Journal of Xidian University ›› 2023, Vol. 50 ›› Issue (2): 1-10.doi: 10.19665/j.issn1001-2400.2023.02.001

• Information and Communications Engineering •     Next Articles

Fairness optimization for the multi-user NOMA-IRS system

HAN Yongkang(),CHEN Jian(),ZHOU Yuchen(),YANG Long()   

  1. School of Telecommunications Engineering,Xidian University,Xi’an 710071,China
  • Received:2022-06-15 Online:2023-04-20 Published:2023-05-12


Non-Orthogonal Multiple Access (NOMA)-Intelligent Reflection Surface (IRS) systems can improve user access capability through joint "transmit-reflect" beamforming between multiple antenna transmitters and IRS.For the user fairness problem of multi-user NOMA-IRS systems,the minimum received signal-to-Interference plus Noise Ratio (SINR) of users should be maximized in a practical scenario with restricted RF links,so as to guarantee the communication quality of each user without any difference.To this end,a maximum-minimum SINR fractional planning problem is constructed by clustering users according to the number of RF links,and the transmit beam vector of this problem is highly coupled with the reflected array element matrix at SINR.Therefore,a semi-definite relaxation and arithmetic-geometric mean-based algorithm is proposed to maximize the minimum channel capacity in each cluster by alternately optimizing the transmit beam vector and the reflected array element matrix in each iteration.Furthermore,a dichotomous search algorithm is used to solve the intra-cluster power allocation problem to enhance the user minimum SINR.Simulation results show that,compared with the zero-forcing scheme,this scheme can improve the minimum SINR among users with lower computational complexity,thus improving the communication quality of each user.Different from the maximum ratio transmission scheme,the minimum SINR of users in this scheme does not saturate with the increase of transmit power at base stations,thus enabling the steady growth of communication quality of each user.

Key words: non-orthogonal multiple access, intelligent reflection surface, fairness, user clustering, beamforming, resource allocation

CLC Number: 

  • TN92