A Dual-Eigen Spectrum Sensing Method Based on Maximum Eigenvalue and Principal Eigenvector

Abstract

The invention discloses a double-feature spectrum sensing method based on maximum feature values and main feature vectors. The method comprises the steps of calculating the maximum feature values andthe corresponding main feature vectors of covariance matrixes of signals received in a current sensing time slot and a plurality of previous continuous sensing time slots; obtaining the estimated value of the main feature vector of the covariance matrix of a licensed user signal and the estimated value of the maximum feature value of the covariance matrix of white gaussian noise according to the corresponding maximum feature values and the corresponding main feature vectors in the plurality of previous continuous sensing time slots; obtaining a first test statistics value and a second test statistics value according to the maximum feature value, the main feature vector and the two estimated values of the covariance matrix of the signal received in the current sensing time slot; and comparing the first test statistics value with a first judgment threshold, and comparing the second test statistics value with a second judgment threshold, thereby realizing spectrum sensing. The method hasthe advantage of effectively improving the spectrum sensing performance.

Description

technical field [0001] The invention relates to a spectrum sensing method in a cognitive radio system, in particular to a dual-feature spectrum sensing method based on a maximum eigenvalue and a main eigenvector. Background technique [0002] With the continuous development of mobile communication, the number of wireless users continues to increase, and people's demand for wireless communication is also increasing. Wireless spectrum resources have become an indispensable and important resource in modern society. However, a large number of studies have shown that the traditional fixed spectrum allocation management mechanism leads to a large number of spectrum resources not being fully utilized, resulting in the contradiction between the shortage of spectrum resources and low spectrum utilization. Therefore, improving spectrum utilization has become a key issue to solve this contradiction. In this case, once the concept of cognitive radio was proposed, it has been widely con...

AI Technical Summary

Problems solved by technology

However, the above-mentioned existing spectrum sensing methods only utilize a single feature of the eigenvalue or eigenvector, which greatly limits the performance of its spectrum sensing

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