Question 1

Which countries lead Wireless Signal Modulation Classification research?

Accepted Answer

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

Question 2

Which institutions lead Wireless Signal Modulation Classification research?

Accepted Answer

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.

Question 3

Who are the leading researchers in Wireless Signal Modulation Classification?

Accepted Answer

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

Question 4

Where is Wireless Signal Modulation Classification research done?

Accepted Answer

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.

Question 5

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

Accepted Answer

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.

Question 6

Is Wireless Signal Modulation Classification research growing?

Accepted Answer

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

Question 7

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

Accepted Answer

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).