9 citations · 9 across the 8 of their papers we have counts for
6 papers · 1 filter
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…
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…
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…
RadEar: A Self-Supervised RF Backscatter System for Voice Eavesdropping and Separation
Qijun Wang, Peihao Yan, Chunqi Qian +1
Eavesdropping on voice conversations presents a growing threat to personal privacy and information security. In this paper, we present RadEar, a novel RF backscatter-based system d…
Integrating Health Sensing into Cellular Networks: Human Sleep Monitoring Using 5G Signals
Ruxin Lin, Peihao Yan, Jie Lu +2
Cellular networks offer a unique opportunity to enable device-free and wide-area health monitoring by exploiting the sensitivity of radio-frequency (RF) propagation to human physio…
xDiff: Online Diffusion Model for Collaborative Inter-Cell Interference Management in 5G O-RAN
Peihao Yan, Huacheng Zeng, Y. Thomas Hou
Open Radio Access Network (O-RAN) is a key architectural paradigm for 5G and beyond cellular networks, enabling the adoption of intelligent and efficient resource management soluti…