Low-altitude wireless networks (LAWNs) are expected to play a central role in future 6G infrastructures, yet uplink transmissions of uncrewed aerial vehicles (UAVs) remain vulnerable to eavesdropping due to their limited transmit power, constrained antenna resources, and highly exposed air-ground propagation conditions. To address this fundamental bottleneck, we propose a flexible-duplex cell-free (CF) architecture in which each distributed access point (AP) can dynamically operate either as a receive AP for UAV uplink collection or as a transmit AP that generates cooperative artificial noise (AN) for secrecy enhancement. Such AP-level duplex flexibility introduces an additional spatial degree of freedom that enables distributed and adaptive protection against wiretapping in LAWNs. Building upon this architecture, we formulate a max-min secrecy-rate problem that jointly optimizes AP mode selection, receive combining, and AN covariance design. This tightly coupled and nonconvex optimization is tackled by first deriving the optimal receive combiners in closed form, followed by developing a penalty dual decomposition (PDD) algorithm with guaranteed convergence to a stationary solution. To further reduce computational burden, we propose a low-complexity sequential scheme that determines AP modes via a heuristic metric and then updates the AN covariance matrices through closed-form iterations embedded in the PDD framework. Simulation results show that the proposed flexible-duplex architecture yields substantial secrecy-rate gains over CF systems with fixed AP roles. The joint optimization method attains the highest secrecy performance, while the low-complexity approach achieves over 90% of the optimal performance with an order-of-magnitude lower computational complexity, offering a practical solution for secure uplink communications in LAWNs.

翻译：低空无线网络（LAWNs）预计将在未来6G基础设施中发挥核心作用，然而无人驾驶飞行器（UAVs）的上行传输因其有限的发射功率、受限的天线资源以及高度暴露的空地传播条件，仍然容易受到窃听威胁。为突破这一根本性瓶颈，本文提出一种灵活双工无蜂窝（CF）架构，其中每个分布式接入点（AP）均可动态地作为接收AP收集UAV上行信号，或作为发射AP生成协作式人工噪声（AN）以增强保密性。这种AP级的双工灵活性引入了额外的空间自由度，使得LAWNs能够实现分布式自适应防窃听保护。基于该架构，我们构建了一个最大-最小保密速率优化问题，联合优化AP模式选择、接收合并与AN协方差设计。针对这一强耦合非凸优化问题，首先推导出闭式最优接收合并器，进而提出一种具有收敛性保证的惩罚对偶分解（PDD）算法以获得平稳解。为降低计算负担，进一步提出一种低复杂度序贯方案：通过启发式度量确定AP模式，随后在PDD框架内通过闭式迭代更新AN协方差矩阵。仿真结果表明，所提灵活双工架构相比固定AP角色的CF系统可获得显著的保密速率增益。联合优化方法实现了最优保密性能，而低复杂度方案以降低一个数量级的计算复杂度实现了超过90%的最优性能，为LAWNs中的安全上行通信提供了实用解决方案。