Generative Artificial Intelligence for Beamforming in Low-Altitude Economy

The growth of low-altitude economy (LAE) has driven a rising demand for efficient and secure communications. However, conventional beamforming optimization techniques struggle in the complex LAE environments. In this context, generative artificial intelligence (GenAI) methods provide a promising solution. In this article, we first introduce the core concepts of LAE and the roles of beamforming in advanced communication technologies for LAE. We then examine their interrelation, followed by an analysis of the limitations of conventional beamforming methods. Next, we provide an overview of how GenAI methods enhance the process of beamforming with a focus on its applications in LAE. Furthermore, we present a case study using a generative diffusion model (GDM)-based algorithm to enhance the performance of collaborative beamforming-enabled secure communications in LAE and simulation results demonstrate that our approach achieves 23% improvement in terms of secrecy rate and 18% reduction in energy consumption compared to baseline algorithms. Finally, promising research opportunities are identified.