Spectrum sensing algorithm based on variational mode decomposition

Abstract

The invention discloses a spectrum sensing algorithm based on variational mode decomposition, and solves the problem that a signal at a receiving end is interfered by a noise background in the prior art. The method comprises the following steps of: 1, generating a simulation signal BPSK; 2, taking the mean value of the instantaneous frequencies of the components as a decomposition parameter, determining an optimal mode decomposition number K according to a change curve of the decomposition parameter, and setting an appropriate penalty factor alpha; 3, performing variational mode decompositionon the BPSK signal according to the obtained decomposition parameters; 4, respectively carrying out power spectrum estimation on the obtained L intrinsic modes; 5, taking the ratio of the sum of the spectral line intensities of the intrinsic modes to the sum of intensities of all the intrinsic modes as a test statistic; and 6, comparing the obtained test statistics with a judgment threshold, and making a final judgment. According to the method, the equivalent band-pass filtering characteristic and the Wiener filtering structure of variational mode decomposition are utilized, frequency bands are better divided, and denoising processing is better carried out; and compared with a traditional power spectrum segmented cancellation algorithm, the detection performance can be remarkably improved.

Description

technical field [0001] The present invention relates to the field of cognitive radio technology, in particular to a spectrum sensing algorithm based on variational mode decomposition. Background technique [0002] Spectrum sensing means that cognitive users obtain spectrum usage information in wireless networks through various signal detection and processing methods. From the perspective of functional layering of wireless networks, spectrum sensing technology mainly involves the physical layer and the link layer. Collaborative perception and perception mechanism optimization and other three aspects. The signal detection studied in this paper is actually the content that needs to be paid attention to and researched at the physical layer in spectrum sensing. [0003] The classic signal detection algorithms in spectrum sensing mainly include energy detection, matched filter detection, cyclostationary feature detection, and eigenvalue detection. Energy Detection (ED) does not...

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Problems solved by technology

[0005] The present invention overcomes the problem that the signal at the receiving end is interfered by the noise background in the prior art, and provides a spectrum sensing algorithm based on

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