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The aim of this study is to use the Discrete Cosine Transform (DCT) instead of the previous methods which used the discrete Fourier transform (DFT) to detect the signal of a primary user by the Bartlett periodogram method. In this study the Digital Video Broadcast-Terrestrial (DVB-T) signals are used as an application example to analyze and assess the proposed spectrum sensing algorithm in the frequency domain using the AWGN channel. The study concludes that an accurate performance analysis of energy detection, reducing the noise variance without decreasing the signal resolution compared with the Bartlett periodogram based on DFT. By using 16-QAM modulation it can be seen the average variance of the noise in the DCT in all the scenario is 0.3478, while in FFT is 5841.37. This is mainly due to DCT being a real transform possessing an energy compaction property and the leakage effect is not there for DCT as compared to DFT. The Monte Carlo trials are used to confirm the accuracy of the proposed analysis. To obtain good accuracy with low noise variance to implemented the system in low complexity, it is required to use some trade-off between Probability of Detection (PD) and the Probability of False Alarm (PFA).

New Detection Scheme in Cognitive Radio by using 16-quadrature Amplitude Modulation for Bartlett Periodogram