15 papers
A Theory of Atomic Beamforming
Mingyao Cui, Qunsong Zeng, Kaibin Huang
Leveraging the quantum advantages of highly excited atoms, Rydberg atomic receivers (RAREs) represent a paradigm shift in microwave detection with extremely high sensitivity and br…
Revisiting Outage for Edge Inference Systems
Zhanwei Wang, Qunsong Zeng, Haotian Zheng +1
One of the key missions of sixth-generation (6G) mobile networks is to deploy large-scale artificial intelligence (AI) models at the network edge to provide remote-inference servic…
In-Memory Computing Enabled Deep MIMO Detection to Support Ultra-Low-Latency Communications
Tingyu Ding, Qunsong Zeng, Kaibin Huang
The development of sixth-generation (6G) mobile networks imposes unprecedented latency and reliability demands on multiple-input multiple-output (MIMO) communication systems, a key…
InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate
Zhengyang Hu, Yanzhi Chen, Hanxiang Ren +5
Measuring statistical dependency between high-dimensional random variables is a fundamental task in data science and machine learning. Neural mutual information (MI) estimators off…
Continuous Quantum Aperture: Beamforming with a Single-Vapor-Cell Rydberg Receiver
Mingyao Cui, Qunsong Zeng, Minze Chen +6
Beamforming is conventionally understood as a collective property of many discrete antenna elements in both communication and radar fields, which links angular selectivity to array…
Parametric-Sensitivity Aware Retransmission for Efficient AI Downloading
You Zhou, Qunsong Zeng, Kaibin Huang
The edge artificial intelligence (AI) applications in next-generation mobile networks demand efficient AI-model downloading techniques to support real-time, on-device inference. Ho…