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Theoretical Analyses of Maximum Cyclic Autocorrelation Selection Based Spectrum Sensing
Shusuke NARIEDA Daiki CHO Hiromichi OGASAWARA Kenta UMEBAYASHI Takeo FUJII Hiroshi NARUSE
IEICE TRANSACTIONS on Communications
Publication Date: 2020/12/01
Online ISSN: 1745-1345
Type of Manuscript: PAPER
Category: Terrestrial Wireless Communication/Broadcasting Technologies
cognitive radio, maximum cyclic autocorrelation selection based spectrum sensing, signal cyclostationary,
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This paper provides theoretical analyses for maximum cyclic autocorrelation selection (MCAS)-based spectrum sensing techniques in cognitive radio networks. The MCAS-based spectrum sensing techniques are low computational complexity spectrum sensing in comparison with some cyclostationary detection. However, MCAS-based spectrum sensing characteristics have never been theoretically derived. In this study, we derive closed form solutions for signal detection probability and false alarm probability for MCAS-based spectrum sensing. The theoretical values are compared with numerical examples, and the values match well with each other.