Cooperative Communication and Network Coding
Cooperative Communication and Network Coding is a research topic within Computer Networks and Communications. Science Explorer counts 49k research works in it since 1950. 19.4% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on cooperative diversity in wireless networks, exploring efficient protocols, outage behavior, network coding, relay networks, space-time coding, and amplify-and-forward techniques. It delves into topics such as physical layer network coding, MIMO relay channels, and the analysis of outage probability in multiuser communication scenarios.
- Cooperative Diversity
- Wireless Networks
- Network Coding
- Relay Networks
- Space-Time Coding
- Amplify-and-Forward
- Physical Layer Network Coding
- MIMO Relay Channels
- Outage Probability
- Multiuser Communication
- Research works
- 49k fractional, since 1950
- In the world top 10%
- 9.5k per year above
- Top-10% rate
- 19.4% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -41% the tick is no change
Which countries lead Cooperative Communication and Network Coding research?
By volume, China and India publish the most (1.3k and 548 works in 2022–2025).
By volume, 2022–2025
- 1 China 1.3k works
- 2 India 548 works
- 3 United States 381 works
- 4 South Korea 157 works
- 5 Japan 131 works
- 6 United Kingdom 124 works
- 7 Germany 116 works
- 8 Canada 113 works
- 9 France 77 works
- 10 Iran 69 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Cooperative Communication and Network Coding research?
By volume in 2022–2025, Beijing University of Posts and Telecommunications publishes the most Cooperative Communication and Network Coding research, followed by Southeast University and Xidian University.
By volume, 2022–2025
- 1 Beijing University of Posts and TelecommunicationsChina 58 works
- 2 Southeast UniversityChina 55 works
- 3 Xidian UniversityChina 35 works
- 4 University of Electronic Science and Technology of ChinaChina 34 works
- 5 Nanjing University of Posts and TelecommunicationsChina 34 works
- 6 Tsinghua UniversityChina 28 works
- 7 Beijing Jiaotong UniversityChina 22 works
- 8 Harbin Institute of TechnologyChina 21 works
- 9 Shanghai Jiao Tong UniversityChina 21 works
- 10 Beijing Institute of TechnologyChina 20 works
Who are the leading researchers in Cooperative Communication and Network Coding?
The most-cited researchers publishing on Cooperative Communication and Network Coding include H. Vincent Poor, Ian F. Akyildiz and Robert W. Heath.
- 1 H. Vincent Poor United States 9.5k citations
- 2 Ian F. Akyildiz United States 8.2k citations
- 3 Robert W. Heath United States 7.1k citations
- 4 Rui Zhang Singapore 6k citations
- 5 Mohamed‐Slim Alouini Saudi Arabia 5.9k citations
- 6 Guanrong Chen Hong Kong 5.4k citations
- 7 Xuemin Shen Canada 5.1k citations
- 8 Peng Shi Australia 5k citations
- 9 Zhu Han United States 4.7k citations
- 10 Georgios B. Giannakis United States 4.6k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Cooperative Communication and Network Coding research done?
The largest centres of Cooperative Communication and Network Coding research in 2022–2025 are Beijing (China), Nanjing (China), Xi'an (China) and Shanghai (China). Among places with at least 20 works in it, it is an unusually large share of all research in Hsinchu.
Largest cities, 2022–2025
Where it is the local speciality
- HsinchuTW · 22.5 works6.4×
Location quotient: how much more of its research is in Cooperative Communication and Network Coding than the world average.
Where is the best place to study Cooperative Communication and Network Coding?
Among universities, judged by research, Chinese University of Hong Kong, Shenzhen, Southeast University and PLA Army Engineering University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Chinese University of Hong Kong, ShenzhenChina | 63.2 | 17.7% | 11.9× | 9 | +311.0% |
| 2 | Southeast UniversityChina | 61.1 | 11.0% | 10.0× | 55 | +20.5% |
| 3 | PLA Army Engineering UniversityChina | 55.2 | 25.2% | 27.0× | 13 | +1.1% |
| 4 | KTH Royal Institute of TechnologySweden | 54.9 | 17.3% | 11.3× | 17 | -51.7% |
| 5 | Beijing University of Posts and TelecommunicationsChina | 54.7 | 8.6% | 23.0× | 58 | -30.7% |
| 6 | Xidian UniversityChina | 53.8 | 11.7% | 11.6× | 35 | -13.7% |
| 7 | University of OuluFinland | 52.9 | 16.7% | 14.9× | 15 | -41.3% |
| 8 | Nanjing University of Posts and TelecommunicationsChina | 52.6 | 9.8% | 19.2× | 34 | +3.9% |
| 9 | Imperial College LondonUnited Kingdom | 49.7 | 33.5% | 2.9× | 10 | +28.4% |
| 10 | University of Electronic Science and Technology of ChinaChina | 49.5 | 13.8% | 7.5× | 34 | -2.9% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Cooperative Communication and Network Coding research growing?
Output in 2018–2022 was 41% lower than in 2013–2017, peaking in 2012. The fastest-growing topics are Cooperative Communication and Network Coding.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.