13 papers
Task-Oriented Wave Processing with Stacked Intelligent Metasurfaces: Framework, Fusion, and Challenges
Qiao Qi, Qiyu Chen, Jiancheng An +4
The deep integration of diverse services in sixth-generation (6G) networks poses significant challenges to conventional task-agnostic channels, often resulting in performance confl…
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…
Recursive Flow: A Generative Framework for MIMO Channel Estimation
Zehua Jiang, Fenghao Zhu, Chongwen Huang +6
Channel estimation is a fundamental challenge in massive multiple-input multiple-output systems, where estimation accuracy governs the spectral efficiency and link reliability. In…
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…
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…
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…