142 citations · 487 across the 83 of their papers we have counts for
21 papers · 1 filter
NetWorld: Communication-Based Diffusion World Model for Multi-Agent Reinforcement Learning in Wireless Networks
Kechen Meng, Rongpeng Li, Yansha Deng +2
As wireless communication networks grow in scale and complexity, diverse resource allocation tasks become increasingly critical. Multi-Agent Reinforcement Learning (MARL) provides…
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…
Conditional Diffusion Model with OOD Mitigation as High-Dimensional Offline Resource Allocation Planner in Clustered Ad Hoc Networks
Kechen Meng, Sinuo Zhang, Rongpeng Li +3
Due to network delays and scalability limitations, clustered ad hoc networks widely adopt Reinforcement Learning (RL) for on-demand resource allocation. Albeit its demonstrated agi…
LLM4MAC: An LLM-Driven Reinforcement Learning Framework for MAC Protocol Emergence
Renxuan Tan, Rongpeng Li, Zhifeng Zhao
With the advent of 6G systems, emerging hyper-connected ecosystems necessitate agile and adaptive medium access control (MAC) protocols to contend with network dynamics and diverse…
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…
RHFedMTL: Resource-Aware Hierarchical Federated Multi-Task Learning
Xingfu Yi, Rongpeng Li, Chenghui Peng +3
The rapid development of artificial intelligence (AI) over massive applications including Internet-of-things on cellular network raises the concern of technical challenges such as…