Fast spectrum perception method in cognitive radio system

Abstract

The invention discloses a fast spectrum perception method in a cognitive radio system. The method comprises the following steps: calculating a decision threshold according to the given constant false alarm probability and the number of sampling points; then calculating relevant coefficients between adjacent sampling points according to sampling values of N sampling points of signals at a target frequency band; taking the relevant coefficients as test statistic; then comparing the test statistic with the decision threshold; and when the test statistic is more than the decision threshold, presenting that the target frequency band is used by a master user, and otherwise, presenting that the target frequency band is not used by the master user. The fast spectrum perception method has the advantages that the decision threshold can be calculated under the condition of any given constant false alarm probability and the number of the sampling points, namely, regardless of the number of the sampling points, the decision threshold meeting the requirement of the constant false alarm probability can be obtained rapidly by utilizing the method, thus the decision threshold can be obtained underthe condition of shortening the perception time when the number of the sampling points is small, thereby not only realizing fast spectrum perception, but also effectively reducing the error of constant false alarm probability.

Description

technical field [0001] The present invention relates to a cognitive radio technology, in particular to a fast spectrum sensing method in a cognitive radio system. Background technique [0002] With the rapid development of semiconductor technology, microelectronics technology and computer technology, wireless communication has been rapidly developed and applied, and has penetrated into various fields of society. The business provided by wireless communication has also developed from a single voice service that does not require high bandwidth to a broadband multimedia service that requires a wider spectrum. As the demand for spectrum resources continues to grow, the spectrum resources for wireless communications are becoming more and more scarce, which has become a bottleneck restricting the development of wireless communications. The shortage of spectrum resources for wireless communication is mainly manifested in the following two aspects: first, the unlicensed frequency b...

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Problems solved by technology

Among them, the energy detection method has been widely studied. It has the advantages of simple implementation, low complexity and no prior knowledge of authorized users. Poor performance at signal-to-noise ratio

Aiming at the problem that the energy detection method is sensitive to noise uncertainty, Naraghi-Pour et al. proposed a method in "Autocorrelation-Based Spectrum Sensing for Cognitive Radios" (autocorrelation-based spectrum sensing method in cognitive radio) published in 2010. A spectrum sensing method based on autocorrelation, which is not sensitive to noise uncertainty, but when deriving the probability density function of the test statistic, the method assumes that the number of sampling points for sampling the electromagnetic wave signal received by the cognitive user is sufficient, Then, the central limit theorem is used in the process of deriving the calculation method of the constant false alarm probability judgment threshold

When using this method, if we want to further improve the spectrum utilization rate of the cognitive radio system, that is to say, to quickly sense the spectrum, it is necessary to reduce the sensing time, and the reduction of the sensing time will inevitably lead to a reduction in the number of sampling points. However, when sampling When the number of points is small, the central limit theorem cannot be used in the calculation process of the constant false alarm probability judgment threshold. At this time, the judgment threshold obtained by the above autocorrelation-based constant false alarm probability judgment threshold calculation method will produce a large false alarm probability. error

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