61 citations · 117 across the 22 of their papers we have counts for
22 papers
Task-Oriented Communications for 6G: Vision, Principles, and Technologies
Yuanming Shi, Yong Zhou, Dingzhu Wen +3
Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is envisaged to go beyond data-centric services to provide intelligent and immersive…
FedLP: Layer-wise Pruning Mechanism for Communication-Computation Efficient Federated Learning
Zheqi Zhu, Yuchen Shi, Jiajun Luo +4
Federated learning (FL) has prevailed as an efficient and privacy-preserved scheme for distributed learning. In this work, we mainly focus on the optimization of computation and co…
Mobile Cell-Free Massive MIMO: Challenges, Solutions, and Future Directions
Jiakang Zheng, Jiayi Zhang, Hongyang Du +4
Cell-free (CF) massive multiple-input multiple-output (MIMO) systems, which exploit many geographically distributed access points to coherently serve user equipments via spatial mu…
Augmented Deep Unfolding for Downlink Beamforming in Multi-cell Massive MIMO With Limited Feedback
Yifan Ma, Xianghao Yu, Jun Zhang +2
In limited feedback multi-user multiple-input multiple-output (MU-MIMO) cellular networks, users send quantized information about the channel conditions to the associated base stat…
Task-Oriented Multi-User Semantic Communications
Huiqiang Xie, Zhijin Qin, Xiaoming Tao +1
While semantic communications have shown the potential in the case of single-modal single-users, its applications to the multi-user scenario remain limited. In this paper, we inves…
How global observation works in Federated Learning: Integrating vertical training into Horizontal Federated Learning
Shuo Wan, Jiaxun Lu, Pingyi Fan +3
Federated learning (FL) has recently emerged as a transformative paradigm that jointly train a model with distributed data sets in IoT while avoiding the need for central data coll…