Cognitive radio spectrum sensing method based on connected component number characteristics

A technology of cognitive radio and connected components, which is applied in the field of cognitive radio spectrum sensing based on the characteristics of the number of connected components, can solve problems such as poor performance and achieve excellent performance

Active Publication Date: 2022-04-01
JINLING INST OF TECH
View PDF6 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This kind of method, on the one hand, uses the topological representation of the graph to further mine and utilize the transfer relationship information between signal sampling points, and quantizes the signal samples during the graph-domain transformation, which is beneficial to suppress noise to some extent. But its performance is not good at low signal-to-noise ratio

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
  • Cognitive radio spectrum sensing method based on connected component number characteristics
  • Cognitive radio spectrum sensing method based on connected component number characteristics
  • Cognitive radio spectrum sensing method based on connected component number characteristics

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] The present invention is described in further detail now in conjunction with accompanying drawing.

[0044] figure 1 It shows a flow of a cognitive radio spectrum sensing method based on the number of connected components, and the specific process includes the following steps:

[0045] 1. De-mean processing

[0046] The observation signal x(t) composed of the transmission signal s(t) through the path loss and the additive Gaussian white noise w(t) is expressed as:

[0047] x(t)=s(t)+w(t)

[0048] in

[0049]

[0050] where ξ(δ) represents the δth information symbol sample, and g(t) represents the 0A continuous-time waveform that carries an information sample at an instant of , g(t-δT 0 ) represents the pulse corresponding to the δth symbol; at the receiving end, x(t) is at the sampling frequency is oversampled, Q is the oversampling factor;

[0051] The set of N consecutive received signal samples is expressed as:

[0052] x(n)=s(n)+w(n)

[0053] In the for...

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 provides a cognitive radio spectrum sensing method based on connected component number characteristics, which comprises the following steps of: performing de-averaging processing on an observation signal, calculating an autocorrelation function of the de-averaged observation signal, and converting the autocorrelation function into a graph domain to obtain an undirected simple graph with a specific number of vertexes and edges; and extracting the number of connected components of the graph as a test statistic, and comparing the statistic with a specific threshold to judge whether the main user signal spectrum is idle or not. According to the method, whether the main user signal spectrum is idle or not can be detected under the condition of an extremely low signal-to-noise ratio, the performance of the method is superior to that of an existing common cognitive radio spectrum sensing algorithm based on energy detection, normality detection and complete graph features, feature decomposition needs to be carried out in the calculation process, and the method is particularly suitable for occasions with different real-time performance.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a cognitive radio spectrum sensing method based on the number characteristics of connected components. Background technique [0002] In recent years, with the rapid development of wireless communication technology, the number of wireless access devices has increased rapidly, and spectrum resources have become increasingly scarce. Cognitive Radio (CR), as a dynamic opportunistic spectrum access mechanism, provides a more effective solution to improve the utilization efficiency of spectrum resources. For the CR system, spectrum sensing is the premise and basis for its effective work, and its task is to check whether the primary user channel is occupied. At present, commonly used spectrum sensing algorithms usually extract features and perform spectrum sensing from the perspectives of time domain, frequency domain, transform domain and probability density func...

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
Patent Type & Authority Applications(China)
IPC IPC(8): H04B17/382H04B17/391
CPCY02D30/70
Inventor 胡国兵赵敦博赵嫔姣陈正宇杨莉姜志鹏
Owner JINLING INST OF TECH
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