A Spectrum Sensing Method Based on Wireless Fingerprint Database

Abstract

The invention relates to a spectrum sensing method based on a wireless fingerprint database, and belongs to the field of wireless communication. The method comprises the following steps: firstly, dividing a target geographic area into L grids with the same size; And when each PU position in the network is known in advance, determining SU access, detection or no access to the PU authorized frequency band according to the PU authorized frequency band availability label corresponding to the grid; when the position of the PU in the grid is unknown, by using the SVM algorithm, firstly predicting PPU working states at the moment, then predicting the grid position and availability labels of PU authorized frequency bands corresponding to N adjacent grids, then combining N + 1 grids, carrying outlabel data fusion on the PU authorized frequency band states of the geographic grid where the SU is located, and finally judging the frequency spectrum state. On the premise of ensuring the PU communication quality, the space spectrum resources of the SU are flexibly distributed, the sensing time is saved, and the spectrum utilization efficiency is further improved.

Description

technical field [0001] The invention belongs to the field of wireless communication and relates to cognitive radio frequency spectrum sensing technology. Background technique [0002] In recent years, the number of wireless network users and the demand for wireless services and applications have increased rapidly, and the amount of wireless network data has also increased rapidly. Due to the non-renewability of spectrum resources, the traditional static spectrum allocation method can no longer meet the growing demand for wireless communication spectrum. Therefore, more efficient spectrum access technology is needed to apply spectrum resources. The core idea of ​​cognitive radio (cognitive radio, CR) technology is to perceive the licensed spectrum status around it through the secondary user (SU), and adjust the parameters of the system itself, so that the SU can opportunistically use the spectrum in its space. free and available licensed spectrum. The basic premise of the C...

AI Technical Summary

Problems solved by technology

The energy detector also has corresponding disadvantages: First, the decision threshold is difficult to determine accurately, which is largely affected by the estimation accuracy of statistical characteristics of noise and interference; secondly, in the case of low SNR, the received PU signal Submerged in noise, the performance of energy detection is seriously insufficient; finally, energy detection only calculates the energy of the signal, and cannot distinguish the format of the PU signal in the received signal, nor can it distinguish between various components such as the PU signal, noise, and interference

For other detection methods, there are often problems such as strong dependence on prior information or the need to predict noise power information in terms of implementation.

[0006] (2) High requirements for SU equipment hardware

In the case of insufficient and incomplete prior information knowledge, spectrum sensing technology is still largely unable to fully and effectively protect the passive PU receiving end from SU interference

[0007] In summary, in view of the performance limitations of traditional spectrum sensing algorithms and the high cost and low implementation possibility caused by the high hardware requirements of SU equipment, a new spectrum sensing method is urgently needed to solve the above problems

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