标题： 语义通信网络中的联合用户关联与带宽分配 显示英文标题

标题： Joint User Association and Bandwidth Allocation in Semantic Communication Networks

摘要： 语义通信（SemCom）最近被认为是一种有前途的解决方案，以保证未来无线网络的高资源利用率和传输可靠性。 然而，独特的背景知识匹配需求使得在语义通信启用的网络（SC-Nets）中实现多用户的高效无线资源管理具有挑战性。 为此，本文从网络的角度研究语义通信，其中系统地解决了SC-Net中的两个基本问题，即用户关联（UA）和带宽分配（BA）。 首先，考虑到移动用户与关联基站之间不同的知识匹配状态，我们确定了两种一般的SC-Net场景，即基于完美知识匹配的SC-Net和基于不完美知识匹配的SC-Net。 随后，针对每种SC-Net场景，我们从语义信息论的角度描述其独特的语义信道模型，从而提出了一种比特率到消息率转换的概念以及一个新的语义层指标，即消息中的系统吞吐量（STM），以衡量整体网络性能。 通过这种方式，我们随后为每种SC-Net场景制定了UA和BA的联合STM最大化问题，并提出了相应的最优解。 两种场景中的数值结果表明，与两个基准相比，我们的解决方案在STM性能方面表现出显著的优势和可靠性。 显示英文摘要

摘要： Semantic communication (SemCom) has recently been considered a promising solution to guarantee high resource utilization and transmission reliability for future wireless networks. Nevertheless, the unique demand for background knowledge matching makes it challenging to achieve efficient wireless resource management for multiple users in SemCom-enabled networks (SC-Nets). To this end, this paper investigates SemCom from a networking perspective, where two fundamental problems of user association (UA) and bandwidth allocation (BA) are systematically addressed in the SC-Net. First, considering varying knowledge matching states between mobile users and associated base stations, we identify two general SC-Net scenarios, namely perfect knowledge matching-based SC-Net and imperfect knowledge matching-based SC-Net. Afterward, for each SC-Net scenario, we describe its distinctive semantic channel model from the semantic information theory perspective, whereby a concept of bit-rate-to-message-rate transformation is developed along with a new semantics-level metric, namely system throughput in message (STM), to measure the overall network performance. In this way, we then formulate a joint STM-maximization problem of UA and BA for each SC-Net scenario, followed by a corresponding optimal solution proposed. Numerical results in both scenarios demonstrate significant superiority and reliability of our solutions in the STM performance compared with two benchmarks.