Matched Filter Based Spectrum Sensing on Cognitive Radio for OFDM WLANs
For the unlicensed users to use the licensed spectrum, unused frequency bands called white spaces need to be detected. Cognitive Radio does this task by dynamic spectrum access. This requires intelligent spectrum sensing techniques. In this paper, such unused spectrum for OFDM WLAN (IEEE 802.11a) is predicted by exploring the signals presence in minimum time using matched filter based detection incorporating optimal threshold selection, thereby increasing the sensing accuracy and interference reduction of secondary network.