中图分类号：TN929.5 文献标志码：A DOI: 10.16157/j.issn.0258-7998.256278
中文引用格式： 薄云鹏，亢抗，潘桂新，等. 一种基于PPO算法的低空基站优化模型[J]. 电子技术应用，2025，51(7)：60-64.
英文引用格式： Bo Yunpeng，Kang Kang，Pan Guixin，et al. A low-altitude base station optimization model based on PPO algorithm[J]. Application of Electronic Technique，2025，51(7)：60-64.

A low-altitude base station optimization model based on PPO algorithm

Abstract： Optimizing existing terrestrial network base stations to provide low-altitude network services offers advantages such as cost-effectiveness and rapid deployment. Facing challenges in the optimization process of low-altitude base stations, including complex wireless environments, diverse configuration parameters, and interrelated optimization objectives, this paper proposes a multidimensional low-altitude network base station optimization model based on the Proximal Policy Optimization (PPO) algorithm. By employing ray tracing technology, the model calculates the low-altitude coverage capability of base stations with different types and angles. It constructs an optimization model that supports multiple objectives and parameter configurations for low-altitude network base stations. The PPO algorithm is utilized to derive base station configuration strategies, which are then trained and validated in a simulated environment. This demonstrates that the model can effectively generate optimization schemes for base stations and exhibits faster convergence speed and better optimization results compared to models based on the Actor-Critic (A2C) method.

Key words : low-altitude base station；low-altitude communication；PPO；reinforcement learning