The combination of non-orthogonal multiple access (NOMA) and intelligent reflecting surface (IRS) is an efficient solution to significantly enhance the energy efficiency of the wireless communication system. In this paper, we focus on a downlink multi-cluster NOMA network, where each cluster is supported by one IRS. We aim to minimize the transmit power by jointly optimizing the beamforming, the power allocation and the phase shift of each IRS. The formulated problem is non-convex and challenging to solve due to the coupled variables, i.e., the beamforming vector, the power allocation coefficient and the phase shift matrix. To address this non-convex problem, we propose an alternating optimization based algorithm. Specifically, we divide the primal problem into the two subproblems for beamforming optimization and phase shifting feasiblity, where the two subproblems are solved iteratively. Moreover, to guarantee the feasibility of the beamforming optimization problem, an iterative algorithm is proposed to search the feasible initial points. To reduce the complexity, we also propose a simplified algorithm based on partial exhaustive search for this system model. Simulation results demonstrate that the proposed alternating algorithm can yield a better performance gain than the partial exhaustive search algorithm, OMA-IRS, and NOMA with random IRS phase shift.

中文翻译：

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多集群 IRS-NOMA 网络中波束成形、相移和功率分配的联合优化

非正交多址（NOMA）和智能反射面（IRS）的结合是显着提高无线通信系统能效的有效解决方案。在本文中，我们关注下行多集群 NOMA 网络，其中每个集群由一个 IRS 支持。我们的目标是通过联合优化每个 IRS 的波束成形、功率分配和相移来最小化发射功率。由于耦合变量，即波束成形矢量、功率分配系数和相移矩阵，公式化的问题是非凸的并且难以解决。为了解决这个非凸问题，我们提出了一种基于交替优化的算法。具体来说，我们将原始问题分为波束成形优化和相移可行性两个子问题，其中两个子问题是迭代解决的。此外，为了保证波束成形优化问题的可行性，提出了一种迭代算法来搜索可行的初始点。为了降低复杂性，我们还针对该系统模型提出了一种基于部分穷举搜索的简化算法。仿真结果表明，与部分穷举搜索算法、OMA-IRS 和具有随机 IRS 相移的 NOMA 相比，所提出的交替算法可以产生更好的性能增益。