Adaptive sampling spectrum sensing method and related device

Abstract

The invention provides a self-adaptive sampling spectrum sensing method, and the method comprises the following steps: inputting an acquired signal of a target frequency band into a trained neural network model to obtain a signal-to-noise ratio of the signal of the target frequency band, and according to the change of the signal-to-noise ratio of the signal of the target frequency band and the signal-to-noise ratio of the signal of the previous frequency band, dynamically adjusting the detection threshold and the sampling point number of the signal for detecting the target frequency band so as to determine whether a user uses the target frequency band, thereby reducing the influence of the change of the signal-to-noise ratio on the spectrum sensing, and improving the accuracy of the spectrum sensing.

Description

technical field [0001] The present disclosure relates to the field of radio technology, and in particular to an adaptive sampling spectrum sensing method and a related device. Background technique [0002] With the advent of the 5G era, the rapid development of the wireless communication field, and the increasing user demands, wireless spectrum resources have gradually become a scarce strategic resource. There are three reasons for the shortage of spectrum resources: First, countries around the world have a huge demand for spectrum, resulting in a shortage of spectrum resources. Second, the unreasonable allocation of spectrum resources in various countries in the world has caused a waste of spectrum resources. Third, the contradiction between algorithm efficiency and algorithm complexity is difficult to reconcile, resulting in low efficiency of spectrum resource utilization. This inspired a key technology in cognitive radio—the concept of spectrum sensing. Its main functi...

AI Technical Summary

Problems solved by technology

There are three reasons for the shortage of spectrum resources: First, countries around the world have a large demand for spectrum, resulting in a shortage of spectrum resources

Second, the unreasonable allocation of spectrum resources in various countries in the world has caused a waste of spectrum resources

Third, the contradiction between algorithm efficiency and algorithm complexity is difficult to reconcile, resulting in low efficiency of spectrum resource utilization

[0004] However, when the related technology executes the energy detection algorithm, it will be easily affected by the radio environment. When the radio environment becomes worse, that is, the signal-to-noise ratio becomes smaller, the detection performance will be significantly reduced.

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