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Wireless Signal Modulation Classification

Wireless Signal Modulation Classification is a research topic within Artificial Intelligence. Science Explorer counts 8.2k research works in it since 1951. 9.8% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the application of deep learning techniques for wireless signal classification, including modulation classification, channel estimation, RF fingerprinting, and spectrum monitoring in cognitive radios. The papers explore the opportunities and challenges of using deep learning in wireless communications and physical layer signal processing.

  • Deep Learning
  • Wireless Communications
  • Modulation Classification
  • Channel Estimation
  • RF Fingerprinting
  • Cognitive Radios
  • Automatic Recognition
  • Physical Layer
  • Massive MIMO
  • Spectrum Monitoring
Research works
8.2k
fractional, since 1951
In the world top 10%
799
per year above
Top-10% rate
9.8%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+129%
the tick is no change
Largest producer
China
65% of the 10 largest, 2022-now
Wireless Signal Modulation Classification

Which countries lead Wireless Signal Modulation Classification research?

By volume, China and the United States publish the most (2.5k and 402 works in 2022-now).

By volume, 2022-now

  1. 1 China 2.5k works
  2. 2 United States 402 works
  3. 3 India 339 works
  4. 4 South Korea 134 works
  5. 5 United Kingdom 122 works
  6. 6 Germany 71 works
  7. 7 Canada 68 works
  8. 8 France 58 works
  9. 9 Türkiye 55 works
  10. 10 Japan 54 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.

China: 65.4%United States: 10.7%India: 9.0%South Korea: 3.6%6 others listed: 11.4%65%largest
China2,461 · 65.4%United States402 · 10.7%India339 · 9.0%South Korea134 · 3.6%6 others listed428 · 11.4%

Shares of the rows listed above, not of the whole node.

Which institutions lead Wireless Signal Modulation Classification research?

By volume in 2022-now, Xidian University publishes the most Wireless Signal Modulation Classification research, followed by National University of Defense Technology and University of Electronic Science and Technology of China.

By volume, 2022-now

  1. 1 Xidian UniversityChina 118 works
  2. 2 National University of Defense TechnologyChina 117 works
  3. 3 University of Electronic Science and Technology of ChinaChina 110 works
  4. 4 Beijing University of Posts and TelecommunicationsChina 95 works
  5. 5 Harbin Engineering UniversityChina 80 works
  6. 6 Southeast UniversityChina 74 works
  7. 7 Beijing Institute of TechnologyChina 67 works
  8. 8 Chinese Academy of SciencesChina 60 works
  9. 9 Nanjing University of Posts and TelecommunicationsChina 54 works
  10. 10 Tsinghua UniversityChina 34 works

Who are the leading researchers in Wireless Signal Modulation Classification?

The most-cited researchers publishing on Wireless Signal Modulation Classification include H. Vincent Poor, Hao Chen and John F. Thompson.

  1. 1 H. Vincent Poor United States 165k citations
  2. 2 Hao Chen China 118k citations
  3. 3 John F. Thompson Australia 118k citations
  4. 4 Rui Zhang Singapore 115k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Wireless Signal Modulation Classification?

The most cited paper in Wireless Signal Modulation Classification is "Squeeze-and-Excitation Networks" (Jie Hu, Li Shen, Gang Zheng Sun, 2018), with 30,332 citations. Next come "An Introduction to Deep Learning for the Physical Layer" (3,031) and "Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems" (2,074).

Most cited papers
#PaperReleasedCitations
1 Squeeze-and-Excitation Networks Jie Hu, Li Shen, Gang Zheng Sun Conference paper Jun 2018 30,332
2 An Introduction to Deep Learning for the Physical Layer Timothy J. O’Shea, Jakob Hoydis · IEEE Transactions on Cognitive Communications and Networking 2 Oct 2017 3,031
3 Power of Deep Learning for Channel Estimation and Signal Detection in OFDM Systems Hao Ye, Geoffrey Ye Li, Biing-Hwang Fred Juang · IEEE Wireless Communications Letters 28 Sep 2017 2,074
4 Guaranteeing Secrecy using Artificial Noise Satashu Goel, Rohit Negi · IEEE Transactions on Wireless Communications Jun 2008 1,945
5 Over-the-Air Deep Learning Based Radio Signal Classification Timothy J. O’Shea, Tamoghna Roy, T. Charles Clancy · IEEE Journal of Selected Topics in Signal Processing Open access 23 Jan 2018 1,629
All 102 most cited papers, with filters and sorting

Where is Wireless Signal Modulation Classification research done?

The largest centres of Wireless Signal Modulation Classification research in 2022-now are Beijing (China), Nanjing (China), Xi'an (China) and Chengdu (China). Among places with at least 20 works in it, it is an unusually large share of all research in Yantai, Xi'an and Harbin.

Largest cities, 2022-now

  1. 1 BeijingChina 517 works
  2. 2 NanjingChina 265 works
  3. 3 Xi'anChina 249 works
  4. 4 ChengduChina 184 works
  5. 5 ChangshaChina 135 works
  6. 6 HarbinChina 123 works
  7. 7 ShanghaiChina 101 works
  8. 8 HangzhouChina 91 works
  9. 9 SeoulSouth Korea 73 works
  10. 10 ShenzhenChina 61 works

Where it is the local speciality

  1. YantaiCN · 20.1 works8.0×
  2. Xi'anCN · 248.7 works7.4×
  3. HarbinCN · 123.1 works7.1×
  4. ChangshaCN · 135.5 works6.4×
  5. ChengduCN · 184.3 works6.4×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Wireless Signal Modulation Classification than the world average.

See Wireless Signal Modulation Classification on the map

Where is the best place to study Wireless Signal Modulation Classification?

Among universities, judged by research, Xidian University, Imperial College London and Nanyang Technological 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.

0%20%40%mean 16.52%fractional works in this field (log) →share of work in the world top 10% →Imperial College Lon…Nanyang Technologica…Xidian UniversityBeijing University o…
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Xidian UniversityChina 67.016.9%42.4×118 +260.7%
2Imperial College LondonUnited Kingdom 63.938.6%2.6×10 +71.8%
3Nanyang Technological UniversitySingapore 62.827.7%6.3×19 +207.6%
4Beijing University of Posts and TelecommunicationsChina 62.114.3%39.1×95 +115.9%
5Southeast UniversityChina 59.811.5%13.2×74 +177.6%
6National University of Defense TechnologyChina 59.09.9%39.7×117 +125.3%
7University of Electronic Science and Technology of ChinaChina 58.27.7%25.6×110 +106.5%
8Nanjing University of Posts and TelecommunicationsChina 58.015.5%33.0×54 +133.5%
9Beijing Institute of TechnologyChina 57.312.5%14.9×67 +179.2%
10Harbin Engineering UniversityChina 56.110.6%40.5×80 +49.3%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Wireless Signal Modulation Classification, country by country

Is Wireless Signal Modulation Classification research growing?

Output in 2022-2025 was 129% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Wireless Signal Modulation Classification.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Wireless Signal Modulation Classification as a percentage of every work published that year, 0.015% in 2024.

still counting0.010%0.020%0.030%Wireless Signal Modulation Classification0.023% in 202519801990200020102020

Fractional works of Wireless Signal Modulation Classification over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Wireless Signal Modulation Classification9.6% in 202520102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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