Spectrum Sensing Method
Adaptive Double Threshold 
Energy Detection 
Table 3 shows the detection performance of the proposed and conventional spectrum sensing methods under the noise uncertainty. It is clear from Table 3 that the proposed spectrum sensing scheme using skewness function offers a 5 dB SNR improvement compared with that of adaptive double threshold based spectrum sensing and a 21 dB SNR gain compared with that of energy detection. Furthermore, in the proposed method, when the kurtosis function is used for spectrum sensing, it provides a 6 dB SNR improvement relative to that of the adaptive double threshold based spectrum sensing and a 22 dB SNR gain relative to that of the energy detection of the conventional autocorrelation based spectrum sensing method. As a result, the proposed method significantly outperforms the conventional spectrum sensing methods.
The proposed method is an effective spectrum sensing scheme considering the poor sensing performance in severe noise and noise uncertainty environments. The higher order statistics, such as skewness function and kurtosis function, are exploited for sensing OFDM primary user signals. The proposed method is applicable under higher order digital modulation for various CP radios with noise uncertainty cases, which is very important for various OFDM based systems. The skewness calculation significantly improves the detection performance of the OFDM transmitted signal compared to the conventional methods, considering the noise uncertainty effect in severe noise environments. In the proposed method, the kurtosis calculation has a tendency to provide a further SNR gain relative to the corresponding skewness calculation considering the effect of noise uncertainty.
The authors would like to thanks Saitama University for supporting this research academically.
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* Mousumi Haque