Method for detecting perception radio collaboration frequency spectrum based on SNR compare

Abstract

The invention applies for the protection of an SNR comparison-based algorithm for cooperative frequency spectrum sensing in cognitive radio and relates to a wireless communication system. The method comprises: SNR estimation technology is applied to cognitive radio; SNRs of signals received by sensing nodes are used as reliable references for the sensing nodes; the sensing nodes transmit local sensing results and estimated SNR values to a fusion center; and in the fusion center, the SNRs from the sensing nodes are compared and sensing nodes with good SNR are selected according to a selection algorithm provided by the invention for judgment and fusion. The algorithm of the can effectively improve frequency spectrum sensing performance and reduce the nodes for judgment and fusion.

Description

A Cooperative Spectrum Detection Method Based on SNR Comparison for Cognitive Radio technical field The present invention relates to the field of wireless communication, in particular to cognitive radio technology. Background technique To improve the detection performance of idle spectrum in Cognitive Radio (CR), a cooperative spectrum detection algorithm based on multi-user cooperation is proposed, which uses a distributed detection system to overcome severely attenuated received signal energy. In the cooperative spectrum detection method, there are many classic algorithms to fuse local judgments and obtain global judgments, such as K / N criterion and so on. However, these guidelines do not take into account the reliability differences of the local detection results of each node. References [PengQihang, ZengKun, WangJun, "aDistributedSpectrumSensingSchemebasedonCredibilityandEvidenceTheoryinCognitiveRadioContext[C]", IEEE17thInternationalSymposiumonPersonal, IndoorandMobi...

AI Technical Summary

Problems solved by technology

However, in the actual cognitive radio network environment, the local detection of sensing nodes is not always completely reliable. Since the sensing nodes are randomly distributed and the distances from the transmitter of the main user are different, the fading and shadow effects experienced by signal transmission are not the same, and ideal power control cannot be achieved in the initial stage of idle spectrum detection. These factors lead to different SNRs of signals received by each sensing node, which will affect the reliability of sensing nodes.

That is to say, those sensing nodes that have experienced severe fading and shadowing (i.e. nodes with low SNR of the received signal), because the received signal is too weak, the reliability of the detection result of the signal is low, so It will have a great impact on the decision fusion performance of cooperative spectrum detection

This is because the sensing nodes in deep fading will have serious false alarms or missed detections, and the information of these sensing nodes with wrong judgments will participate in the final cooperative judgment. As a result, when the number of such nodes is large, The performance of cooperative spectrum detection will be degraded

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