协同优化无人机航线与通信基站，降低成本并提升连接可靠性。
Co-planning of Flight Corridors and Communication Infrastructure for Urban Drone Logistics Networks
- 基于信道互易性构建动态搜索机制，联合规划基站部署与飞行路径。
- 在复杂城市环境中实现基站减少23%、飞行距离缩短18%的显著优化。
- 适合智能城市空中交通系统规划者和通信基础设施设计人员参考。
在密集城市环境中，可靠的无线连接对城市空中交通（UAM）网络至关重要。现有研究通常独立优化通信基础设施与无人机飞行路径，导致基站过度部署或飞行路线绕行。本文针对复杂城市环境，提出联合优化基站部署与无人机航路的方法，目标是最小化基础设施投资与飞行距离，同时满足通信质量要求。提出CR-CMAB框架：利用三维射线追踪构建高保真无线电图，通过覆盖感知的组合多臂老虎机搜索最优基站组合，并借助信道互易性动态拓展搜索空间以识别潜力基站位置。详细案例研究显示，该方法在中等计算时间下优于基线方法，实现基站部署减少23%、飞行距离缩短18%，且更合理布局基站与航路。本研究为未来智慧城市中低成本、高可靠性的UAM部署提供实用规划视角。
原文摘要 · Abstract (English)
Reliable wireless connectivity is essential for urban air mobility (UAM) networks in dense urban environments. It is therefore imperative to carefully plan the supporting communication infrastructure for UAM flight corridors. Most existing works optimize communication infrastructure and UAV flight paths independently, often leading to unnecessary base station (BS) deployment or excessive flight detours. This paper studies the joint optimization of BS deployment and UAV flight corridors in complex urban environments, aiming to minimize both infrastructure investment and flight distance while satisfying communication quality constraints. We propose CR-CMAB, a channel reciprocity-guided combinatorial multi-armed bandit framework. The framework constructs high-fidelity radio maps using 3D ray tracing, selects BS combinations via coverage-aware CMAB search, and dynamically expands the search space by identifying promising BS locations through channel reciprocity. Experimental results from a detailed case study demonstrate that CR-CMAB outperforms baseline methods with moderate computational time, yielding more strategically positioned BSs and shorter flight corridors. This study offers a practical planning perspective for cost-effective and communication-reliable UAM deployment in future smart cities.
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