| With the rapid development of wireless communication services, wireless spectrum resource is increasingly scarce, and the cognitive radio technology provides a new situation. Because of the frequency hopping communication has many advantages, more and more attention industry standard. Spectrum detection is the primary basis of cognitive radio. This dissertation researches and analyzes the fixed-frequency interference on the primary users by frequency hopping communication mode in spectrum detection, and completes the following innovative results:The traditional time-domain autocorrelation algorithm hardly detects the primary users when the fixed-frequency interference burst. For the problem, according to the frequency hopping signal power spectrum changing with time difference and the Wiener Khintchine theorem (power spectrum and autocorrelation function is a pair of Fourier transform), this dissertation by using power spectrum elimination to improve the traditional time-domain autocorrelation algorithm. Simulation analyses show that the improved time-domain autocorrelation method not only can improve the detection performance, but also can prevent the collision between the fixed-interference frequency and the frequency of the primary user.When the fixed-frequency interference burst, the traditional time-frequency analysis method also can’t detect the primary users by frequency hopping communication mode. For the problem, this dissertation combines the Yin destroyed filter technology and traditional time-frequency analysis method to suppress fixed-frequency interference and detect the primary users. Simulation analyses show that this method improves the accuracy of cognitive radio spectrum detection.Finally, the full text is summarized in this paper, and prospect some questions about the primary users detection in cognitive radio frequency hopping communication by bursting fixed-frequency interference. |
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