61 citations · 189 across the 32 of their papers we have counts for
8 papers · 1 filter
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR
Tao Du, Jie Yang, Fan Liu +4
Millimeter-wave (mmWave) 5G New Radio (NR) communication systems, with their high-resolution antenna arrays and extensive bandwidth, offer a transformative opportunity for high-thr…
RainGaugeNet: CSI-Based Sub-6 GHz Rainfall Attenuation Measurement and Classification for ISAC Applications
Yan Li, Jie Yang, Yixuan Huang +3
Rainfall impacts daily activities and can lead to severe hazards such as flooding. Traditional rainfall measurement systems often lack granularity or require extensive infrastructu…
Semantic Communications using Foundation Models: Design Approaches and Open Issues
Peiwen Jiang, Chao-Kai Wen, Xinping Yi +3
Foundation models (FMs), including large language models, have become increasingly popular due to their wide-ranging applicability and ability to understand human-like semantics. W…
RIS-Enhanced Semantic Communications Adaptive to User Requirements
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Semantic communication significantly reduces required bandwidth by understanding semantic meaning of the transmitted. However, current deep learning-based semantic communication me…
Gradient-Based Markov Chain Monte Carlo for MIMO Detection
Xingyu Zhou, Le Liang, Jing Zhang +2
Accurately detecting symbols transmitted over multiple-input multiple-output (MIMO) wireless channels is crucial in realizing the benefits of MIMO techniques. However, optimal MIMO…
Communication-efficient Personalized Federated Edge Learning for Massive MIMO CSI Feedback
Yiming Cui, Jiajia Guo, Chao-Kai Wen +1
Deep learning (DL)-based channel state information (CSI) feedback has received significant research attention in recent years. However, previous research has overlooked the potenti…
Wireless Semantic Transmission via Revising Modules in Conventional Communications
Peiwen Jiang, Chao-Kai Wen, Shi Jin +1
Semantic communication has become a popular research area due its high spectrum efficiency and error-correction performance. Some studies use deep learning to extract semantic feat…
Solving Sparse Linear Inverse Problems in Communication Systems: A Deep Learning Approach With Adaptive Depth
Wei Chen, Bowen Zhang, Shi Jin +2
Sparse signal recovery problems from noisy linear measurements appear in many areas of wireless communications. In recent years, deep learning (DL) based approaches have attracted…