Cooperative spectrum sensing method based on characteristic values

Abstract

The invention discloses a cooperative spectrum sensing method based on characteristic values. The new cooperative spectrum sensing method based on the characteristic values - SMEE method is provided under an MIMO multi-channel environment. According to the method, a spectrum sensing threshold is obtained through Monte Carlo simulation, and the threshold is compared with the ratio between the maximum characteristic value and the minimum characteristic value lambda max / lambda min of the covariance matrix of received signals to judge whether signals of an authorization main user exist. The method does not need the priori knowledge of channels and signals, is not affected by the uncertainty of noise, effectively improves the sensing performance of spectrum sensing under the conditions of a low signal-to-noise ratio and small samples, and can carry out normal sensing under any given dimension.

Description

technical field [0001] The invention relates to the technical field of computer communication, in particular to a collaborative spectrum sensing method based on eigenvalues. Background technique [0002] At present, with the ever-increasing demand for wireless spectrum resources from the growing wireless services, and the inherent spectrum resource allocation methods, the available spectrum resources are increasingly scarce, making how to improve spectrum efficiency has become a key issue before people. Faced with this situation, cognitive radio came into being. The basic idea of ​​cognitive radio is spectrum reuse or spectrum sharing, which allows cognitive users to use the frequency band for communication when the primary user frequency band is idle. In order to achieve this, cognitive users need to perform spectrum sensing frequently. Therefore, the task of spectrum sensing is to find and utilize idle frequency bands of the authorized primary user spectrum. The high det...

AI Technical Summary

Problems solved by technology

However, its conclusions are complex and abstract, and it is difficult to apply them in practice

[0004] At the same time, in the case of low signal-to-noise ratio of the above methods, the detection performance of spectrum sensing is not ideal

In summary, the detection performance of existing eigenvalue-based spectrum sensing methods is far from meeting the needs of practical applications in the case of low SNR and small samples.

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