标题： NOMA网络中语义和比特双模用户的功率高效优化 显示英文标题

标题： Power-Efficient Optimization for Coexisting Semantic and Bit-Based Users in NOMA Networks

摘要： 语义通信侧重于传输数据的意义，旨在实现高效、相关的信息传递，而非正交多址接入（NOMA）通过允许多个用户共享同一频谱来提高频谱效率。将基于比特的用户与语义用户集成到NOMA网络中可以同时提升传输效率和频谱效率。然而，语义通信的性能指标与传统通信显著不同，在同时满足单个用户需求和最小化传输功率方面提出了挑战，尤其是在存在语义用户和基于比特的用户的混合场景下。此外，语义用户和基于比特的用户的硬件架构差异使得连续干扰消除（SIC）的实施变得复杂。 为了解决这些挑战，本文提出了一种分簇框架以减轻SIC的复杂性，并提出了两种多址（MA）方案，即纯分簇型NOMA（P-CNOMA）和混合分簇型NOMA（H-CNOMA），以最小化总传输功率。P-CNOMA方案能够实现最低的传输功率，但可能无法满足高质量服务（QoS）要求。相比之下，H-CNOMA在略微增加功率的情况下降低了语义速率，解决了这些问题。这两种方案相互补充，实现了适应特定网络条件和用户需求的自适应MA选择机制。 显示英文摘要

摘要： Semantic communication focuses on transmitting the meaning of data, aiming for efficient, relevant communication, while non-orthogonal multiple access (NOMA) enhances spectral efficiency by allowing multiple users to share the same spectrum. Integrating semantic users into a NOMA network with bit-based users improves both transmission and spectrum efficiency. However, the performance metric for semantic communication differs significantly from that of traditional communication, posing challenges in simultaneously meeting individual user demands and minimizing transmission power, especially in scenarios with coexisting semantic and bit-based users. Furthermore, the different hardware architectures of semantic and bit-based users complicate the implementation of successive interference cancellation (SIC). To address these challenges, in this paper, we propose a clustered framework to mitigate the complexity of SIC and two multiple access (MA) schemes, e.g., pure cluster-based NOMA (P-CNOMA) and hybrid cluster-based NOMA (H-CNOMA), to minimize the total transmission power. The P-CNOMA scheme can achieve the minimum transmission power, but may not satisfy the high quality of service (QoS) requirement. In contrast, H-CNOMA addresses these issues with a slight increase in power and a reduced semantic rate. These two schemes complement each other, enabling an adaptive MA selection mechanism that adapts to specific network conditions and user requirements.