Y
Yuanwei Liu
Researcher at Queen Mary University of London
Publications - 477
Citations - 18977
Yuanwei Liu is an academic researcher from Queen Mary University of London. The author has contributed to research in topics: Computer science & Engineering. The author has an hindex of 53, co-authored 359 publications receiving 11049 citations. Previous affiliations of Yuanwei Liu include Xidian University & University of Houston.
Papers
More filters
Posted Content
Integrating Over-the-Air Federated Learning and Non-Orthogonal Multiple Access: What Role can RIS Play?
TL;DR: In this paper, a reconfigurable intelligent surface (RIS)-aided hybrid network by leveraging the RIS to flexibly adjust the signal processing order of heterogeneous data is proposed.
Journal Article
User Association and Resource Allocation in Unified Non-Orthogonal Multiple Access Enabled Heterogeneous Ultra Dense Networks
TL;DR: The application of NOMA techniques in HUDNs to support massive connectivity in 5G systems is investigated, with particular focus on user association and resource allocation.
Proceedings ArticleDOI
Semi-Grant-Free Uplink NOMA with Contention Control: A Stochastic Geometry Model
TL;DR: This work utilizes a semi-grant-free (semi-GF) NOMA scheme for enhancing network performance by enabling grant-based and GF users to share the same spectrum resources and proposes a novel dynamic protocol, which provides more accurate access thresholds than open-loop protocol, thereby the interference from the GF users is reduced to a large extent.
Posted Content
Reconfigurable Intelligent Surface Assisted Cooperative Non-orthogonal Multiple Access Systems
TL;DR: This paper considers the downlink of reconfigurable intelligent surface (RIS) assisted cooperative non-orthogonal multiple access (CNOMA) systems and proposes a low-complexity suboptimal algorithm that can achieve near-optimal performance.
Posted Content
Robotic Communications for 5G and Beyond: Challenges and Research Opportunities
TL;DR: Signal and spatial modeling for robotic communications are presented, and a novel simultaneous localization and radio mapping (SLARM) framework is proposed for integrating localization and communications into robotic networks.