Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Broadband distributed Bayes compression spectrum sensing method

A Bayesian compression and spectrum sensing technology, applied in the field of computer communication, can solve the problem that the signal reconstruction algorithm does not take into account the prior knowledge of the signal, etc.

Inactive Publication Date: 2015-11-18
NANJING UNIV OF POSTS & TELECOMM
View PDF2 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In compressed sensing theory, traditional signal reconstruction algorithms do not take into account the prior knowledge of the signal

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
  • Broadband distributed Bayes compression spectrum sensing method
  • Broadband distributed Bayes compression spectrum sensing method
  • Broadband distributed Bayes compression spectrum sensing method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0039] Such as figure 1 As shown, the cognitive radio system involved in the present invention uses a wide range of frequency bands, and the primary user and the secondary user share the frequency band within the entire wide frequency range. Opportunity to access. In order to facilitate research, the present invention divides the whole broadband spectrum into several sub-frequency bands, from figure 1 It can be seen that the black part of the sub-frequency band indicates that it is occupied by the primary user, and the primary user randomly occupies the sub-frequency band, and the blank part of the sub-frequency band indicates that it is not occupied and can be used by secondary users. The amplitude of each sub-band can be unequal, and the occupied sub-band is a small part compared to the entire broadband, so its spectrum data is sparse in the entire broadband range, and it has the possibility of being compressed in the frequency domain. exist figure 1 In , the spectrum sen...

Embodiment 2

[0060] Such as image 3 As shown, the present invention assumes that the total bandwidth that the cognitive user needs to detect is BHz, which can be continuously and evenly divided into L non-overlapping sub-bands, and the edge position frequency of each sub-band is respectively f 0 ... f L+1 , and have f i j (ij , assuming it satisfies the conditional probability p(s j |β j ), let the reciprocal of the noise variance of the jth user be α 0,j =1 / σ j 2 , the measured value y of the jth user j in condition s j and alpha 0,j The following is a random process with conditional distribution probability p(y j |s j ,α j,0 ), where α 0,j and beta j are hyperparameters.

[0061] Method flow:

[0062] The invention provides a wideband distributed Bayesian compressed spectrum sensing method, which comprises the following steps:

[0063] Step 1: J cognitive users perceive the signal to be tested, so that the signal passes through J AIC converters, and the J noise variance ...

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 broadband distributed Bayes compression spectrum sensing method. The method is applied to detection of broadband spectrum occupation condition in a cognitive radio system and is a new method for spectrum sensing in a broadband range by use of a Bayes compression sensing technology. The actual distribution condition, with which Bayes parameters are in compliance, is considered under the spectrum sensing condition of the distributed multiple cognitive users. Due to introduction of a Laplace hierarchical prior model, experience information occupied by spectrum is fused in the detection process. Cooperative detection of multiple cognitive users is fully considered, reconstruction errors brought about by compression sensing are reduced to the greatest extent through a distributed joint reconstruction algorithm, and the spectrum occupation condition of each sub-band can be detected rapidly and accurately.

Description

technical field [0001] The invention relates to the technical field of computer communication, in particular to a broadband distributed Bayesian compressed spectrum sensing method. Background technique [0002] Radio frequency spectrum is an important and scarce resource. At present, radio frequency bands are mainly assigned and authorized by the management department, and the spectrum allocation method of static and fixed frequency bands is adopted. The wireless spectrum management methods of various countries are basically the same. They all divide the wireless spectrum into several continuous frequency bands, and each frequency band is allocated to a specific authorized user. In order to ensure the normal access and operation of each wireless device, sufficient protection bandwidth is reserved between each frequency band to avoid interference. Due to the increasing demand for radio spectrum use, there are almost no spectrum resources available for allocation within a cert...

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): H04B17/382H04L27/00
Inventor 王韦刚胡海峰涂真珍
Owner NANJING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products