To accommodate the stringent requirements of massive connectivity and ultra-high throughput, both reconfigurable intelligent surface (RIS) and non-orthogonal multiple access (NOMA) have been perceived as the key techniques for future communication networks. In this paper, a versatile framework is conceived to boost transmit power efficiency for RIS-enabled multi-group NOMA networks in the presence of coordinated multi-point (CoMP) reception and imperfect successive interference cancellation (SIC). Particularly, a group-level SIC (GSIC) method is proposed to eliminate the decoded group’s interference together with the well-designed transceivers to mitigate the aggregated interference, including the intra-group interference, the residual interference caused by imperfect SIC, and the interference of NOMA users decoded later. According to the novel framework, a power minimization problem is formulated by collaboratively optimizing the transmit power and the phase shifts. To render the problem tractable, an alternating scheme is developed to optimize the transmit power and the phase shifts iteratively. Specifically, the transmit powers for the users in the same group are devised by a parallel iteration algorithm, whilst the phase shifts are optimized by a sequential rotation method. In simulations, it is shown that the proposed scheme requires less transmit power than various benchmark methods under the constraint of each user’s quality of service.

中文翻译：

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具有 GSIC 的上行链路 RIS 辅助 CoMP-NOMA 网络的功率最小化

为了适应大规模连接和超高吞吐量的严格要求，可重构智能表面（RIS）和非正交多址（NOMA）都被认为是未来通信网络的关键技术。在本文中，构想了一个通用框架，以在存在协调多点 (CoMP) 接收和不完善的连续干扰消除 (SIC) 的情况下提高支持 RIS 的多组 NOMA 网络的传输功率效率。特别地，提出了一种组级SIC（GSIC）方法来消除解码组的干扰以及精心设计的收发器，以减轻聚合干扰，包括组内干扰、由不完善的SIC引起的残余干扰以及干扰的 NOMA 用户稍后解码。根据新框架，通过协同优化发射功率和相移来制定功率最小化问题。为了使问题易于处理，开发了一种交替方案来迭代优化发射功率和相移。具体而言，同组用户的发射功率通过并行迭代算法设计，而相移通过顺序旋转方法进行优化。仿真表明，在每个用户服务质量的约束下，所提出的方案比各种基准方法需要更少的发射功率。开发了一种交替方案来迭代优化发射功率和相移。具体而言，同组用户的发射功率通过并行迭代算法设计，而相移通过顺序旋转方法进行优化。仿真表明，在每个用户服务质量的约束下，所提出的方案比各种基准方法需要更少的发射功率。开发了一种交替方案来迭代优化发射功率和相移。具体而言，同组用户的发射功率通过并行迭代算法设计，而相移通过顺序旋转方法进行优化。仿真表明，在每个用户服务质量的约束下，所提出的方案比各种基准方法需要更少的发射功率。