Chang-Jun Ahn

1k citations
184 papers · 731 · h-index 11

Impact in

Papers in

Chang-Jun Ahn

155 papers receiving 712 citations

Peers

Chang-Jun Ahn
Comparison fields: 5 of 29
  • Electrical and Electronic Engineering 496
  • Computer Networks and Communications 84
  • Biomedical Engineering 122
  • Signal Processing 26
  • Artificial Intelligence 53
Replace Robert J. Baxley with:
Robert J. Baxley United States
Aziz Benlarbi‐Delaï France
Seun Sangodoyin United States
Yao Yuan China
Yu Zhu China
Barend van Liempd Belgium
Marko Kosunen Finland
Ole Kiel Jensen Denmark
H. Barthélemy France
Ulf Gustavsson Sweden
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Citations per field
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Citations per year

Countries citing papers authored by Chang-Jun Ahn

Since Specialization
Citations

This map shows the geographic impact of Chang-Jun Ahn's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Chang-Jun Ahn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chang-Jun Ahn more than expected).

Fields of papers citing papers by Chang-Jun Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang-Jun Ahn. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Chang-Jun Ahn. The network helps show where Chang-Jun Ahn may publish in the future.

Co-authors

The 25 scholars most cited alongside Chang-Jun Ahn, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Chang-Jun Ahn Line = papers co-authored together Chang-Jun Ahn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 184 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201654
2 201940
3 201236
4 201130
5 202128
6 201825
7 201214
8 200513
9 201712
10 201211
11 201211
12 201311
13 201811
14
Decision Direct and Linear Prediction based Fast Fading Compensation for TFI-OFDM
200810
15 201110
16 201210
17 20049
18
Prototype of 5.8 GHz wireless power transmission system for electric vehicle system (回路とシステム)
20119
19 20119
20 20138

About Chang-Jun Ahn

Chang-Jun Ahn is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Signal Processing, Biomedical Engineering and Artificial Intelligence, having authored 184 papers that have together received 731 indexed citations. Recurring topics across this work include Advanced Wireless Communication Techniques (90 papers), Advanced MIMO Systems Optimization (23 papers), PAPR reduction in OFDM (23 papers), Optical Wireless Communication Technologies (12 papers), Acoustic Wave Resonator Technologies (12 papers), Advanced Wireless Network Optimization (12 papers), Wireless Communication Networks Research (10 papers) and Direction-of-Arrival Estimation Techniques (9 papers). The work is most often cited by research in Electrical and Electronic Engineering (496 citations), Computer Networks and Communications (84 citations), Biomedical Engineering (122 citations), Signal Processing (26 citations) and Artificial Intelligence (53 citations). Chang-Jun Ahn has collaborated with scholars based in Japan, South Korea and China. Frequent co-authors include Kazuki Maruta, Tatsuya Omori, Ken‐ya Hashimoto, Ken-ya Hashimoto, Yeon Ho Chung, Willy Anugrah Cahyadi, Dongsoo Har, Hyunju Kim, Masahiro Sakamoto and Wenjian Wang. Their work appears in journals such as Electronics, ICT Express, IEEE Access, Digital Signal Processing and IEEE Transactions on Circuits and Systems I Regular Papers.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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