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Blind test method and device for modulation mode parameters, based on machine learning

A modulation method and machine learning technology, applied in the field of wireless communication, can solve the problem of low blind detection accuracy

Active Publication Date: 2018-11-27
BEIJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0004] The traditional maximum likelihood blind detection algorithm has high blind detection accuracy in high signal-to-noise ratio scenes, but low blind detection accuracy in low signal-to-noise ratio scenes

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  • Blind test method and device for modulation mode parameters, based on machine learning
  • Blind test method and device for modulation mode parameters, based on machine learning
  • Blind test method and device for modulation mode parameters, based on machine learning

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Embodiment Construction

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the application with reference to the drawings in the embodiments of the application. Apparently, the described embodiments are only some of the embodiments of the application, not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

[0028] An embodiment of the present invention provides a method for blind detection of modulation mode parameters based on machine learning. The method is applied to a terminal. The terminal is a receiving end for receiving a target signal sent by a sending device in a wireless communication system, such as a mobile phone, a smart phone, etc. Smart home devices such as meters. A wireless communication system generally includes a sending device that sends a target signal, a receiving...

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Abstract

The embodiment of the invention provides a blind test method and device for modulation mode parameters, based on machine learning, and belongs to the technical field of wireless communication. The blind test method for modulation mode parameters, based on machine learning includes the steps: acquiring constellation graph data of a first to-be-detected signal, and a pre-stored first candidate synthetic constellation sequence corresponding to a preset first interference device; determining a first feature vector of the first to-be-detected signal according to the first candidate synthetic constellation sequence and the constellation graph data, by means of a pre-stored feature extraction algorithm; determining a second feature vector corresponding to the first feature vector, according to the pre-stored feature mapping algorithm and the first feature vector; and determining modulation mode of the first interference device through the second feature vector, a pre-stored feature element ofthe first to-be-detected signal, and a pre-stored classification model. The blind test method for modulation mode parameters, based on machine learning can improve the blind test accuracy in a low signal to noise ratio scene.

Description

technical field [0001] The present application relates to the technical field of wireless communication, in particular to a method and device for blind detection of modulation mode parameters based on machine learning. Background technique [0002] In the non-orthogonal multiple access technology, the receiving end can learn the modulation mode of the interference device according to the characteristics of the signal to be detected through the blind detection algorithm, and then delete the interference signal in the signal to be detected according to the modulation mode of the interference device. [0003] The processing process of the commonly used maximum likelihood blind detection algorithm is as follows: 1. The receiving end combines the modulation mode of the target signal with the modulation mode that may be selected by the sending device to obtain multiple joint modulation modes, and generates a corresponding joint modulation mode for each joint modulation mode. Alter...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L27/00H04L1/00
CPCH04L1/0038H04L1/0091H04L27/0012
Inventor 程凯张宁波康桂霞
Owner BEIJING UNIV OF POSTS & TELECOMM
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