Compressed spectrum sensing method based on autocorrelation matrix reconstitution

A technology for compressing spectrum sensing and autocorrelation matrix, which is applied in the field of communication, can solve the problems of detection performance loss and large calculation overhead, and achieve the effects of reducing sampling rate, avoiding performance loss, and reducing computational complexity

Inactive Publication Date: 2013-02-27
XIDIAN UNIV
View PDF5 Cites 23 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, there are still some problems: when the detection bandwidth is very large, reconstructing the power spectrum of the entire frequency band will still cause excessive computational overhead. At the same time, the estimation error of the power spectrum will also bring about a decrease in detection performance loss

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
  • Compressed spectrum sensing method based on autocorrelation matrix reconstitution
  • Compressed spectrum sensing method based on autocorrelation matrix reconstitution
  • Compressed spectrum sensing method based on autocorrelation matrix reconstitution

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] Principle of the present invention and technical scheme are further described below:

[0035] refer to figure 1 , the realization flowchart of the present invention is as follows:

[0036]Step 1, the secondary user uses the observation matrix Φ to perform compressed sampling on the analog signal x(t).

[0037] 1.1) Suppose the frequency range of the analog signal x(t) is [f min , f max ], there are N non-overlapping physical channels on this frequency for authorized users LU, their labels are 1, 2,..., N, each channel bandwidth is B, and it is assumed that the secondary user SU has each A priori information on subband locations.

[0038] Perform Nyquist sampling of x(t) through the analog-to-digital converter ADC, and take N points in the output sequence x[n] to form an N×1-dimensional sampling sequence x[k]:

[0039] x[k]=[x[kN],x[kN+1],...,x[kN+N-1]] T

[0040] Where T represents matrix transposition, k takes a positive integer, and N represents the total numbe...

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 compressed spectrum sensing method based on autocorrelation matrix reconstitution and mainly solves the problem that an existing sensing algorithm is high in sampling speed and large computation overhead. The compressed spectrum sensing method comprises that a secondary user obtains an observation sequence of a frequency spectrum environment through compressed sensing and obtains an autocorrelation matrix estimated value of Nyquist sampling by utilizing autocorrelation vector quantity of a autocorrelation matrix reconstitution Nyquist sample sequence of the observation sequence; a multi-signal classification MUSIC algorithm is adopted to obtain an estimated value of occupied channel number according to a characteristic value of the autocorrelation matrix estimated value; a characteristic spectrum is constructed according to the characteristic value and the estimated value of the occupied channel number, spectral amplitude values corresponding to characteristics of channels are added to obtain a sum, and mark numbers of the occupied channels are judged. By means of the compressed spectrum sensing method, the sampling speed of a secondary user receiving machine can be reduced, algorithm complexity at the reconstitution end is low, and spectral amplitude occupying situation in a cognitive radio system can be judged quickly.

Description

Technical field: [0001] The invention belongs to the technical field of communication, relates to a spectrum sensing method, and further relates to a compressed spectrum sensing method based on autocorrelation matrix reconstruction, which can be used in a cognitive radio system. Background technique: [0002] In recent years, the rapid growth of wireless communication has led to a sharp increase in the demand for wireless services on both licensed and unlicensed frequency bands. However, the current fixed spectrum allocation strategy makes spectrum usage inefficient. In order to solve the problems of spectrum resource shortage and low spectrum utilization, the concept of cognitive radio CR is proposed. The CR technology can effectively utilize unoccupied frequency bands, thereby improving spectrum utilization. In the CR system, one of the most important tasks of each secondary user SU is spectrum sensing, that is, to detect the radio frequency environment to determine whet...

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): H04B17/00H04B17/382
Inventor 赵林靖文璐李钊张文柱刘勤
Owner XIDIAN UNIV
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