activity
20082023
most citedDeep Learning for Physical-Layer 5G Wireless Techniques: Opportunities, Challenges and Solutions

28 citations · 42 across the 18 of their papers we have counts for

collaborators

18 papers

cs.IT2023

Sum-Rate Maximization in Active RIS-Assisted Multi-Antenna WPCN

Jie Jiang, Bin Lyu, Pengcheng Chen +1

In this paper, we propose an active reconfigurable intelligent surface (RIS) enabled hybrid relaying scheme for a multi-antenna wireless powered communication network (WPCN), where…

cs.IT2022

Joint Reconfigurable Intelligent Surface Location and Passive Beamforming Optimization for Maximizing the Secrecy-Rate

Haiyan Guo, Zhen Yang, Yulong Zou +3

The physical layer security (PLS) is investigated for reconfigurable intelligent surface (RIS) assisted wireless networks, where a source transmits its confidential information to…

cs.CV2020

Universal Multi-Source Domain Adaptation

Yueming Yin, Zhen Yang, Haifeng Hu +1

Unsupervised domain adaptation enables intelligent models to transfer knowledge from a labeled source domain to a similar but unlabeled target domain. Recent study reveals that kno…

cs.AI2020★ 1 cited

Unveiling Class-Labeling Structure for Universal Domain Adaptation

Yueming Yin, Zhen Yang, Xiaofu Wu +1

As a more practical setting for unsupervised domain adaptation, Universal Domain Adaptation (UDA) is recently introduced, where the target label set is unknown. One of the big chal…

cs.LG2020★ 1 cited

Metric-Learning-Assisted Domain Adaptation

Yueming Yin, Zhen Yang, Haifeng Hu +1

Domain alignment (DA) has been widely used in unsupervised domain adaptation. Many existing DA methods assume that a low source risk, together with the alignment of distributions o…

eess.SP2020★ 3 cited

Optimized Energy and Information Relaying in Self-Sustainable IRS-Empowered WPCN

Bin Lyu, Parisa Ramezani, Dinh Thai Hoang +3

This paper proposes a hybrid-relaying scheme empowered by a self-sustainable intelligent reflecting surface (IRS) in a wireless powered communication network (WPCN), to simultaneou…