Non-orthogonal multiple access (NOMA)-aided cell-free massive multiple-input multiple-output (CFmMIMO) has been considered as a promising technology to fulfill strict quality of service requirements for ultra-reliable low-latency communications (URLLC). However, finite blocklength coding (FBC) in URLLC makes it challenging to achieve the optimal performance in the NOMA-aided CFmMIMO system. In this paper, we investigate the performance of the NOMA-aided CFmMIMO system with FBC in terms of achievable sum rate (ASR). Firstly, we derive a lower bound (LB) on the ergodic data rate. Then, we formulate an ASR maximization problem by jointly considering power allocation and user equipment (UE) clustering. To tackle such an intractable problem, we decompose it into two sub-problems, i.e., the power allocation problem and the UE clustering problem. A successive convex approximation (SCA) algorithm is proposed to solve the power allocation problem by transforming it into a series of geometric programming problems. Meanwhile, two algorithms based on graph theory are proposed to solve the UE clustering problem by identifying negative loops. Finally, alternative optimization is performed to find the maximum ASR of the NOMA-aided CFmMIMO system with FBC. The simulation results demonstrate that the proposed algorithms significantly outperform the benchmark algorithms in terms of ASR under various scenarios.

翻译：非正交多址接入（NOMA）辅助的无小区大规模多输入多输出（CFmMIMO）系统被认为是一种有望满足超可靠低时延通信（URLLC）严格服务质量要求的技术。然而，URLLC中的有限块长编码（FBC）使得在NOMA辅助CFmMIMO系统中实现最优性能面临挑战。本文研究了采用FBC的NOMA辅助CFmMIMO系统在可达和速率（ASR）方面的性能。首先，我们推导了遍历数据速率的下界（LB）。随后，通过联合考虑功率分配和用户设备（UE）聚类，构建了ASR最大化问题。为求解该棘手问题，将其分解为两个子问题，即功率分配问题和UE聚类问题。提出了一种逐次凸近似（SCA）算法，通过将功率分配问题转化为一系列几何规划问题进行求解。同时，提出两种基于图论的算法，通过识别负环来解决UE聚类问题。最后，通过交替优化来寻找采用FBC的NOMA辅助CFmMIMO系统的最大ASR。仿真结果表明，在不同场景下，所提算法在ASR性能上显著优于基准算法。