Shuguang Cui

30.8k total citations · 21 hit papers
477 papers, 19.7k citations indexed

About

Shuguang Cui is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Shuguang Cui has authored 477 papers receiving a total of 19.7k indexed citations (citations by other indexed papers that have themselves been cited), including 245 papers in Electrical and Electronic Engineering, 218 papers in Computer Networks and Communications and 135 papers in Artificial Intelligence. Recurrent topics in Shuguang Cui's work include Advanced MIMO Systems Optimization (98 papers), Cooperative Communication and Network Coding (81 papers) and Energy Harvesting in Wireless Networks (53 papers). Shuguang Cui is often cited by papers focused on Advanced MIMO Systems Optimization (98 papers), Cooperative Communication and Network Coding (81 papers) and Energy Harvesting in Wireless Networks (53 papers). Shuguang Cui collaborates with scholars based in China, United States and Hong Kong. Shuguang Cui's co-authors include Andrea Goldsmith, H. Vincent Poor, Ahmad Bahai, Mingzhe Chen, Rui Zhang, Zhi Quan, Ali H. Sayed, Jie Xu, Walid Saad and Zhaohui Yang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Bioinformatics.

In The Last Decade

Shuguang Cui

456 papers receiving 19.2k citations

Hit Papers

Energy-Efficiency of MIMO and Cooperative MIMO Techniques... 2004 2026 2011 2018 2004 2005 2020 2008 2017 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shuguang Cui China 63 11.9k 11.2k 4.3k 2.4k 1.7k 477 19.7k
Geoffrey Ye Li China 83 23.8k 2.0× 12.7k 1.1× 5.6k 1.3× 5.9k 2.5× 1.4k 0.8× 503 30.1k
Khaled B. Letaief Hong Kong 78 22.0k 1.8× 20.6k 1.8× 3.2k 0.7× 4.3k 1.8× 1.6k 1.0× 722 31.1k
Michele Zorzi Italy 66 17.7k 1.5× 16.4k 1.5× 1.1k 0.3× 2.2k 0.9× 1.4k 0.8× 807 26.3k
Tony Q. S. Quek Singapore 68 13.1k 1.1× 11.8k 1.1× 3.8k 0.9× 3.1k 1.3× 1.1k 0.7× 919 20.7k
Guan Gui China 62 7.0k 0.6× 3.4k 0.3× 5.2k 1.2× 4.2k 1.8× 1.5k 0.9× 592 14.9k
Arumugam Nallanathan United Kingdom 73 18.7k 1.6× 9.8k 0.9× 1.5k 0.3× 7.2k 3.0× 965 0.6× 732 23.1k
Ramjee Prasad Denmark 54 14.0k 1.2× 12.4k 1.1× 1.0k 0.2× 2.1k 0.9× 995 0.6× 1.0k 18.8k
K. J. Ray Liu United States 68 10.4k 0.9× 9.4k 0.8× 1.5k 0.3× 1.3k 0.6× 2.3k 1.4× 500 17.0k
Branka Vucetic Australia 66 13.4k 1.1× 10.6k 0.9× 1.6k 0.4× 2.2k 0.9× 524 0.3× 642 16.2k
Nirwan Ansari United States 69 9.6k 0.8× 9.9k 0.9× 2.8k 0.6× 2.5k 1.1× 3.7k 2.2× 632 19.2k

Countries citing papers authored by Shuguang Cui

Since Specialization
Citations

This map shows the geographic impact of Shuguang Cui's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Shuguang Cui with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuguang Cui more than expected).

Fields of papers citing papers by Shuguang Cui

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shuguang Cui. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Shuguang Cui. The network helps show where Shuguang Cui may publish in the future.

Co-authorship network of co-authors of Shuguang Cui

This figure shows the co-authorship network connecting the top 25 collaborators of Shuguang Cui. A scholar is included among the top collaborators of Shuguang Cui based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Shuguang Cui. Shuguang Cui is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Li, Mingxiao, Kaiming Shen, & Shuguang Cui. (2025). A Semantic Approach to Successive Interference Cancellation for Multiple Access Networks. IEEE Internet of Things Journal. 12(11). 16424–16437. 1 indexed citations
2.
Li, Yuhang, Yang Lu, Guangyang Zhang, et al.. (2025). Homogeneous and Heterogeneous Graph Learning for Hybrid Beamforming in mmWave Systems. IEEE Transactions on Wireless Communications. 24(10). 8086–8100. 1 indexed citations
3.
Li, Shuling, et al.. (2025). Semantic Knowledge Base Empowered Generative Semantic Communication. IEEE Transactions on Communications. 73(11). 11308–11322.
4.
Du, Yuanyuan, Jianan Zhang, Xiang Cheng, & Shuguang Cui. (2025). Cooperative Motion Planning in Divided Environments via Congestion-Aware Deep Reinforcement Learning. IEEE Robotics and Automation Letters. 10(3). 2295–2302. 1 indexed citations
5.
Yang, Yang, et al.. (2024). A Survey on Indoor Visible Light Positioning Systems: Fundamentals, Applications, and Challenges. IEEE Communications Surveys & Tutorials. 27(3). 1656–1686. 17 indexed citations
6.
Du, Hongyang, Ruichen Zhang, Yinqiu Liu, et al.. (2024). Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization. IEEE Communications Surveys & Tutorials. 26(4). 2611–2646. 111 indexed citations breakdown →
7.
Zhu, Minhao, et al.. (2024). Power Allocation for Finite-Blocklength IR-HARQ. IEEE Communications Letters. 28(11). 2673–2677.
8.
Zhang, Zezhong, et al.. (2024). Fast and Accurate Cooperative Radio Map Estimation Enabled by GAN. 1641–1646. 6 indexed citations
9.
Gao, Xiangyu, Yaping Sun, Xiaodong Xu, et al.. (2024). Learning for Semantic Knowledge Base-Guided Online Feature Transmission in Dynamic Channels. 1035–1040. 1 indexed citations
10.
Sun, Ya‐Ping, et al.. (2024). Codebook-Enabled Generative End-to-End Semantic Communication Powered by Transformer. 1–6. 2 indexed citations
11.
Li, Shuling, Yaping Sun, Jinbei Zhang, et al.. (2024). Cooperative Semantic Knowledge Base Update Policy for Multiple Semantic Communication Pairs. 2178–2183. 2 indexed citations
12.
Lyu, Zhonghao, Yuchen Li, Guangxu Zhu, et al.. (2024). Rethinking Resource Management in Edge Learning: A Joint Pre-Training and Fine-Tuning Design Paradigm. IEEE Transactions on Wireless Communications. 24(2). 1584–1601. 9 indexed citations
13.
Cui, Shuguang, et al.. (2023). NG-NAS: Node growth neural architecture search for 3D medical image segmentation. Computerized Medical Imaging and Graphics. 108. 102268–102268. 8 indexed citations
14.
Zhu, Guangxu, Zhonghao Lyu, Peixi Liu, et al.. (2023). Pushing AI to wireless network edge: an overview on integrated sensing, communication, and computation towards 6G. Science China Information Sciences. 66(3). 144 indexed citations breakdown →
15.
Liu, Liang, et al.. (2022). Device-Free Sensing in OFDM Cellular Network. IEEE Journal on Selected Areas in Communications. 40(6). 1838–1853. 75 indexed citations
16.
Yu, Lu, Junwei Bao, Yan Song, et al.. (2021). RevCore: Review-Augmented Conversational Recommendation. 1161–1173. 36 indexed citations
17.
Liao, Yinghong, Fuyu Wang, Bin Zhang, et al.. (2021). Medical-VLBERT: Medical Visual Language BERT for COVID-19 CT Report Generation With Alternate Learning. IEEE Transactions on Neural Networks and Learning Systems. 32(9). 3786–3797. 48 indexed citations
18.
Zhang, Han, et al.. (2020). Noncoherent Energy-Modulated Massive SIMO in Multipath Channels: A Machine Learning Approach. IEEE Internet of Things Journal. 7(9). 8263–8270. 8 indexed citations
19.
Yin, Feng, et al.. (2020). An Interpretable and Sample Efficient Deep Kernel for Gaussian Process. Uncertainty in Artificial Intelligence. 759–768. 1 indexed citations
20.
Xu, Yue, et al.. (2019). Voting-Based Multi-Agent Reinforcement Learning.. arXiv (Cornell University). 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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