109 citations · 246 across the 32 of their papers we have counts for
35 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…
Diffusion Inpainting MIMO-OFDM Channels with Limited Noisy Observations
Weijie Zhou, Zhaoyang Zhang, Yuzhi Yang +3
Acquiring the channel state information from limited and noisy observations at pilot positions is critical for wireless multiple-input multiple-output (MIMO)-orthogonal frequency d…
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…
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…
Dynamical Multimodal Fusion with Mixture-of-Experts for Localizations
Bohao Wang, Zitao Shuai, Fenghao Zhu +6
Multimodal fingerprinting is a crucial technique to sub-meter 6G integrated sensing and communications (ISAC) localization, but two hurdles block deployment: (i) the contribution e…
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…
TeleMoM: Consensus-Driven Telecom Intelligence via Mixture of Models
Xinquan Wang, Fenghao Zhu, Chongwen Huang +5
Large language models (LLMs) face significant challenges in specialized domains like telecommunication (Telecom) due to technical complexity, specialized terminology, and rapidly e…
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…
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…
Electromagnetic Channel Modeling and Capacity Analysis for HMIMO Communications
Li Wei, Shuai S. A. Yuan, Chongwen Huang +6
Advancements in emerging technologies, e.g., reconfigurable intelligent surfaces and holographic MIMO (HMIMO), facilitate unprecedented manipulation of electromagnetic (EM) waves,…
Multi-Sources Fusion Learning for Multi-Points NLOS Localization in OFDM System
Bohao Wang, Zitao Shuai, Chongwen Huang +7
Accurate localization of mobile terminals is a pivotal aspect of integrated sensing and communication systems. Traditional fingerprint-based localization methods, which infer coord…
Exploring Hannan Limitation for 3D Antenna Array
Ran Ji, Chongwen Huang, Xiaoming Chen +6
Hannan Limitation successfully links the directivity characteristics of 2D arrays with the aperture gain limit, providing the radiation efficiency upper limit for large 2D planar a…
FedsLLM: Federated Split Learning for Large Language Models over Communication Networks
Kai Zhao, Zhaohui Yang, Chongwen Huang +2
Addressing the challenges of deploying large language models in wireless communication networks, this paper combines low-rank adaptation technology (LoRA) with the splitfed learnin…
RIS-assisted Coverage Enhancement in mmWave Integrated Sensing and Communication Networks
Xu Gan, Chongwen Huang, Zhaohui Yang +6
Integrated sensing and communication (ISAC) has emerged as a promising technology to facilitate high-rate communications and super-resolution sensing, particularly operating in the…
Exploring Channel Estimation and Signal Detection for ODDM-based ISAC Systems
Dezhi Wang, Chongwen Huang, Lei Liu +5
Inspired by providing reliable communications for high-mobility scenarios, in this letter, we investigate the channel estimation and signal detection in integrated sensing and comm…
Beamforming Inferring by Conditional WGAN-GP for Holographic Antenna Arrays
Fenghao Zhu, Xinquan Wang, Chongwen Huang +5
The beamforming technology with large holographic antenna arrays is one of the key enablers for the next generation of wireless systems, which can significantly improve the spectra…
Exploiting Matrix Information Geometry for Integrated Decoding of Massive Uncoupled Unsourced Random Access
Feiyan Tian, Xiaoming Chen, Chongwen Huang +1
In this paper, we explore an efficient uncoupled unsourced random access (UURA) scheme for 6G massive communication. UURA is a typical framework of unsourced random access that add…
Electromagnetic Information Theory for Holographic MIMO Communications
Li Wei, Tierui Gong, Chongwen Huang +6
Holographic multiple-input multiple-output (HMIMO) utilizes a compact antenna array to form a nearly continuous aperture, thereby enhancing higher capacity and more flexible config…
Robust Beamforming with Gradient-based Liquid Neural Network
Xinquan Wang, Fenghao Zhu, Chongwen Huang +5
Millimeter-wave (mmWave) multiple-input multiple-output (MIMO) communication with the advanced beamforming technologies is a key enabler to meet the growing demands of future mobil…
Robust Continuous-Time Beam Tracking with Liquid Neural Network
Fenghao Zhu, Xinquan Wang, Chongwen Huang +6
Millimeter-wave (mmWave) technology is increasingly recognized as a pivotal technology of the sixth-generation communication networks due to the large amounts of available spectrum…
Low-Complexity Beam Training for Multi-RIS-Assisted Multi-User Communications
Yuan Xu, Chongwen Huang, Li Wei +5
In this paper, we investigate the beam training problem in the multi-user millimeter wave (mmWave) communication system, where multiple reconfigurable intelligent surfaces (RISs) a…
Hashing Beam Training for Near-Field Communications
Yuan Xu, Li Wei, Chongwen Huang +6
In this paper, we investigate the millimeter-wave (mmWave) near-field beam training problem to find the correct beam direction. In order to address the high complexity and low iden…