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It make use of the cyclostationary features of PU signal to determine the presence of PU signal. A signal is said to be cyclostationary if its mean and auto correlation are periodic with respect to a time period. These cyclostationary features are due to the periodicity from carrier waves, hopping sequences or pulse trains that are associated with modulation of PU signal. These cyclostationary features cannot be found in any interference signal or stationary noise. Hence these features can be exploited to identify the PUs. This method has higher noise immunity than energy detection especially in low SNR regions. Here, Cyclic Spectral Density CSD or Cyclic Spectral Correlation Function SCF is used for detecting the PU signals. By plotting SCF, we can nd out if spectrum is occupied by PU or not. A peak in the centre of SCF indicates the presence of PU and viceversa 25. The block diagram of cyclostationary feature detector is shown in the g 9. Fig. 9. Block diagram of cyclostationary feature detection Advantages: It performs better than any other detection method in the low SNR regions. Also, cyclostationary spectrum sensing method can be used to nd out the type of modulation scheme used by the PU signal. Disadvantages: It requires long sensing duration and has highly complex circuitry. Because of the high complexity involved, it also costs high. Inorder to reduce the circuit complexity of this method, a blind cyclostationary spectrum sensing is proposed in 26. Here, instead of nding CSD, sum of squares of magnitude of CSD is found out and used for the detection. This method has relatively low power consumption. Inorder to enhance the CR throughput and reduce the sensing duration, wide band spectrum sensing can be used 27. To enable fast sensing in wideband spectrum, a cooperative cyclostationary compressed algorithm is proposed in 28. This algorithm has two stages. The rst includes the cooperation between SUs and recovery of signal spectrum using compressive sensing whereas the second stage contains the cyclic feature detection.

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