Low-Altitude Economy Networks (LAENets) have emerged as a critical communication paradigm for operation-critical and regulation-aware applications, where Unmanned Aerial Vehicles (UAVs) transmit task-related information under stringent low-probability-of-detection constraints. These constraints severely limit the available transmission power and bandwidth, rendering conventional bit-level communication inefficient when task performance depends on high-level semantic understanding rather than raw data fidelity. Fortunately, Semantic Communication (SemCom) can be a promising solution by prioritizing task-relevant information over bit-level accuracy. However, different levels of semantic abstraction inherently introduce different degrees of information loss and redundancy, which may either compromise task reliability or incur excessive transmission overhead if not properly controlled. To this end, we propose an incentive-aware semantic entropy control framework for covert communications in LAENets. Specifically, we regulate semantic uncertainty at the receiver by adjusting the semantic abstraction level at the UAV side, thereby enabling reliable task information delivery under extreme covert constraints. Since the Base Station (BS) cannot directly observe the semantic processing capabilities and abstraction-dependent transmission costs of UAVs, information asymmetry naturally arises in SemCom service provision. Accordingly, we propose a contract theoretic model, where we adopt Prospect Theory (PT) to capture the subjective utility of the BS toward personalized semantic services. Furthermore, we design a Regularized Diffusion-based Soft Actor-Critic (RDSAC) algorithm for optimal contract design under PT. This algorithm enhances contract design by introducing diffusion entropy regularization together with action entropy regularization.

翻译：低空经济网络已成为关键任务与监管敏感应用中的关键通信范式，其中无人机需在严格的低检测概率约束下传输任务相关信息。这些约束严重限制了可用传输功率与带宽，使得当任务性能依赖于高层语义理解而非原始数据保真度时，传统比特级通信效率低下。幸运的是，语义通信通过优先传输任务相关信息而非追求比特级精度，可成为一种极具前景的解决方案。然而，不同层级的语义抽象天然引入不同程度的信息损失与冗余，若控制不当，可能损害任务可靠性或导致过高的传输开销。为此，本文提出一种面向低空经济网络隐蔽通信的激励感知语义熵控制框架。具体而言，我们通过调整无人机端的语义抽象层级来调控接收端的语义不确定性，从而在极端隐蔽约束下实现可靠的任务信息传递。由于基站无法直接观测无人机的语义处理能力及依赖抽象层级的传输成本，语义通信服务提供中自然存在信息不对称问题。据此，我们提出一种合约理论模型，其中采用前景理论来刻画基站对个性化语义服务的主观效用。进一步，我们设计了一种基于正则化扩散的柔性演员-评论家算法，用于在前景理论下实现最优合约设计。该算法通过引入扩散熵正则化与动作熵正则化，增强了合约设计的性能。