Spectrum Sensing Using Matched Filter Detection
Increasing use of wireless applications is putting a pressure on licensed spectrum which is insufficient and expensive. Indeed, because of allocation of fixed spectrum, more portion of spectrum is underutilized. Spectrum sensing can be used for efficient use of the radio spectrum. It detects the unused spectrum channels in cognitive radio network. In cognitive radio, spectrum sensing techniques such as energy detection, cyclostationary feature-based spectrum sensing technique, matched filter detection, etc., have been used. When user information is available, matched filter-based sensing gives better performance. In this paper, the probability of detection (PD) and probability of false alarm (PFA) at different SNR levels are observed. Matched filter detection performance depends on threshold value to detect the primary user. At 25 dB SNR, better probability of detection is observed for a given PFAs.
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