Spectrum sensing method, system and device

Abstract

The invention discloses a spectrum sensing method, which comprises the following steps: receiving sensing signals obtained by each secondary user, and respectively obtaining sensing signal matrixes corresponding to each secondary user according to the sensing signals; clustering the sensing signal matrixes, and performing matrix recombination on the sensing signal matrixes in each cluster to obtain a recombination matrix; converting the recombination matrix into a covariance matrix, and determining a feature vector of the sensing signal according to the covariance matrix and a Riemannian meanvalue; utilizing a K-medoids clustering algorithm to analyze the feature vector, to judge whether the main user exists or not. The spectrum sensing method can effectively improve the spectrum sensingperformance. The invention also discloses a spectrum sensing system and device and a computer readable storage medium which all have the above technical effects.

Description

technical field [0001] The present application relates to the field of cognitive radio technologies, and in particular to a spectrum sensing method; and also relates to a spectrum sensing system, device, and computer-readable storage medium. Background technique [0002] Cognitive radio is a method that can make full use of wireless spectrum resources, which allows secondary users to dynamically access spectrum without affecting the normal use of primary users. Among them, spectrum sensing, as the first step in the cognitive radio system, is mainly responsible for sensing whether the primary user exists. At present, there are many and different schemes for spectrum sensing, such as energy detection schemes, matched filtering schemes, and cyclostationary feature detection schemes. Regardless of which solution, there are defects in varying degrees, which affect the performance of spectrum sensing. For example, the decision threshold in the energy detection scheme is difficul...

AI Technical Summary

Problems solved by technology

Regardless of which solution, there are varying degrees of defects, which affect the performance of spectrum sensing.

For example, the decision threshold in the energy detection scheme is difficult to determine, and it is easily affected by noise uncertainty in the environment of low signal-to-noise ratio, resulting in misjudgment; the matched filter method needs to know the prior information of the main user in advance, which is not conducive to widespread use ; The algorithm of the cyclostationary detection method has a high degree of responsibility, a long detection time, and low detection efficiency; etc.

Images