Large Language Model Aided Integrated Sensing and Communication for Low-Altitude Economy

The rapid expansion of the low-altitude economy (LAE) necessitates robust and intelligent integrated sensing and communication (ISAC) systems. These systems are critical for managing dense airspace, ensuring safe navigation of drones and electric vertical take-off and landing (eVTOL), and delivering seamless data services. This paper explores the transformative potential of large language models (LLMs) in advancing ISAC technologies for LAE applications. LLMs, with their profound capabilities in contextual understanding, multi-modal data fusion, and probabilistic reasoning, can be leveraged to interpret complex sensing data, optimize communication resources, and facilitate intelligent decision-making in dynamic environments. As a concrete example, we introduce an LLM-based multi-scale three-dimensional (3D) localization framework. This algorithm utilizes an LLM as a cognitive engine to integrate and analyze the acquired data streams and is capable of providing multi-scale positioning for unmanned aerial vehicles (UAVs). Moreover, we outline a number of key technical challenges as well as potential solutions associated with LLM-aided ISAC for LAE.