Maximum Likelihood Channel Estimation
Maximum Likelihood Channel Estimation is a parametric estimation method that belongs to the class of statistical inference techniques in signal processing, distinguished by its use of maximizing the likelihood function of observed data to obtain the most probable channel parameters under assumed noise and signal models.
470
Publications
19K
Citations
916
Authors
373
Institutions
Publications per year
2017–2026
55
Variants
Mlce
Parents
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1–5 of 470
916
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University of Southern California
Los Angeles, United States
16 h-index
44 publications
1.5K citations

University of Alberta
Edmonton, Canada
14 h-index
25 publications
779 citations
California Institute of Technology
Pasadena, United States
10 h-index
18 publications
481 citations

University of Pisa
Pisa, Italy
9 h-index
19 publications
3K citations

McGill University
Montreal, Canada
9 h-index
17 publications
446 citations
EURECOM
Valbonne, France
8 h-index
17 publications
1K citations
National University of Singapore
Singapore, Singapore
7 h-index
11 publications
217 citations

University of Toronto
Toronto, Canada
7 h-index
13 publications
296 citations
1–8 of 373
54 publications · 3.3K citations
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44 publications · 2.9K citations
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35 publications · 1.5K citations
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28 publications · 1.7K citations
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21 publications · 717 citations
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