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Let¡¯s dive into the core statistical model behind spectrum sensing. We frame this as a binary hypothesis testing problem: H0 means only noise is present; H1 means signal plus noise. We evaluate detectors using two key metrics: probability of detection (Pd), which should be high. Pd is the probability that the detector correctly identifies the presence of the PU when it is truly there, and the probability of false alarm (Pf), which should be low. Pf is the probability that the detector incorrectly identifies the presence of the PU when it is not there. In a conventional system, every method is decided by comparing a test statistic to a threshold.
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IEEE/ICACT20260241 Slide.06
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