Uncrewed aerial vehicles (UAVs) have played an important role in the low-altitude economy and have been used in various applications. However, with the increasing number of UAVs and explosive wireless data, the existing bit-oriented communication network has approached the Shannon capacity, which cannot satisfy the quality of service (QoS) with ultra-reliable low-latency communication (URLLC) requirements for command and control (C\&C) transmission in bit-oriented UAV communication networks. To address this issue, we propose a novel semantic-aware C\&C transmission for multi-UAVs under limited wireless resources. Specifically, we leverage semantic similarity to measure the variation in C\&C messages for each UAV over continuous transmission time intervals (TTIs) and capture the correlation of C\&C messages among UAVs, enabling multicast transmission. Based on the semantic similarity and the importance of UAV commands, we design a trigger function to quantify the QoS of UAVs. Then, to maximize the long-term QoS and exploit multicast opportunities of C\&C messages induced by semantic similarity, we develop a proximal policy optimization (PPO) algorithm to jointly determine the transmission mode (unicast/multicast/idle) and the allocation of limited resource blocks (RBs) between a base station (BS) and UAVs. Experimental results show that our proposed semantic-aware framework significantly increases transmission efficiency and improves effectiveness compared with bit-oriented UAV transmission.

翻译：无人机在低空经济中扮演着重要角色，并已被广泛应用于各类场景。然而，随着无人机数量的激增和无线数据的爆炸式增长，现有面向比特的通信网络已接近香农容量极限，无法满足面向比特的无人机通信网络中指挥控制传输对超可靠低时延通信的服务质量要求。为解决这一问题，我们提出了一种在有限无线资源下面向多无人机的新型语义感知指挥控制传输方案。具体而言，我们利用语义相似度来衡量每架无人机在连续传输时间间隔内指挥控制消息的变化，并捕获无人机间指挥控制消息的关联性，从而实现组播传输。基于语义相似度与无人机指令的重要性，我们设计了一个触发函数来量化无人机的服务质量。随后，为最大化长期服务质量并利用语义相似度带来的指挥控制消息组播机会，我们开发了一种近端策略优化算法，以联合确定基站与无人机之间的传输模式（单播/组播/空闲）及有限资源块的分配。实验结果表明，与面向比特的无人机传输方案相比，我们提出的语义感知框架显著提升了传输效率并改善了传输效果。