56 citations · 101 across the 29 of their papers we have counts for
32 papers
DeepTelecom: A Differentiable Multimodal Framework for Channel Twinning in Dynamic Heterogeneous Wireless Environments
Bohao Wang, Tianen Yuan, William Yen +12
Large-scale multimodal data are a key enabler for integrating large generative artificial intelligence models into wireless networks. However, existing wireless datasets offer limi…
TelecomGPT-R1: Unified Post-Training for Reasoning Across Heterogeneous Telecom Tasks
Bohao Wang, Chenwei Wu, Hang Zou +7
Large language models (LLMs) offer great potential to automate a broad range of telecom engineering tasks by reasoning over standards, network configurations, mathematical models,…
TelecomGPT-R1: A Unified Open-Source Reasoner for the Telecom Stack
Bohao Wang, Chenwei Wu, Haoyu Li +8
Telecommunications is a high-leverage domain for large language model (LLM)-based reasoning because routine engineering workflows require joint grounding in normative specification…
QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks
Zhihan Zeng, Kaihe Wang, Zhongpei Zhang +1
Static radio maps provide location-dependent propagation priors, but they cannot capture short-term blockage caused by moving objects. Direct sensing-assisted beam prediction is al…
Full-Domain Coupler: A Wireless Native Neural Backbone for Channel Representation and Deduction
Zirui Chen, Ziqing Xing, Zhaoyang Zhang +5
Data representation is a fundamental issue in deep learning. However, as wireless data scales and deeply couples across many physical domains such as time, space, and frequency, ex…
Deep Mixture of Experts Network for Resource Optimization in Aerial-Terrestrial CF-mMIMO Systems under URLLC
Donggen Li, Chong Huang, Jingfu Li +4
As a critical component of sixth-generation (6G) wireless networks, ultra-reliable and low-latency communication (URLLC) is expected to support real-time and reliable information e…
P-Flow: Proxy-gradient Flows for Linear Inverse Problems
Zehua Jiang, Fenghao Zhu, Xinquan Wang +2
Generative models based on flow matching have emerged as a powerful paradigm for inverse problems, offering straighter trajectories and faster sampling compared to diffusion models…
Seeing Radio: From Zero RF Priors to Explainable Modulation Recognition with Vision Language Models
Hang Zou, Bohao Wang, Yu Tian +4
Current RF machine-learning pipelines rely on task-specific deep networks for modulation classification and related tasks, but these models require custom architectures and labeled…
Physics-Inspired Target Shape Detection and Reconstruction in mmWave Communication Systems
Ziqing Xing, Zhaoyang Zhang, Xin Tong +2
The integration of sensing and communication (ISAC) is an essential function of future wireless systems. Due to its large available bandwidth, millimeter-wave (mmWave) ISAC systems…
One-Step Generative Channel Estimation via Average Velocity Field
Zehua Jiang, Fenghao Zhu, Siming Jiang +5
Generative models have shown immense potential for wireless communication by learning complex channel data distributions. However, the iterative denoising process associated with t…
Recursive Flow: A Generative Framework for MIMO Channel Estimation
Zehua Jiang, Fenghao Zhu, Chongwen Huang +5
Channel estimation is a fundamental challenge in massive multiple-input multiple-output systems, where estimation accuracy governs the spectral efficiency and link reliability. In…
Toward Efficient and Privacy-Aware eHealth Systems: An Integrated Sensing, Computing, and Semantic Communication Approach
Yinchao Yang, Yahao Ding, Zhaohui Yang +4
Real-time and contactless monitoring of vital signs, such as respiration and heartbeat, alongside reliable communication, is essential for modern healthcare systems, especially in…
Agentic AI for Low-Altitude Semantic Wireless Networks: An Energy Efficient Design
Zhouxiang Zhao, Ran Yi, Yihan Cang +5
This letter addresses the energy efficiency issue in unmanned aerial vehicle (UAV)-assisted autonomous systems. We propose a framework for an agentic artificial intelligence (AI)-p…
DeepTelecom: A Digital-Twin Deep Learning Dataset for Channel and MIMO Applications
Bohao Wang, Zehua Jiang, Zhenyu Yang +9
Domain-specific datasets are the foundation for unleashing artificial intelligence (AI)-driven wireless innovation. Yet existing wireless AI corpora are slow to produce, offer limi…
Unified Design of Space-Air-Ground-Sea Integrated Maritime Communications
Zhehan Zhou, Xiaoming Chen, Ming Ying +4
With the explosive growth of maritime activities, it is expected to provide seamless communications with quality of service (QoS) guarantee over broad sea area. In the context, thi…
ICWLM: A Multi-Task Wireless Large Model via In-Context Learning
Yuxuan Wen, Xiaoming Chen, Maojun Zhang +3
The rapid evolution of wireless communication technologies, particularly massive multiple-input multiple-output (mMIMO) and millimeter-wave (mmWave), introduces significant network…
Bridging Physical and Digital Worlds: Embodied Large AI for Future Wireless Systems
Xinquan Wang, Fenghao Zhu, Zhaohui Yang +5
Large artificial intelligence (AI) models offer revolutionary potential for future wireless systems, promising unprecedented capabilities in network optimization and performance. H…
Integrated Sensing, Computing and Semantic Communication for Vehicular Networks
Yinchao Yang, Zhaohui Yang, Chongwen Huang +4
This paper introduces a novel framework for integrated sensing, computing, and semantic communication (ISCSC) within vehicular networks comprising a roadside unit (RSU) and multipl…
Robust Deep Learning-Based Physical Layer Communications: Strategies and Approaches
Fenghao Zhu, Xinquan Wang, Chen Zhu +6
Deep learning (DL) has emerged as a transformative technology with immense potential to reshape the sixth-generation (6G) wireless communication network. By utilizing advanced algo…
Wireless large AI model: shaping the AI-empowered future of 6G and beyond
Fenghao Zhu, Xinquan Wang, Siming Jiang +22
The emergence of sixth-generation and beyond communication systems is expected to fundamentally transform digital experiences through introducing unparalleled levels of intelligenc…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
Entropy-and-Channel-Aware Adaptive-Rate Semantic Communication with MLLM-Aided Feature Compensation
Weixuan Chen, Qianqian Yang, Yuhao Chen +4
Despite the transmission efficiency gains of semantic communication (SemCom) over traditional methods, most existing SemCom schemes still operate at a fixed transmission rate regar…
Generative AI Empowered Semantic Feature Multiple Access (SFMA) Over Wireless Networks
Jiaxiang Wang, Yinchao Yang, Zhaohui Yang +4
This paper investigates a novel generative artificial intelligence (GAI) empowered multi-user semantic communication system called semantic feature multiple access (SFMA) for video…
E-Healthcare Systems: Integrated Sensing, Computing, and Semantic Communication with Physical Layer Security
Yinchao Yang, Zhaohui Yang, Weijie Yuan +5
This paper introduces an integrated sensing, computing, and semantic communication (ISCSC) framework tailored for smart healthcare systems. The framework is evaluated in the contex…