37 citations · 39 across the 15 of their papers we have counts for
6 papers · 1 filter
A Theoretical Analysis of State Similarity Between Markov Decision Processes
Zhenyu Tao, Wei Xu, Xiaohu You
The bisimulation metric (BSM) is a powerful tool for analyzing state similarities within a Markov decision process (MDP), revealing that states closer in BSM have more similar opti…
Two-Stage Signal Reconstruction for Amplitude-Phase-Time Block Modulation-based Communications
Meidong Xia, Min Fan, Wei Xu +2
Operating power amplifiers (PAs) at lower input back-off (IBO) levels is an effective way to improve PA efficiency, but often introduces severe nonlinear distortion that degrades t…
Toward Trustworthy Digital Twins in AI Agent-based Wireless Network Optimization: Challenges, Solutions, and Opportunities
Zhenyu Tao, Wei Xu, Xiaohu You
Optimizing modern wireless networks is exceptionally challenging due to their high dynamism and complexity. While the AI agent powered by reinforcement learning (RL) offers a promi…
A Generalized Bisimulation Metric of State Similarity between Markov Decision Processes: From Theoretical Propositions to Applications
Zhenyu Tao, Wei Xu, Xiaohu You
The bisimulation metric (BSM) is a powerful tool for computing state similarities within a Markov decision process (MDP), revealing that states closer in BSM have more similar opti…
Provable Performance Bounds for Digital Twin-driven Deep Reinforcement Learning in Wireless Networks: A Novel Digital-Twin Bisimulation Metric
Zhenyu Tao, Wei Xu, Xiaohu You
Digital twin (DT)-driven deep reinforcement learning (DRL) has emerged as a promising paradigm for wireless network optimization, offering safe and efficient training environment f…
Combating Interference for Over-the-Air Federated Learning: A Statistical Approach via RIS
Wei Shi, Jiacheng Yao, Wei Xu +4
Over-the-air computation (AirComp) integrates analog communication with task-oriented computation, serving as a key enabling technique for communication-efficient federated learnin…