This paper studies a novel approach for successive interference cancellation (SIC) ordering and beamforming in a multiple antennas non-orthogonal multiple access (NOMA) network with multi-carrier multi-user setup. To this end, we formulate a joint beamforming design, subcarrier allocation, user association, and SIC ordering algorithm to maximize the worst-case energy efficiency (EE). The formulated problem is a non-convex mixed integer non-linear programming (MINLP) which is generally difficult to solve. To handle it, we first adopt the linearizion technique as well as relaxing the integer variables, and then we employ the Dinkelbach algorithm to convert it into a more mathematically tractable form. The adopted non-convex optimization problem is transformed into an equivalent rank-constrained semidefinite programming (SDP) and is solved by SDP relaxation and exploiting sequential fractional programming. Furthermore, to strike a balance between complexity and performance, a low complex approach based on alternative optimization is adopted. Numerical results unveil that the proposed SIC ordering method outperforms the conventional existing works addressed in the literature.

中文翻译：

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针对 MC MISO-NOMA 支持的 6G 的稳健节能资源管理、SIC 排序和波束成形设计


本文研究了一种在具有多载波多用户设置的多天线非正交多址 (NOMA) 网络中进行连续干扰消除 (SIC) 排序和波束成形的新方法。为此，我们制定了联合波束成形设计、子载波分配、用户关联和SIC排序算法，以最大化最坏情况下的能源效率（EE）。所提出的问题是非凸混合整数非线性规划（MINLP），通常很难解决。为了处理它，我们首先采用线性化技术以及松弛整数变量，然后使用 Dinkelbach 算法将其转换为数学上更容易处理的形式。所采用的非凸优化问题被转化为等效的秩约束半定规划（SDP），并通过SDP松弛和利用顺序分数规划来求解。此外，为了在复杂性和性能之间取得平衡，采用了基于替代优化的低复杂性方法。数值结果表明，所提出的 SIC 排序方法优于文献中讨论的传统现有方法。