Enhanced spectrum sensing based on Energy detection in cognitive radio network using adaptive threshold

Abstract

There's a huge demand for spectrum, but in conventional system radio spectrum is inefficiently used. To overcome this problem and increase array use of spectrum, cognitive radio (CR) technology concept was proposed. CR is the greatest mechanism for use spectrum efficiently. The main objective of CR is to use scarce and limited natural resources efficiently without any interference to the primary users (PUs). Among most challenging problems in cognitive radio systems is spectrum sensing concepts. Energy detection, Matched filter detection and Cyclostationary detections are most common strategies for spectrum sensing. This study has been performed based on Energy detection spectrum method. The reason for choosing Energy detection technique, it doesn't need any earlier information from the PU transmission. Also, the particular result of energy detection method degrades with lower sign to noises ratio (SNR) level signal location. General detection performance of Energy detection is highly dependent upon noise, especially while the SNR is very low for PU. Considering this issue, this paper presents an adaptive threshold model for efficient Energy detection technique to enhance the detection performance at low SNR level. Simulation outcomes show, the detection performance using offered system model is more preferable than fixed threshold at low SNR signal locations.