37 citations · 39 across the 15 of their papers we have counts for
17 papers
Should I Use This Synthetic Dataset for Training? How to Test with Minimal Real Data
Zhenyu Tao, Wei Xu, Xiaohu You +2
Digital twins (DTs) and learned world models are increasingly used to generate synthetic data that augment the scarce real datasets available for training artificial intelligence (…
Transfer Learning-Enabled Distortion Compensation for Amplitude-Phase-Time Block Modulation-Based Nonlinear Single-Carrier Wireless Communications
Guoxing Duan, Min Fan, Cheng Yi +4
Power amplifier (PA) nonlinearity and memory effects significantly limit the spectral compliance, reliability, and energy efficiency of communication systems. To address this, we p…
Intelligent Base Station Deployment in Urban Wireless Networks: A Geographic Data-Informed Digital Twin Approach
Zhenyu Tao, Yuxuan Li, Wei Xu +2
The placement of base station (BS) is a fundamental determinant of coverage and capacity of urban wireless networks. Yet large-scale BS deployment optimization remains challenging…
A Framework for Learning and Reliability Certification in Neural Polar Decoding
Hongzhi Zhu, Wei Xu, Xiaohu You
This paper investigates a framework that connects network training, independently certified population risk and sequential reliability in neural polar decoding. Network outputs det…
Hierarchy-Guided Multimodal Representation Learning for Taxonomic Inference
Sk Miraj Ahmed, Xi Yu, Yunqi Li +2
Accurate biodiversity identification from large-scale field data is a foundational problem with direct impact on ecology, conservation, and environmental monitoring. In practice, t…
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…
Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks
Zhenyu Tao, Wei Xu, Xiaohu You
Optimization of user association in a densely deployed cellular network is usually challenging and even more complicated due to the dynamic nature of user mobility and fluctuation…
Map2Traj: Street Map Piloted Zero-shot Trajectory Generation with Diffusion Model
Zhenyu Tao, Wei Xu, Xiaohu You
User mobility modeling serves a crucial role in analysis and optimization of contemporary wireless networks. Typical stochastic mobility models, e.g., random waypoint model and Gau…
MSE-Based Training and Transmission Optimization for MIMO ISAC Systems
Zhenyao He, Wei Xu, Hong Shen +2
In this paper, we investigate a multiple-input multiple-output (MIMO) integrated sensing and communication (ISAC) system under typical block-fading channels. As a non-trivial exten…
Wireless Federated Learning over Resource-Constrained Networks: Digital versus Analog Transmissions
Jiacheng Yao, Wei Xu, Zhaohui Yang +3
To enable wireless federated learning (FL) in communication resource-constrained networks, two communication schemes, i.e., digital and analog ones, are effective solutions. In thi…
Unlocking Potentials of Near-Field Propagation: ELAA-Empowered Integrated Sensing and Communication
Zhenyao He, Wei Xu, Zhaohui Yang +5
The exploration of extremely large antenna arrays (ELAAs) using high-frequency spectrum has led to a paradigm shift in electromagnetic radiation field, transitioning from the commo…
Learning Wireless Data Knowledge Graph for Green Intelligent Communications: Methodology and Experiments
Yongming Huang, Xiaohu You, Hang Zhan +3
Intelligent communications have played a pivotal role in shaping the evolution of 6G networks. Native artificial intelligence (AI) within green communication systems must meet stri…