Joint Source-Channel Coding is a coding paradigm in information theory where a single integrated scheme jointly optimizes the compression of source data and its reliable transmission over a noisy channel, departing from the traditional separation-based approach of independently designing source and channel codes.
760
Publications
40.2K
Citations
1.1K
Authors
430
Institutions
Publications per year
2017–2026
137
Publications
760
1–5 of 760
Authors
1.1K
- DG
27
h-index
- KR
18
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- JG
17
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- LW
15
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- ZX
14
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1–5 of 1.1K
Institutions
430
Imperial College London
London, United Kingdom
23 h-index
69 publications
7.5K citations
Texas A&M University
College Station, United States
21 h-index
79 publications
2.5K citations
University of California, Berkeley
Berkeley, United States
21 h-index
57 publications
5.4K citations
Princeton University
Princeton, United States
19 h-index
40 publications
2.8K citations
University of Maryland, College Park
College Park, United States
18 h-index
43 publications
2.6K citations
University of Delaware
Newark, United States
17 h-index
51 publications
1.8K citations
Stanford University
Stanford, United States
17 h-index
42 publications
7.3K citations
Beijing University of Posts and Telecommunications
Beijing, China
16 h-index
90 publications
7.2K citations
1–8 of 430
Venues
- IEEE Transactions on Information Theory
86 publications · 11.8K citations
45
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- IEEE Transactions on Communications
67 publications · 2.8K citations
30
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- IEEE Journal on Selected Areas in Communications
24 publications · 2.6K citations
23
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- IEEE Transactions on Circuits and Systems for Video Technology
17 publications · 1K citations
15
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- IEEE Communications Letters
20 publications · 617 citations
15
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