Demo Data from EDBT 2026 / reviewers in the wild / expert
Yunnuo Xu
dblp:292/3459
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2026
0000-0003-2081-2041ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 1 first-author · 2 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Physical-layer communications · 67% Vehicular, aerial and satellite networks · 17% Cellular and mobile networks · 17% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 50% Algorithmic game theory and mechanism design · 50% |
Topics — the 8 heaviest of 8, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cellular and mobile networks
interference management |
0.8 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Physical-layer communications
multiple access |
0.8 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Physical-layer communications › MIMO
precoding |
0.8 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Physical-layer communications › multiple access › non-orthogonal multiple access
rate-splitting multiple access |
0.8 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Physical-layer communications › MIMO › precoder design
robust precoding |
0.8 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Vehicular, aerial and satellite networks
satellite communication |
0.8 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Algorithmic game theory and mechanism design › fair division
max-min fairness |
0.2 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Mathematical optimization
nonconvex optimization |
0.2 | 1 | 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite Communications · IEEE Trans. Commun. 2024 |
Methods — techniques the papers use, named apart from their topics
successive convex approximation · 1.5robust optimization · 1.5rate-splitting multiple access · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Adaptive cooperative uplink NOMA with opportunistic Alamouti coding in cellular networks
Keying Zhang, Jiachao Yu, Yunnuo Xu |
Comput. Networks | 5 |
| 2026 | MCCL: Entailment tree generation via multi-fact contrastive selection and consistent LLM-based inference
Siwen Zhao, Wei Wang 0375, Yunnuo Xu |
Inf. Sci. | 7 |
| 2024 | Distributed Rate-Splitting Multiple Access for Multilayer Satellite CommunicationsabstractFuture wireless networks, in particular, 5G and beyond, are anticipated to deploy dense Low Earth Orbit (LEO) satellites to provide global coverage and broadband connectivity. However, the limited frequency band and the coexistence of multiple constellations bring new challenges for interference management. In this paper, we propose a robust multilayer interference management scheme for spectrum sharing in heterogeneous satellite networks with statistical Channel State Information (CSI) at the Transmitter (CSIT) and Receivers (CSIR). In the proposed scheme, Rate-Splitting Multiple Access (RSMA), as a general and powerful framework for interference management and multiple access strategies, is implemented distributedly at Geostationary Orbit (GEO) and LEO satellites, coined Distributed-RSMA (D-RSMA). By doing so, D-RSMA aims to mitigate the interference and boost the user fairness of the overall multilayer satellite system. Specifically, we study the problem of jointly optimizing the GEO/LEO precoders and message splits to maximize the minimum rate among User Terminals (UTs) subject to a transmit power constraint at all satellites. A robust algorithm is proposed to solve the original non-convex optimization problem. Numerical results demonstrate the effectiveness and robustness towards network load and CSI uncertainty of our proposed D-RSMA scheme. Benefiting from the interference management capability, D-RSMA provides significant max-min fairness performance gains compared to several benchmark schemes. Yunnuo Xu, Longfei Yin, Yijie Mao, Wonjae Shin, Bruno Clerckx |
IEEE Trans. Commun. | 1 |