Machine-learning-based spectrum sensing method and apparatus

A technology of spectrum sensing and machine learning, applied in the field of spectrum sensing methods and devices based on machine learning, can solve the problems of difficult determination of decision threshold, noise uncertainty affecting detection performance degradation, and inaccurate spectrum detection results, etc.

Active Publication Date: 2017-11-17
佛山国防科技工业技术成果产业化应用推广中心
View PDF3 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

At present, the more classic spectrum detection methods include energy detection algorithm. However, in the energy detection algorithm, because the decision threshold is difficult to determine, it is easy to be affected by noise uncertainty in a low s

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Machine-learning-based spectrum sensing method and apparatus
  • Machine-learning-based spectrum sensing method and apparatus
  • Machine-learning-based spectrum sensing method and apparatus

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0063] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0064] The embodiment of the invention discloses a machine learning-based spectrum sensing method and device to obtain accurate spectrum detection results.

[0065] see figure 1 , a machine learning-based spectrum sensing method provided by an embodiment of the present invention specifically includes:

[0066] S101, extracting RMET features of the training signal;

[0067] Specifically, during training, firstly, when the primary user (PU) exists, the secondary us...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a machine-learning-based spectrum sensing method. An RMET feature of a training signal is extracted; a feature vector is determined based on the RMET feature and a classifier is determined according to a K-medoids algorithm and the feature vector; a testing signal is obtained at a current channel and a testing RMET feature of the testing signal is extracted; and the testing RMET feature is classified by using the classifier and a detection probability is calculated based on the classification result. According to the method disclosed by the invention, the RMET is used as the feature; the K-medoids algorithm is used for classification; the classifier is trained; data of the testing signal are inputted into the classifier to carry out classification and the classification result is obtained. On the basis of combination of the RMET and the K-medoids, whether a channel is available is sensed, so that the accuracy of detection is improved.

Description

technical field [0001] The present invention relates to the field of radio technology, and more specifically, to a machine learning-based spectrum sensing method and device. Background technique [0002] With the progress and development of radio technology, all walks of life have more and more demands on radio frequencies, and the problem of scarcity of spectrum resources is becoming more and more serious. At present, the spectrum resource adopts the management mode of national unified allocation and authorization, and the spectrum is divided into two types: authorized frequency band and unlicensed frequency band. Among them, licensed frequency bands occupy most of the spectrum resources, such as TV broadcasting frequency bands, but many licensed frequency bands are idle; unlicensed frequency bands open to use account for a small part of the entire spectrum resources, such as wireless local area networks, wireless metropolitan area networks and other wireless networks. Mos...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): H04W16/14H04W24/02H04B17/382
CPCH04W16/14H04W24/02H04B17/382
Inventor 张顺超万频王永华张勇威肖逸瑞
Owner 佛山国防科技工业技术成果产业化应用推广中心
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap