Error Correcting Code Techniques
Error Correcting Code Techniques is a research topic within Computer Networks and Communications. Science Explorer counts 16k research works in it since 1960. 14.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the design, analysis, and implementation of Low-Density Parity-Check (LDPC) codes and Polar codes for efficient and reliable channel coding. The papers cover topics such as factor graphs, sum-product algorithm, belief propagation, iterative decoding, capacity-achieving codes, stochastic computing, and error correction techniques.
- LDPC Codes
- Polar Codes
- Factor Graphs
- Sum-Product Algorithm
- Belief Propagation
- Channel Coding
- Iterative Decoding
- Capacity-Achieving Codes
- Stochastic Computing
- Error Correction
- Research works
- 16k fractional, since 1960
- In the world top 10%
- 2.4k per year above
- Top-10% rate
- 14.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -13% the tick is no change
Which countries lead Error Correcting Code Techniques research?
By volume, China and the United States publish the most (648 and 249 works in 2022–2025).
By volume, 2022–2025
- 1 China 648 works
- 2 United States 249 works
- 3 India 145 works
- 4 Germany 88 works
- 5 South Korea 73 works
- 6 Japan 70 works
- 7 France 54 works
- 8 Russia 50 works
- 9 Canada 44 works
- 10 United Kingdom 42 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 Error Correcting Code Techniques research?
By volume in 2022–2025, Beijing University of Posts and Telecommunications publishes the most Error Correcting Code Techniques research, followed by Sun Yat-sen University and Southeast University.
By volume, 2022–2025
- 1 Beijing University of Posts and Telecommunications China 32 works
- 2 Sun Yat-sen University China 29 works
- 3 Southeast University China 22 works
- 4 Xidian University China 18 works
- 5 Beihang University China 15 works
- 6 University of Electronic Science and Technology of China China 14 works
- 7 National University of Defense Technology China 14 works
- 8 Tsinghua University China 13 works
- 9 Huawei Technologies (China) China 13 works
- 10 Harbin Institute of Technology China 13 works
Who are the leading researchers in Error Correcting Code Techniques?
The most-cited researchers publishing on Error Correcting Code Techniques include H. Vincent Poor, Robert W. Heath and Mohamed‐Slim Alouini.
- 1 H. Vincent Poor 9.5k citations
- 2 Robert W. Heath 7.1k citations
- 3 Mohamed‐Slim Alouini 5.9k citations
- 4 David R. Karger 5.2k citations
- 5 Zhu Han 4.7k citations
- 6 Mérouane Debbah 4.3k citations
- 7 Yonina C. Eldar 4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Error Correcting Code Techniques research done?
The largest centres of Error Correcting Code Techniques research in 2022–2025 are Beijing (China), Nanjing (China), Guangzhou (China) and Xi'an (China). Among places with at least 20 works in it, it is an unusually large share of all research in Shenzhen.
Largest cities, 2022–2025
Where it is the local speciality
- ShenzhenCN · 37.7 works6.0×
Location quotient: how much more of its research is in Error Correcting Code Techniques than the world average.
Where is the best place to study Error Correcting Code Techniques?
Among universities, judged by research, Sun Yat-sen University, Southeast University and UNSW Sydney 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 | Sun Yat-sen University China | 62.4 | 9.2% | 9.9× | 29 | +34.6% |
| 2 | Southeast University China | 55.5 | 6.5% | 9.0× | 22 | +71.4% |
| 3 | UNSW Sydney Australia | 55.2 | 24.3% | 5.4× | 8 | +28.0% |
| 4 | Beijing University of Posts and Telecommunications China | 55.0 | 5.6% | 27.7× | 32 | -5.5% |
| 5 | Xidian University China | 49.5 | 7.0% | 13.4× | 18 | -6.3% |
| 6 | Technion – Israel Institute of Technology Israel | 46.6 | 6.5% | 17.4× | 11 | +5.1% |
| 7 | National University of Defense Technology China | 39.6 | 3.1% | 10.0× | 14 | +11.9% |
| 8 | Beihang University China | 39.2 | 1.3% | 7.4× | 15 | +130.4% |
| 9 | National Yang Ming Chiao Tung University Taiwan | 37.2 | 5.7% | 11.7× | 9 | -58.7% |
| 10 | Karlsruhe Institute of Technology Germany | 37.1 | 6.3% | 9.1× | 9 | -45.5% |
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 Error Correcting Code Techniques research growing?
Output in 2018–2022 was 13% lower than in 2013–2017, peaking in 2010.
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.