Cyclostationary Feature Detection
Cyclostationary Feature Detection is a signal processing technique in cognitive radio systems that exploits the inherent cyclostationarity of communication signals to detect spectral holes by identifying periodic statistical features in the frequency domain, thereby distinguishing man-made transmissions from noise and interference.
149
Publications
8.5K
Citations
394
Authors
200
Institutions
Publications per year
2017–2026
30
Parents
149
1–5 of 149
394
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Memorial University of Newfoundland
St. John's, Canada
6 h-index
11 publications
667 citations
Virginia Tech
Blacksburg, United States
5 h-index
15 publications
2.1K citations
Wright State University
Dayton, United States
5 h-index
11 publications
266 citations

United States Air Force Research Laboratory
Wright-Patterson AFB, United States
5 h-index
5 publications
162 citations

Shanghai Jiao Tong University
Shanghai, China
5 h-index
14 publications
260 citations
University of California, Los Angeles
Los Angeles, United States
5 h-index
16 publications
520 citations

Trinity College Dublin
Dublin, Ireland
5 h-index
13 publications
2.1K citations
University of California, Berkeley
Berkeley, United States
4 h-index
11 publications
8.4K citations
1–8 of 200
MSSP · 7 publications · 429 citations
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5 publications · 189 citations
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4 publications · 163 citations
4
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4 publications · 126 citations
4
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3 publications · 128 citations
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