In recent years, semantic communication is progressively emerging as an effective means of facilitating intelligent and context-aware communication. However, current researches seldom simultaneously consider the reliability and timeliness of semantic communication, where scheduling and resource allocation (SRA) plays a crucial role. In contrast, conventional age-based approaches cannot seamlessly extend to semantic communication due to their oversight of semantic importance. To bridge this gap, we introduce a novel metric: Age of Semantic Importance (AoSI), which adaptly captures both the freshness of information and its semantic importance. Utilizing AoSI, we formulate an average AoSI minimization problem by optimizing multi-source SRA. To address this problem, we proposed a AoSI-aware joint SRA algorithm based on Deep Q-Network (DQN). Simulation results validate the effectiveness of our proposed method, demonstrating its ability to facilitate timely and reliable semantic communication.

翻译：近年来，语义通信逐渐成为一种促进智能且上下文感知通信的有效手段。然而，现有研究很少同时考虑语义通信的可靠性和时效性，而调度与资源分配在其中扮演关键角色。相比之下，传统的基于年龄的方法因忽视语义重要性，无法无缝扩展到语义通信。为弥补这一差距，我们引入了一种新指标：语义重要性年龄，它能自适应地捕捉信息的新鲜度及其语义重要性。利用语义重要性年龄，我们通过优化多源调度与资源分配构建了一个平均语义重要性年龄最小化问题。为解决该问题，我们提出了一种基于深度Q网络的语义重要性年龄感知联合调度与资源分配算法。仿真结果验证了所提方法的有效性，表明其能够支持及时且可靠的语义通信。