Fairness of User Clustering in MIMO Non-Orthogonal Multiple Access Systems

Abstract

In this letter, a downlink multiple-input-multiple-output non-orthogonal multiple access scenario is considered. We investigate a dynamic user clustering problem from a fairness perspective. In order to solve this optimization problem, three sub-optimal algorithms, namely, top-down A, top-down B, and bottom up, are proposed to realize the different tradeoffs of complexity and throughput of the worst user. In addition, for each given user clustering case, we optimize the power allocation coefficients for the users in each cluster by adopting a bisection search-based algorithm. Numerical results show that the proposed algorithms can lower the complexity with an acceptable degradation on the throughput compared with the exhaustive search method. It is worth noting that the top-down B algorithm can achieve a good tradeoff between the complexity and the throughput among the three proposed algorithms.