Blind spectrum sensing method and device based on low-rank sparse matrix decomposition

Abstract

The invention discloses a blind spectrum sensing method based on low-rank sparse matrix decomposition. The method includes: receiving wireless signals of a to-be-sensed frequency band, and sampling to obtain observation signals; performing discrete time Fourier transformation on the observation signals to obtain transformed observation signals; performing low-rank sparse decomposition on the transformed observation signals according to the sparse factors of set low-rank factors to obtain low-rank elements and sparse elements; performing reverse discrete time Fourier transformation on the low-rank elements and the sparse elements to obtain transformed low-rank elements and transformed sparse elements, and acquiring final observation signals according to the transformed low-rank elements and the transformed sparse elements; calculating the average energy value of the transformed sparse elements and the final observation signals in a time domain to obtain a sparse energy value and a final observation signal energy value, and judging whether the to-be-sensed frequency band is idle or not according the relation of the sparse energy value and the final observation signal energy value with a preset judging threshold. The method is applicable to spectrum sensing with uncertain noise and high in sensing precision.

Description

Technical field [0001] The present invention relates to the technical field of cognitive radio, in particular to a blind spectrum sensing method and device based on low-rank sparse matrix decomposition. Background technique [0002] The radio frequency spectrum plays a vital role in wireless communication, so the radio frequency spectrum is a precious resource that is strictly controlled. With the rapid development of wireless communication technology, the demand for radio frequency spectrum has continued to grow, resulting in an extreme shortage of radio frequency spectrum resources. According to a report by the Federal Communications Commission (FCC: Federal Communication Commission), the current utilization rate of authorized radio spectrum is only about 30%, indicating that the scarcity of spectrum is only an artificial result of the spectrum management and registration process. To this end, the FCC issued a new policy that allows unlicensed users to selectively use spectrum...

AI Technical Summary

Problems solved by technology

According to the current research status, the detection performance of spectrum sensing is severely degraded in strong noise environments such as battlefields, which significantly increases the probability of false positives and false positives of detection results.

Obviously, the noise in the wireless channel seriously affects the accuracy and reliability of spectrum sensing; noise uncertainty has become a bottleneck restricting the development of spectrum sensing technology, and even an insurmountable obstacle in the entire wireless communication

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