Performance Analysis of the Cyclic-periodogram-based Signal Detector in Cognitive Radio

Abstract

Spectrum sensing in cognitive radio aims to quickly and accurately detect communication signals of primary or secondary users in frequency domain. One of the well-known spectrum sensing techniques is a periodogram-based energy detection method. Unlike the conventional detection scheme which draws one detection result in the observed samples in one time window, the periodogram-based energy detector compares the value of the periodogram to the pre-determined threshold on each FFT (fast Fourier transform) bin. Another spectrum sensing technique considered in the cognitive radio area is a cyclostationary detector. The cyclostationary detector is generally known for outperforming the energy based detector. However, the cyclostationary detector has not been applied to the periodogram-based detection scheme. In this paper, we analyze the performance of the cyclic-periodogram detector which derives the detection results on each FFT bin. Simulation results show that the detection performance of the multi-cycle detector using the multiple cyclic frequencies outperforms the single-cycle detector and the periodogram-based energy detector.