AI 中文总结
研究复杂城市环境中基站部署与无人机飞行走廊联合优化问题，提出CR-CMAB框架，利用3D射线追踪、覆盖感知搜索和信道互易性动态扩展搜索空间，实验表明该框架能在适度计算时间内优化部署，提供实用规划视角。
AI 中文摘要
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，因此必须精心规划UAM飞行走廊的支持通信基础设施。现有工作大多独立优化通信基础设施和无人机飞行路径，常导致不必要的基站部署或过多飞行绕行。本文研究复杂城市环境中基站部署和无人机飞行走廊的联合优化，以在满足通信质量约束的同时最小化基础设施投资和飞行距离。我们提出CR-CMAB，一种信道互易性引导的组合多臂老虎机框架。该框架利用3D射线追踪构建高保真无线电地图，通过覆盖感知的CMAB搜索选择基站组合，并通过信道互易性识别有前景的基站位置来动态扩展搜索空间。详细案例研究的实验结果表明，CR-CMAB在适度计算时间内优于基线方法，能产生更具战略位置的基站和更短的飞行走廊。本研究为未来智慧城市中经济高效且通信可靠的UAM部署提供了实用的规划视角。
英文摘要
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.
Comments13 pages, 8 figures, preprint
