Semantic Communication for Low-Altitude Economy: Harnessing the Power of Generative AI and Edge Intelligence

With the rapid development of the low-altitude economy (LAE), low-altitude wireless networks (LAWNs) are emerging as critical infrastructure for a wide range of applications, including urban inspection and intelligent logistics. To support these emerging services, LAWNs must ensure efficient data transmission, low latency, and adaptive service delivery, yet they remain constrained by limited onboard resources and unstable communication links. Semantic communication (SemCom), which transmits the meaning of data rather than raw data itself, offers potential solutions but faces implementation challenges. Integrating generative artificial intelligence (GAI) models with low-altitude SemCom networks provides a possible solution to address these issues by efficiently generating and interpreting multi-modal data, reducing transmission needs, enhancing reliability, and enabling personalized communication. This paper provides a comprehensive review of low-altitude SemCom network architecture, explores GAI applications in low-altitude SemCom, and presents a real-world case study demonstrating how the synergy of GAI, SemCom, and edge intelligence enables task-oriented unmanned aerial vehicle inspection image backhauling in LAE scenarios.