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Minimizing of Error Detection Using Bartlett-DCT Periodogram in Cognitive Radio Networks

Mustafa Mahdi Ali 1 and Mokhalad Khaleel Alghrairi 2
1. Mustansiriyah University, Faculty of Engineering, Electrical Engineering Department, Baghdad, Iraq
2. Shiite Endowment, Baghdad, Iraq
Abstract—The Bartlett’s periodogram is widely used in the spectrum sensing applications since it does not need any pre-known information about the primary user signal. However, it is effected by the noise during detection process resulting high error ratio. In this paper, a minimizing error ratio of a periodogram using Bartlett-DCT estimator has been presented. The primary user signal is generated randomly and transmitted via AWGN channel. The estimator has been examined using three scenarios. The first scenario, the detected primary user signal has two modes; 2K mode and 8K mode. Then both modes applied with second scenario that is examined with different SNR values. Third scenario is examined both modes with various cyclic prefix values then all results have been compared with the traditional Bartlett’s estimator. All scenarios have been analysis by the Monte Carlo trials with two values for both modes. The results described that the proposed algorithm offer lower error ratio.
 
Index Terms—Spectrum sensing, Bartlett’s periodogram, Energy detection, discrete cosine transform

Cite: Mustafa Mahdi Ali and Mokhalad Khaleel Alghrairi, "Minimizing of Error Detection Using Bartlett-DCT Periodogram in Cognitive Radio Networks," Journal of Communications, vol. 14, no. 5, pp. 363-367, 2019. Doi: 10.12720/jcm.14.5.363-367
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