Multi-cycle Cyclostationary based Spectrum Sensing Algorithm for OFDM Signals with Noise Uncertainty in Cognitive Radio Networks

摘要

This paper proposes a simple multi-cycle cyclostationary based signaldetection (spectrum sensing) algorithm for Orthogonal Frequency DivisionMultiplexed (OFDM) signals in cognitive radio networks. We assume that thenoise samples are independent and identically distributed (i.i.d) randomvariables all with unknown (imperfect) variance. Our detection algorithm employthe following three steps. First, we formulate the test statistics as a ratioof two quadratic cyclic autocorrelation functions. Second, we derive a closedform expression for the false alarm probability. Third, we evaluate thedetection probability of our algorithm for a given false alarm probability. Thetheoretical probability of false alarm expression matches with that of thesimulation result. Moreover, we have observed that the proposed multi-cyclealgorithm exhibits significantly superior probability of detection compared tothe existing low complexity cyclostationary based and the well known energydetection algorithms.