Song Tu

1.6k citations
8 papers · 1.1k indexed · 1 hit paper · h-index 7
Topics
Advanced MIMO Systems Optimization (6 papers)Cooperative Communication and Network Coding (5 papers)Millimeter-Wave Propagation and Modeling (3 papers)

In The Last Decade

Song Tu

8 papers receiving 1.1k citations

Hit Papers

5G Ultra-Dense Cellular Networks20162026201920222016250500750

Peers

Song Tu
Comparison fields: 5 of 78
  • Electrical and Electronic Engineering 949
  • Computer Networks and Communications 602
  • Aerospace Engineering 135
  • Media Technology 104
  • Computer Vision and Pattern Recognition 48
Replace Zexian Li with:
Zexian Li Finland
Antonino Orsino Italy
Andreas Maeder Germany
Sandra Lagén Spain
Andrey Samuylov Finland
Zhengang Pan China
Athul Prasad Finland
David Soldani Finland
Michał Maternia Germany
Song Tu relative to Zexian Li Finland Zexian Li's profile →
Citations per field
00.5×1.5×1.8×
Zexian Li · 1×
Citations per year

Countries citing papers authored by Song Tu

Since Specialization
Citations

This map shows the geographic impact of Song Tu'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 Song Tu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Tu more than expected).

Fields of papers citing papers by Song Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Song Tu. 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 Song Tu. The network helps show where Song Tu may publish in the future.

Co-authorship network of co-authors of Song Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Song Tu. A scholar is included among the top collaborators of Song Tu 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 Song Tu. Song Tu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
#WorkIndexed citations
1 22
2 89
3 10
4 118
5
5G Ultra-Dense Cellular Networksbreakdown →
815
6 17
7
Establishment of a cell model for screening antibody drugs against rheumatoid arthritis with ADCC and CDC.
6
8 68

About Song Tu

Song Tu is a scholar working on Toxicology, Computer Networks and Communications and Media Technology, having authored 8 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced MIMO Systems Optimization (6 papers), Cooperative Communication and Network Coding (5 papers) and Millimeter-Wave Propagation and Modeling (3 papers). The work is most often cited by research in Computer Networks and Communications (602 citations), Electrical and Electronic Engineering (949 citations) and Media Technology (104 citations). Song Tu has collaborated with scholars based in China, Australia and United Kingdom. Frequent co-authors include Xiaohu Ge, Guoqiang Mao, Tao Han, Cheng‐Xiang Wang, Qiang Li, Yang Yang, Hui Cheng, Vincent K. N. Lau, Hsiao‐Hwa Chen and Wenjun Cheng. Their work appears in journals such as IEEE Transactions on Vehicular Technology, IEEE Wireless Communications and IEEE Transactions on Multimedia.

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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