标题： 非正交多址接入网络中共存语义和基于比特的用户的节能优化 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，专注于传输数据的语义含义，已被提出作为一种新范式，以实现高效且相关的通信。 同时，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。 然而，由于后者仍占主导地位，语义通信在不久的将来不太可能完全取代传统的比特级通信。 因此，将语义用户集成到与传统基于比特的用户一起的 NOMA 网络中，成为一种有意义的方法，以提高传输和频谱效率。 然而，由于缺乏一个能准确描述语义收发器性能与无线资源分配之间关系的数学模型，通过资源优化来提升性能仍然是一个挑战。 此外，连续干扰消除（SIC），NOMA 中的一项关键技术，给系统设计和实现带来了额外的复杂性。 为了解决这些挑战，本文首先改进了深度语义通信（DeepSC）收发器，使其适应变化的无线传输条件。 随后，采用数据驱动的回归方法开发一个数学模型，以捕捉无线资源对语义收发器性能的影响。 同时，提出了一种多簇混合 NOMA（H-NOMA）框架，其中每个簇由一个语义用户和一个基于比特的用户组成，以减轻 SIC 引入的复杂性。 然后，通过联合优化波束成形设计、带宽分配和语义符号因子，制定了一个总发射功率最小化问题。 显示英文摘要

摘要： Semantic communications, which focus on transmitting the semantic meaning of data, have been proposed as a novel paradigm for achieving efficient and relevant communication. Meanwhile, non-orthogonal multiple access (NOMA) enhances spectral efficiency by allowing multiple users to share the same spectrum. However, semantic communications are unlikely to fully replace conventional bit-level communications in the near future, as the latter remain dominant. Therefore, integrating semantic users into a NOMA network alongside conventional bit-based users becomes a meaningful approach to improve both transmission and spectrum efficiency. Nonetheless, due to the lack of a mathematical model that accurately characterizes the relationship between the performance of semantic transceivers and wireless resource allocation, enhancing performance through resource optimization remains a challenge. Moreover, successive interference cancellation (SIC), a key technique in NOMA, introduces additional complexity in system design and implementation. To address these challenges, this paper first improves the deep semantic communication (DeepSC) transceiver to make it adaptive to varying wireless transmission conditions. Subsequently, a data-driven regression approach is employed to develop a mathematical model that captures the impact of wireless resources on semantic transceiver performance. In parallel, a multi-cluster hybrid NOMA (H-NOMA) framework is proposed, where each cluster consists of one semantic user and one bit-based user, to mitigate the complexity introduced by SIC. A total transmit power minimization problem is then formulated by jointly optimizing the beamforming design, bandwidth allocation, and semantic symbol factor.