Cooperative modulation signal identifying method based on data fusion of decision layer

Abstract

The invention discloses a cooperative modulation signal identifying method based on data fusion of a decision layer, belonging to the technical field of wireless communication. According to the cooperative modulation signal identifying method provided by the invention, a judging result of each receiving node is obtained by obtaining characteristic values of sample signals collected by a plurality of receiving nodes and using a support vector machine based on a binary tree decision; and a data fusion center uses a decision with a maximum posterior probability, so as to finally determine a modulation manner of signals to be identified. With the adoption of the cooperative modulation signal identifying method provided by the invention, the quantity of the support vector machines to be trained is reduced by using the SVM (Support Vector Machine) based on a binary tree, so as to improve the classification efficiency. An error caused by single-user detection is corrected by multi-user cooperative identification, particularly the identification rate at a low signal-to-noise ratio can be improved; and compared with the traditional voting fusion decision, the fusion decision with the maximum posterior probability has higher reliability of an identifying result by considering influences caused by a prior identification condition in a system and the judging results of the receiving nodes.

Description

technical field [0001] The invention relates to a cooperative modulation signal identification method based on decision-making layer data fusion, and belongs to the technical field of wireless communication. Background technique [0002] With the rapid development of electronic technology and communication technology, in order to make full use of communication resources, the modulation methods of communication signals are more diverse and complex. The constant changes in the communication environment make the signals in the same space more and more dense. In many fields (such as the field of electronic reconnaissance and spectrum monitoring), the receiver receives one or more unknown signals. In addition to monitoring the signal and estimating parameters for the signal of interest, it is also necessary to judge the modulation type of the signal, and On this basis, other communication tasks such as signal demodulation, threat assessment and other interference identification ...

AI Technical Summary

Problems solved by technology

However, since this method first needs to preprocess the original sensor information to obtain the respective judgment results, it also leads to high preprocessing costs.

In addition, the existing decision-level fusion mostly adopts the voting strategy to identify the modulated signal, and does not consider the prior situation identified in the system

The voting strategy relies on the independent judgment results of each receiving node, and does not consider the mutual influence of the judgment results of multiple receiving nodes, which reduces the accuracy of modulation signal recognition

[0005] At present, most modulation identification research is limited to a single node, but with the development of communication technology, modulation methods and signal systems are increasing day by day. In addition, the wireless communication environment is complex and changeable, and there are deep fading, shadow fading and hidden nodes. and other problems, making the signal modulation recognition results of a single node unstable, especially at low signal-to-noise ratios

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