低空立体覆盖网络中的关键技术：网络规划与优化

摘要：随着低空经济的蓬勃发展，无人机（UAV）物流、空中巡检及城市空中交通等应用场景对无线通信网络提出了全新的挑战。传统的地面二维网络覆盖已无法满足低空立体空间的通信需求。深入探讨了低空立体覆盖网络中的两大核心环节：网络规划与网络优化。在网络规划方面，介绍了一种基于解耦表征学习的低空网络覆盖预测框架，重点分析了如何利用专家知识与深度学习解决基站波束方向图无法获取以及数据稀疏性问题。在网络优化方面，聚焦于低空通信场景下的覆盖增强策略，重点阐述了初始接入阶段的覆盖场景配置对低空覆盖的影响，以及天线面板角度的优化方法。本研究旨在为构建高效、可靠的低空立体智联网络提供理论依据与技术参考。

关键词：网络优化；网络规划；低空经济；通信网络；天线朝向优化；覆盖场景优化；立体覆盖

Abstract: With the vigorous development of the low-altitude economy, application scenarios such as UAV (unmanned aerial vehicle) logistics, aerial inspection, and urban air mobility pose brand-new challenges to wireless communication networks. Traditional ground-based 2D network coverage can no longer meet the communication needs of the low-altitude 3D space. This paper deeply explores two core links in the low-altitude 3D coverage network: network planning and network optimization. In terms of network planning, this paper presents a low-altitude network coverage prediction framework based on disentangled representation learning, focusing on analyzing how to use expert knowledge and deep learning to solve the problems of unavailable base station beam patterns and data sparsity. In terms of network optimization, this paper focuses on coverage enhancement strategies in low-altitude communication scenarios, elaborating on the impact of coverage scenario configuration on low-altitude coverage during the initial access phase, as well as the optimization mechanism of antenna panel angles. This paper aims to provide a theoretical basis and technical reference for building efficient and reliable low-altitude 3D intelligent networks.

Keywords: network optimization; network planning; low-altitude economy; wireless communication networks; antenna orientation optimization; coverage scenario optimization; 3D coverage