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Evidence-discount-based cooperative modulation identification method

A technology of modulation recognition and evidence discounting, applied in the field of communication, which can solve the problems of recognition errors, low recognition rate, deep fading, etc.

Inactive Publication Date: 2014-12-24
NANJING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

[0006] Technical problem: Due to problems such as deep fading, shadow effect and hidden nodes in the wireless communication environment, a single user may make mistakes in identifying the debugging mode in a certain period of time, especially when the signal-to-noise ratio is low, the recognition rate is very low. The present invention proposes A collaborative modulation identification method based on evidence discounting to address this problem

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  • Evidence-discount-based cooperative modulation identification method
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  • Evidence-discount-based cooperative modulation identification method

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Embodiment Construction

[0044]The characteristic parameter is the key to distinguish the modulated signal, and the extracted characteristic parameter is required to be insensitive to the signal-to-noise ratio, but sensitive to the modulation type. In addition, it is best for the parameters to be complementary, because some parameters cannot distinguish the modulation type of the signal under certain signal-to-noise ratios, but if there is another parameter that can distinguish the modulation type under this signal-to-noise ratio, the two can be combined A parameter completes the identification of the signal modulation type. Since there are many types of signals to be identified in the present invention, the recognition effect is not very good if only parameters based on instantaneous characteristics or high-order cumulants are used, so the present invention selects the following 7 characteristic parameters as the identification of these 11 modulations Signal characteristic parameters: 3 parameters ba...

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Abstract

The invention aims at providing an evidence-discount-based cooperative modulation identification method, wherein identification of eleven kinds of modulation modes can be completed by cooperation of a plurality of nodes. The specific process of the method is as follows: seven feature parameters for distinguishing modulation types are extracted respectively and individually from N nodes; the seven parameters are sent into a BP neural network that has been trained in advance for identification and the output of the neural network is sent to a fusion center; and the fusion center carries out fusion by using an evidence theory and the output of the neural network is used as a basic probability assignment function (BPAF) in a D-S evidence theory, the evidence is adjusted according to the signal-to-noise-ratio receiving situations of the nodes, and data of the N nodes are fused by the evidence theory, thereby obtaining a final identification result. Therefore, the contribution of data with the high signal to noise ratio to the fusion result can be improved; the influence of the data with the low signal to noise ratio on the fusion result can be reduced; and the fusion performance is effectively improved.

Description

technical field [0001] The invention relates to a cooperative modulation signal recognition method scheme based on decision-making layer data fusion, and belongs to the technical field of communication. Background technique [0002] Modulation recognition is an intermediate process between signal detection and information demodulation. Its task is to properly process the observation data of the signal of interest received by the receiver on the basis of signal detection and partial parameter estimation. According to a certain rule, it is judged that the signal belongs to one of several preset modulation forms, and the necessary information is provided for subsequent communication tasks such as information demodulation. [0003] Although the identification methods and strategies of communication signal modulation are various and complicated, at present, there are mainly two basic methods for identification and classification, one is the method of decision theory, and the othe...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L27/34
Inventor 朱琦朱冬梅
Owner NANJING UNIV OF POSTS & TELECOMM
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