As the interplay between intelligent reflecting surface (IRS) and non-orthogonal multiple access (NOMA) can boost both the spectrum- and the power-efficiency, this letter investigates an IRS-NOMA system, taking into account the multi-group detection and imperfect successive interference cancellation (SIC). Specifically, a group-level SIC (GSIC) is conceived to remove the decoded groups’ signals, whilst the joint design of power control and equalizers is leveraged to mitigate the aggregated interference caused by NOMA, imperfect SIC, and concurrent transmissions per group. According to the newly formulated multi-group NOMA framework, the transmit power and the phase shifts are optimized alternately to reduce the total energy consumption together with the minimum mean square error equalizer. Thereof, the power control and the phase shift subproblems are respectively addressed by a group-level parallel iteration method and an element-specific sequential rotation method. Compared with various existing methods, the superiority of the proposed IRS-NOMA scheme is demonstrated through simulations.

中文翻译：

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具有不完美 SIC 的智能反射表面辅助 NOMA 上行链路

由于智能反射面 (IRS) 和非正交多址 (NOMA) 之间的相互作用可以提高频谱效率和功率效率，因此本文研究了 IRS-NOMA 系统，同时考虑了多组检测和不完善的问题。连续干扰消除（SIC）。具体来说，组级 SIC (GSIC) 旨在去除解码组的信号，同时利用功率控制和均衡器的联合设计来减轻由 NOMA、不完善的 SIC 和每组并发传输引起的聚合干扰。根据新制定的多组NOMA框架，通过最小均方误差均衡器交替优化发射功率和相移以降低总能量消耗。其中，功率控制和相移子问题分别通过组级并行迭代方法和特定元素顺序旋转方法来解决。与现有的各种方法相比，通过仿真证明了所提出的 IRS-NOMA 方案的优越性。