4 papers
LLM-Empowered Agentic MAC Protocols: A Dynamic Stackelberg Game Approach
Renxuan Tan, Rongpeng Li, Fei Wang +4
Medium Access Control (MAC) protocols, essential for wireless networks, are typically manually configured. While deep reinforcement learning (DRL)-based protocols enhance task-spec…
Optimizing NetGPT via Routing-Based Synergy and Reinforcement Learning
Yuxuan Chen, Rongpeng Li, Xianfu Chen +4
Large language model (LLM) agents at the network edge offer low-latency execution for routine queries. In contrast, complex requests often require the superior capability of cloud…
Overview of AI and Communication for 6G Network: Fundamentals, Challenges, and Future Research Opportunities
Qimei Cui, Xiaohu You, Ni Wei +22
With the growing demand for seamless connectivity and intelligent communication, the integration of artificial intelligence (AI) and sixth-generation (6G) communication networks ha…
Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G
Xiaoxue Yu, Xingfu Yi, Rongpeng Li +4
In the evolution towards 6G, integrating Artificial Intelligence (AI) with advanced network infrastructure emerges as a pivotal strategy for enhancing network intelligence and reso…