4 citations · 7 across the 6 of their papers we have counts for
6 papers
AirTF: Over-the-Air Token Fusion for Task-Oriented Multi-Modal Token Communications
Bole Liu, Li Qiao, Minghui Wu +2
In the Internet of Vehicles (IoV), transmitting high-dimensional multi-modal sensory data to edge servers for time-sensitive tasks faces severe spectrum bottlenecks. To address thi…
E2E Learning Massive MIMO for Multimodal Semantic Non-Orthogonal Transmission and Fusion
Minghui Wu, Zhen Gao
This paper investigates multimodal semantic non-orthogonal transmission and fusion in hybrid analog-digital massive multiple-input multiple-output (MIMO). A Transformer-based cross…
Residual Cross-Attention Transformer-Based Multi-User CSI Feedback with Deep Joint Source-Channel Coding
Hengwei Zhang, Minghui Wu, Li Qiao +3
This letter proposes a deep-learning (DL)-based multi-user channel state information (CSI) feedback framework for massive multiple-input multiple-output systems, where the deep joi…
Deep Joint Semantic Coding and Beamforming for Near-Space Airship-Borne Massive MIMO Network
Minghui Wu, Zhen Gao, Zhaocheng Wang +3
Near-space airship-borne communication network is recognized to be an indispensable component of the future integrated ground-air-space network thanks to airships' advantage of lon…
Deep Learning-Based Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Aided Tera-Hertz Massive MIMO
Minghui Wu, Zhen Gao, Yang Huang +3
Reconfigurable intelligent surface (RIS) can significantly enhance the service coverage of Tera-Hertz massive multiple-input multiple-output (MIMO) communication systems. However,…
Improving Mandarin Speech Recogntion with Block-augmented Transformer
Xiaoming Ren, Huifeng Zhu, Liuwei Wei +2
Recently Convolution-augmented Transformer (Conformer) has shown promising results in Automatic Speech Recognition (ASR), outperforming the previous best published Transformer Tran…