Habong Chung

49 papers receiving 652 citations

Peers

Habong Chung
Comparison fields: 5 of 39
  • Electrical and Electronic Engineering 630
  • Artificial Intelligence 347
  • Computer Networks and Communications 341
  • Computational Theory and Mathematics 87
  • Discrete Mathematics and Combinatorics 53
Replace Vladimir Sidorenko with:
Vladimir Sidorenko Germany
M.U. Siddiqi Malaysia
Michael E. O’Sullivan United States
Xiaoni Du China
Øyvind Ytrehus Norway
Shudi Yang China
Roxana Smarandache United States
Juriaan Simonis Netherlands
Tero Laihonen Finland
P. Piret Belgium
Habong Chung relative to Vladimir Sidorenko Germany Vladimir Sidorenko's profile →
Citations per field
00.5×2.6×
Vladimir Sidorenko · 1×
Citations per year

Countries citing papers authored by Habong Chung

Since Specialization
Citations

This map shows the geographic impact of Habong Chung'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 Habong Chung with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Habong Chung more than expected).

Fields of papers citing papers by Habong Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Habong Chung. 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 Habong Chung. The network helps show where Habong Chung may publish in the future.

Co-authorship network of co-authors of Habong Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Habong Chung. A scholar is included among the top collaborators of Habong Chung based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Habong Chung. Habong Chung is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 24
3 1
4 3
5 13
6 1
7 28
8
A New PTS OFDM Scheme with Low Complexity for PAPR Reduction
2
9
Analysis of Autocorrelation Distributions of M-ary Sidel’nikov Sequences
1
10
Cyclotomic Numbers of Order 5 Over F p n
0
11
Protograph Codes with Circulant Permutation Matrices
1
12 1
13 4
14 152
15
q-ary Lempel–Cohn–Eastman Sequences
1
16
On the Phase Sequences for Selected Mapping OFDM System
1
17 4
18 20
19 43
20
A Theory on the Construction of Binary Sequences with Ideal Autocorrelation
0

About Habong Chung

Habong Chung is a scholar working on Discrete Mathematics and Combinatorics, Computer Networks and Communications and Artificial Intelligence, having authored 61 papers that have together received 703 indexed citations. Recurring topics across this work include Coding theory and cryptography (40 papers), graph theory and CDMA systems (26 papers) and Advanced Wireless Communication Techniques (23 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (53 citations), Computer Networks and Communications (341 citations) and Electrical and Electronic Engineering (630 citations). Habong Chung has collaborated with scholars based in South Korea, United States and China. Frequent co-authors include Jong‐Seon No, Dae‐Woon Lim, Dong‐Joon Shin, Sunghwan Kim, Hong‐Yeop Song, Seok-Joong Heo, Kyeongcheol Yang, Ji-Woong Jang, Hosung Park and Young Sik Kim. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and IEEE Transactions on Wireless Communications.

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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