10 papers
Weight Hybrid Architecture of Rydberg-Atomic Sensors
Hao Wu, Xinyuan Yao, Shanchi Wu +3
Rydberg atomic quantum receivers have been seen as novel radio frequency measurements and the high sensitivity to a large range of frequencies makes it attractive for communication…
Digital Twin Synchronization Over Mobile Embodied AI Network With Agentic Intelligence
Zhouxiang Zhao, Jiaxiang Wang, Yahao Ding +6
Efficient digital twin (DT) synchronization relies on maintaining high-fidelity virtual representations with minimal age of information (AoI). However, the synergistic potential of…
Agentic AI-Empowered Wireless Agent Networks With Semantic-Aware Collaboration via ILAC
Zhouxiang Zhao, Jiaxiang Wang, Zhaohui Yang +4
The rapid development of agentic artificial intelligence (AI) is driving future wireless networks to evolve from passive data pipes into intelligent collaborative ecosystems under…
Quantum-PROBE: Rydberg Atomic Receiver-Based Multi-AoA Estimation with RF Lens
Hong-Bae Jeon, Kaibin Huang, Chan-Byoung Chae
This paper presents the Quantum-Power pROfile Based Estimation (PROBE) framework, a Rydberg Atomic Receiver (RARE)-based multi-user angle-of-arrival (AoA) estimation approach equip…
Channel-Adaptive Edge AI: Maximizing Inference Throughput by Adapting Computational Complexity to Channel States
Jierui Zhang, Jianhao Huang, Kaibin Huang
\emph{Integrated communication and computation} (IC) has emerged as a new paradigm for enabling efficient edge inference in sixth-generation (6G) networks. However, the design…
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…
Data Sourcing Random Access using Semantic Queries for Massive IoT Scenarios
Anders E. Kalør, Petar Popovski, Kaibin Huang
Efficiently retrieving relevant data from massive Internet of Things (IoT) networks is essential for downstream tasks such as machine learning. This paper addresses this challenge…
Semantic-Relevance Based Sensor Selection for Edge-AI Empowered Sensing Systems
Zhiyan Liu, Kaibin Huang
The sixth-generation (6G) mobile network is envisioned to incorporate sensing and edge artificial intelligence (AI) as two key functions. Their natural convergence leads to the eme…
Ultra-Low-Latency Edge Inference for Distributed Sensing
Zhanwei Wang, Anders E. Kalør, You Zhou +2
There is a broad consensus that artificial intelligence (AI) will be a defining component of the sixth-generation (6G) networks. As a specific instance, AI-empowered sensing will g…
Over-the-Air Fusion of Sparse Spatial Features for Integrated Sensing and Edge AI over Broadband Channels
Zhiyan Liu, Qiao Lan, Kaibin Huang
The 6G mobile networks feature two new usage scenarios -- distributed sensing and edge artificial intelligence (AI). Their natural integration, termed integrated sensing and edge A…