Weighted frequency spectrum detection method of cognitive network based on signal correlation characteristics

A cognitive network and spectrum detection technology, applied in transmission monitoring, electrical components, transmission systems, etc.

Active Publication Date: 2016-12-21
HARBIN INST OF TECH
View PDF4 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The present invention aims to solve the following problems of the current spectrum detection method in the cognitive system:

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
  • Weighted frequency spectrum detection method of cognitive network based on signal correlation characteristics
  • Weighted frequency spectrum detection method of cognitive network based on signal correlation characteristics
  • Weighted frequency spectrum detection method of cognitive network based on signal correlation characteristics

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment approach 1

[0047] Specific embodiments 1. A weighted spectrum detection method based on signal correlation characteristics in a cognitive network,

[0048] First, the signal model is introduced: assume that each cognitive user has M cognitive antennas. The primary user signal reaches the receiving end of each cognitive user through the Rayleigh channel. Then receive the signal sampling vector at the kth moment, namely: x(k)=[x 1 (k),x 2 (k),...,x M (k)] T ,for:

[0049] x ( k ) = { w ( k ) H 0 s ( k ) ...

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 weighted frequency spectrum detection method of a cognitive network based on signal correlation characteristics. The method is used to solve problems such as influences of uncertainty of noise power on a conventional frequency spectrum detection algorithm, demands on a main user signal and noise signal priori knowledge, and weak detection performance in a low signal-to-noise ratio weak signal correlation system. Sampling is carried out, and a sample covariance matrix is calculated by using a sampling point. Corresponding detection statistic is calculated according to the sample covariance matrix. A decision threshold is calculated according to an expected false alarm probability. Whether the main user signal exists is determined by comparing the statistic with the decision threshold. The weighted frequency spectrum detection method is suitable for the frequency spectrum detection in the cognitive network, and whether the main user signal exists in the cognitive signal is determined.

Description

technical field [0001] The invention relates to the technical field of information and communication, in particular to a spectrum detection method in a cognitive network. Background technique [0002] Cognitive Radio (Cognitive Radio) can effectively improve the spectrum utilization rate of wireless systems, and has been widely concerned at present. Spectrum detection technology is a key technology of cognitive radio. Through spectrum detection, cognitive networks can use licensed frequency bands without causing interference to primary users. [0003] In order to improve the spectrum detection performance of cognitive systems, researchers have carried out a lot of related research, such as energy detection method ED (Energy Detection), matched filter method, cyclostationary feature detection method and signal correlation characteristic detection method. In general, these detection methods mentioned earlier need to exploit different degrees of prior knowledge of the receive...

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): H04B17/336H04B17/382
CPCH04B17/336H04B17/382
Inventor 贾敏王欣玉郭庆尹志胜王林方沈凌宇杨健
Owner HARBIN 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