Cognitive Radio Networks and Spectrum Sensing
Cognitive Radio Networks and Spectrum Sensing is a research topic within Computer Networks and Communications. Science Explorer counts 12k research works in it since 1966. 20.9% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on cognitive radio networks, spectrum sensing, dynamic spectrum access, cooperative sensing, and opportunistic spectrum access. It covers topics such as spectrum sharing, MAC protocols, security threats, and game theory in the context of cognitive radio and wireless networks.
- Cognitive Radio
- Spectrum Sensing
- Dynamic Spectrum Access
- Cooperative Sensing
- Opportunistic Spectrum Access
- Wireless Networks
- Spectrum Sharing
- MAC Protocols
- Security Threats
- Game Theory
- Research works
- 12k fractional, since 1966
- In the world top 10%
- 2.5k per year above
- Top-10% rate
- 20.9% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -41% the tick is no change
Which countries lead Cognitive Radio Networks and Spectrum Sensing research?
By volume, India and China publish the most (366 and 347 works in 2022–2025).
By volume, 2022–2025
- 1 India 366 works
- 2 China 347 works
- 3 United States 114 works
- 4 Canada 31 works
- 5 South Korea 29 works
- 6 United Kingdom 26 works
- 7 ?? 25 works
- 8 France 24 works
- 9 Iraq 21 works
- 10 Japan 20 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 Cognitive Radio Networks and Spectrum Sensing research?
By volume in 2022–2025, University of Electronic Science and Technology of China publishes the most Cognitive Radio Networks and Spectrum Sensing research, followed by Vellore Institute of Technology University and Saveetha University.
By volume, 2022–2025
- 1 University of Electronic Science and Technology of ChinaChina 17 works
- 2 Vellore Institute of Technology UniversityIndia 13 works
- 3 Saveetha UniversityIndia 13 works
- 4 Xidian UniversityChina 10 works
- 5 National University of Defense TechnologyChina 10 works
- 6 Beijing University of Posts and TelecommunicationsChina 10 works
- 7 Nanjing University of Posts and TelecommunicationsChina 10 works
- 8 Nanjing University of Aeronautics and AstronauticsChina 9 works
- 9 Southeast UniversityChina 9 works
- 10 Vels UniversityIndia 9 works
Who are the leading researchers in Cognitive Radio Networks and Spectrum Sensing?
The most-cited researchers publishing on Cognitive Radio Networks and Spectrum Sensing include H. Vincent Poor, Ian F. Akyildiz and Rui Zhang.
- 1 H. Vincent Poor United States 9.5k citations
- 2 Ian F. Akyildiz United States 8.2k citations
- 3 Rui Zhang Singapore 6k citations
- 4 Mohamed‐Slim Alouini Saudi Arabia 5.9k citations
- 5 Xuemin Shen Canada 5.1k citations
- 6 Zhu Han United States 4.7k citations
- 7 Georgios B. Giannakis United States 4.6k citations
- 8 Dusit Niyato Singapore 4.5k citations
- 9 Mérouane Debbah France 4.3k citations
- 10 Yonina C. Eldar Israel 4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Cognitive Radio Networks and Spectrum Sensing research done?
The largest centres of Cognitive Radio Networks and Spectrum Sensing research in 2022–2025 are Beijing (China), Chennai (India), Nanjing (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Chennai.
Largest cities, 2022–2025
Where it is the local speciality
- ChennaiIN · 49.0 works7.7×
Location quotient: how much more of its research is in Cognitive Radio Networks and Spectrum Sensing than the world average.
Where is the best place to study Cognitive Radio Networks and Spectrum Sensing?
Among universities, judged by research, Vellore Institute of Technology University, Saveetha University and University of Electronic Science and Technology of China 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 | Vellore Institute of Technology UniversityIndia | 79.4 | 20.3% | 10.3× | 13 | +1390.0% |
| 2 | Saveetha UniversityIndia | 70.4 | 18.4% | 9.9× | 12 | — |
| 3 | University of Electronic Science and Technology of ChinaChina | 67.8 | 16.4% | 11.6× | 17 | -39.4% |
| 4 | Xidian UniversityChina | 65.5 | 24.4% | 10.8× | 10 | -39.4% |
| 5 | Nanjing University of Posts and TelecommunicationsChina | 43.8 | 13.4% | 17.7× | 10 | -39.6% |
| 6 | National University of Defense TechnologyChina | 43.1 | 13.9% | 10.0× | 10 | -6.9% |
| 7 | Beijing University of Posts and TelecommunicationsChina | 37.6 | 10.6% | 12.4× | 10 | -55.4% |
| 8 | Nanjing University of Aeronautics and AstronauticsChina | 36.7 | 10.0% | 8.1× | 9 | +141.5% |
| 9 | Vels UniversityIndia | 32.6 | 7.5% | 45.9× | 9 | — |
| 10 | Southeast UniversityChina | 26.0 | 15.4% | 5.2× | 9 | -19.4% |
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 Cognitive Radio Networks and Spectrum Sensing research growing?
Output in 2018–2022 was 41% lower than in 2013–2017, peaking in 2014. The fastest-growing topics are Cognitive Radio Networks and Spectrum Sensing.
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.