Abstract-In this letter, a downlink multiple-input-multipleoutput 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. Index Terms-Fairness, MIMO, NOMA, and user clustering.
Since one of key features of NOMA is to balance throughput against fairness, a principle of maximizing the SINR of the worst user in each cluster is proposed in REF , which can be regarded as max-min fairness and achieve a good tradeoff between throughput and fairness.
Fairness of User Clustering in MIMO Non-Orthogonal Multiple Access Systems
IEEE Communications Letters
IEEE Communications Letters
Computer Science