Scope & Topics

As a powerful branch of artificial intelligence (AI), generative AI has emerged as a concept for innovative AI algorithms that are capable of generating human-like content, including text, images, videos, etc., setting the scene for a new era of intelligent self-governed machines. As a unique field within the generative AI paradigm, large language models (LLMs) hold a significant promise in reshaping the future of intelligence. The rapid evolution of large language models (LLMs) has brought revolutionary changes to various domains, and the wireless networking landscape is no exception. Recently, LLMs have been proposed to leverage their immense potential in transforming traditional wireless networks into intelligent, efficient, and autonomous communication systems. In particular, by harnessing the power of LLMs, we can revolutionize the design, optimization, and management of wireless networks, paving the way for robust and intelligent connectivity solutions. 

The aim of this workshop is to advance the research in the emerging field of "Large Language Models for Wireless Networks," exploring the opportunities, challenges, and future directions for leveraging these powerful language models in the realm of wireless communications. The papers of this workshop will contribute to advancing the understanding and adoption of LLMs in revolutionizing the wireless communication infrastructure, paving the way for a smarter, more efficient, and inclusive wireless future. It is worthy to note that the research on the interplay of LLM and wireless networks is relatively new and has not been well investigated in the recent literature, and therefore, this workshop aims to promote the research on this field, and to bring together contributors from academia and industry to present their vision on Telecom LLM. It further opens the floor for interactive live discussions among highly skilled researchers (through its panel discussion) in order to explore the potentials realized when integrating the LLM paradigm in the design and optimization of future wireless networks. 

Topics of interest include, but are not limited to:

• LLMs for wireless sensing.

• LLMs for wireless transmission.

• Improved beamforming and handover through LLMs.

• Security and privacy in LLMs Telecom.

• LLMs for network fault diagnosis and troubleshooting.

• LLMs for resource allocation and quality of service optimization.

• LLMs for network performance prediction.

• LLMs for network protocol design.

• LLMs for spectrum management.

• Network configuration and optimization through LLMs.

• Telecom LLM benchmarking.

• LLMs for Self-Synthesizing Networks.

• LLMs in wireless standards.

• Wireless Networks for LLMs.

• Machine-to-machine LLM.

• Multimodal Telecom LLM.