109 citations · 232 across the 12 of their papers we have counts for
13 papers
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…
Robust Hybrid Beamforming with Liquid Crystal Antennas and Liquid Neural Networks
Xinquan Wang, Mingjun Ying, Hongren Chen +6
Sub-terahertz (sub-THz) multi-user multiple-input multiple-output (MU-MIMO) systems unlock immense bandwidth for 6G wireless communications. However, practical deployment of wirele…
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…
Liquid Neural Networks: Next-Generation AI for Telecom from First Principles
Fenghao Zhu, Xinquan Wang, Chen Zhu +1
Artificial intelligence (AI) has emerged as a transformative technology with immense potential to reshape the next-generation of wireless networks. By leveraging advanced algorithm…
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…
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…
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…
Robust Beamforming for RIS-aided Communications: Gradient-based Manifold Meta Learning
Fenghao Zhu, Xinquan Wang, Chongwen Huang +6
Reconfigurable intelligent surface (RIS) has become a promising technology to realize the programmable wireless environment via steering the incident signal in fully customizable w…
Energy-efficient Beamforming for RISs-aided Communications: Gradient Based Meta Learning
Xinquan Wang, Fenghao Zhu, Qianyun Zhou +6
Reconfigurable intelligent surfaces (RISs) have become a promising technology to meet the requirements of energy efficiency and scalability in future six-generation (6G) communicat…