3 papers
cs.NI2026
Deep Reinforcement Learning for 6G AI-RAN: A Comprehensive Survey
Jie Lu, Peihao Yan, Qijun Wang +2
The evolution toward sixth-generation (6G) networks is transforming the radio access network (RAN) into a programmable and intelligent control platform that must continuously adapt…
cs.NI2026
Demystifying Deep Reinforcement Learning: A Neuro-Symbolic Framework for Interpretable Open RAN Automation
Jie Lu, Peihao Yan, Pang-Ning Tan +2
Open Radio Access Networks (O-RAN) are increasingly adopting data-driven control through Deep Reinforcement Learning (DRL) to optimize complex tasks such as network slicing and mob…
cs.NI2026
TARMM: Scaling Delay-Critical Edge AI Offloading in 5G O-RAN via Temporal Graph Mobility Management
Peihao Yan, Yun Chen, Jie Lu +2
Emerging delay-critical edge AI applications, such as VR perception and real-time video analytics, impose stringent latency and reliability requirements on 5G networks. However, ex…