72 citations · 179 across the 25 of their papers we have counts for
25 papers
Deep Learning for Asynchronous Massive Access with Data Frame Length Diversity
Yanna Bai, Wei Chen, Bo Ai +1
Grant-free non-orthogonal multiple access has been regarded as a viable approach to accommodate access for a massive number of machine-type devices with small data packets. The spo…
Deep-Learning-Aided Alternating Least Squares for Tensor CP Decomposition and Its Application to Massive MIMO Channel Estimation
Xiao Gong, Wei Chen, Bo Ai +1
CANDECOMP/PARAFAC (CP) decomposition is the mostly used model to formulate the received tensor signal in a massive MIMO system, as the receiver generally sums the components from d…
Digital-SC: Digital Semantic Communication with Adaptive Network Split and Learned Non-Linear Quantization
Lei Guo, Wei Chen, Yuxuan Sun +1
Semantic communication, an intelligent communication paradigm that aims to transmit useful information in the semantic domain, is facilitated by deep learning techniques. Robust se…
CSI-PPPNet: A One-Sided One-for-All Deep Learning Framework for Massive MIMO CSI Feedback
Wei Chen, Weixiao Wan, Shiyue Wang +3
To reduce multiuser interference and maximize the spectrum efficiency in orthogonal frequency division duplexing massive multiple-input multiple-output (MIMO) systems, the downlink…
Deep Joint Source-Channel Coding for Semantic Communications
Jialong Xu, Tze-Yang Tung, Bo Ai +3
Semantic communications is considered as a promising technology to increase the efficiency of next-generation communication systems, particularly targeting human-machine and machin…
Data-Driven Compressed Sensing for Massive Wireless Access
Yanna Bai, Wei Chen, Feifei Sun +2
The central challenge in massive machine-type communications (mMTC) is to connect a large number of uncoordinated devices through a limited spectrum. The typical mMTC communication…