Abstract
The paper discusses the hybrid sensing method and presents the hybrid detector (HD) which improves the sensing performance. The proposed HD takes advantage of the energy detection (ED) and a method based on the Covariance Absolute Value (CAV) or Cyclic Autocorrelation Function (CAF). The paper chara
Highlights
Cognitive radio systems [1][2] are an effective solution to the problem of spectrum scarcity, mainly owing to Dynamic Spectrum Access (DSA) to bandwidths that are temporarily not used by primary users (PU)
The purpose of the simulations was to check the efficiency of HDCAV and HDCAF in comparison to other available techniques (ED, Covariance Absolute Value (CAV), Cyclic Autocorrelation Function (CAF))
The proposed hybrid detectors were first tested for the ideal case, i.e. in an environment that did not take into account the uncertainty of spectral density of noise power estimation and the tests were repeated for an environment with such uncertainty
Summary
Cognitive radio systems [1][2] are an effective solution to the problem of spectrum scarcity, mainly owing to Dynamic Spectrum Access (DSA) to bandwidths that are temporarily not used by primary users (PU). Numerous spectrum scanning techniques have been proposed for cognitive radio systems, which have both advantages and disadvantages For this reason the literature dealing with the methods of spectrum sensing optimization in order to increase their efficiency proposes detectors with hybrid architecture, which combines advantages of various detection methods [3][4]. ED [5] is characterized by low computational complexity and simple implementation This method is a semi-blind detection which requires knowledge of spectral density of noise power for signal detection and as such, ED is sensitive to the uncertainty of its estimation [6][7]. In the literature [8][9] the results of HD research show the superiority of the hybrid method over others These publications refer to an ideal situation in which the uncertainty of spectral density of noise power estimation is not taken into account. The results obtained indicate that the optimization of the scenario by introducing the uncertainty of spectral power density estimation leads to significant deterioration of the results, but still allows us to achieve better HD detection properties in relation to other methods
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