The development of 6G/B5G wireless networks, which have requirements that go beyond current 5G networks, is gaining interest from academia and industry. However, to increase 6G/B5G network quality, conventional cellular networks that rely on terrestrial base stations are constrained geographically and economically. Meanwhile, NOMA allows multiple users to share the same resources, which improves the spectral efficiency of the system and has the advantage of supporting a larger number of users. Additionally, by intelligently manipulating the phase and amplitude of both the reflected and transmitted signals, STAR-RISs can achieve improved coverage, increased spectral efficiency, and enhanced communication reliability. However, STAR-RISs must simultaneously optimize the amplitude and phase shift corresponding to reflection and transmission, which makes the existing terrestrial networks more complicated and is considered a major challenging issue. Motivated by the above, we study the joint user pairing for NOMA and beamforming design of Multi-STAR-RISs in an indoor environment. Then, we formulate the optimization problem with the objective of maximizing the total throughput of MUs by jointly optimizing the decoding order, user pairing, active beamforming, and passive beamforming. However, the formulated problem is a MINLP. To address this challenge, we first introduce the decoding order for NOMA networks. Next, we decompose the original problem into two subproblems, namely: 1) MU pairing and 2) Beamforming optimization under the optimal decoding order. For the first subproblem, we employ correlation-based K-means clustering to solve the user pairing problem. Then, to jointly deal with beamforming vector optimizations, we propose MAPPO, which can make quick decisions in the given environment owing to its low complexity.

翻译：6G/B5G无线网络的发展需求超越现有5G网络，正引起学术界和工业界的广泛关注。然而，为提升6G/B5G网络质量，依赖地面基站的传统蜂窝网络在地理和经济层面均受限制。与此同时，NOMA技术允许多个用户共享相同资源，可提升系统频谱效率并支持更多用户接入。此外，通过智能调控反射与透射信号的相位和幅度，STAR-RIS能够改善覆盖范围、提升频谱效率及通信可靠性。但STAR-RIS需同时优化反射与透射对应的幅度和相移，这使得现有地面网络更加复杂，成为重大挑战课题。基于上述问题，本文研究了室内环境下NOMA联合用户配对及多STAR-RIS波束赋形设计。随后构建优化问题，旨在通过联合优化解码顺序、用户配对、主动波束赋形及被动波束赋形最大化用户总吞吐量。该问题被表述为混合整数非线性规划。针对此挑战，本文首先引入NOMA网络解码顺序，继而将原问题分解为两个子问题：1）用户配对与2）最优解码顺序下的波束赋形优化。针对第一个子问题，采用基于相关性的K-means聚类方法解决用户配对问题。为联合处理波束赋形向量优化，我们提出MAPPO算法，该算法凭借低复杂度可在给定环境中快速决策。