneously increases,the system performance will be greatly restricted.To minimize the influence of SIC constraints on system performance,users are firstly clustered,and then each cluster collects energy from H-AP and finally,users transfer information based on NOMA with the assistance of IRS.Specifically,this paper aims to maximize the sum throughput of the system by jointly optimizing the beamforming of IRS and resource allocation of the system.The semi-definite relaxation(SDR)algorithm is employed to alternately optimize the beamforming of IRS in each time slot,and the joint optimization problem about user’s transmit power and time is transformed into two optimal time allocation sub-problems.The numerical results show that the proposed optimization scheme can effectively improve the sum throughput of the system.In addition,the results in the paper further reveals the positive impact of IRS on improving the sum throughput of the system.