POSTER: Simplifying the Networking of Wireless Embedded Systems using a Large Language Model

Wireless embedded systems have seen rapid growth. Nonetheless, the further growth of these systems is now threatened due to the complexities of programming, networking, and deploying them. Developing embedded systems today is a challenging task primarily due to the vast diversity in radio standards, network stacks, microcontrollers, sensors, and other parts of the embedded system ecosystem. This complexity makes it a task suited only for experts, thus hindering the broader adoption of embedded systems.

In this early work, we tackle a particular aspect of this challenge related to the complexities of wireless communication. Specifically, we explore the hypothesis that the emergent properties of large language models could help mitigate the complexities of programming the wireless communication stack. We adopt a complex radio transmitter design based on a backscatter mechanism and explore the generation of the transmitter's logic using state-of-the-art language models. Our exploration leads to insights that, with appropriate prompting, today's state-of-the-art large language models are already capable of generating complex modulation and backscatter logic. This finding warrants further efforts to design language model generated radio transmitters to simplify embedded systems.