324 citations · 1.5k across the 87 of their papers we have counts for
20 papers · 1 filter
Semantic Communications for Speech Signals
Zhenzi Weng, Zhijin Qin, Geoffrey Ye Li
We consider a semantic communication system for speech signals, named DeepSC-S. Motivated by the breakthroughs in deep learning (DL), we make an effort to recover the transmitted s…
Deep Learning for Joint Channel Estimation and Feedback in Massive MIMO Systems
Jiajia Guo, Tong Chen, Shi Jin +3
The great potentials of massive Multiple-Input Multiple-Output (MIMO) in Frequency Division Duplex (FDD) mode can be fully exploited when the downlink Channel State Information (CS…
AnciNet: An Efficient Deep Learning Approach for Feedback Compression of Estimated CSI in Massive MIMO Systems
Yuyao Sun, Wei Xu, Lisheng Fan +2
Accurate channel state information (CSI) feedback plays a vital role in improving the performance gain of massive multiple-input multiple-output (m-MIMO) systems, where the dilemma…
Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks
Ying-Chang Liang, Qianqian Zhang, Erik G. Larsson +1
The heterogenous wireless services and exponentially growing traffic call for novel spectrum- and energy-efficient wireless communication technologies. In this paper, a new techniq…
Model-Driven Deep Learning for Massive MU-MIMO with Finite-Alphabet Precoding
Hengtao He, Mengjiao Zhang, Shi Jin +2
Massive multiuser multiple-input multiple-output (MU-MIMO) has been the mainstream technology in fifth-generation wireless systems. To reduce high hardware costs and power consumpt…
Model-Driven DNN Decoder for Turbo Codes: Design, Simulation and Experimental Results
Yunfeng He, Jing Zhang, Shi Jin +2
This paper presents a novel model-driven deep learning (DL) architecture, called TurboNet, for turbo decoding that integrates DL into the traditional max-log-maximum a posteriori (…