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DMWC Node Selection Method Based on Markov Random Field

A node selection and random field technology, applied in transmission monitoring, electrical components, transmission systems, etc., to achieve the best selection effect

Inactive Publication Date: 2020-09-08
SICHUAN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention aims to solve the problem of how the fusion center selects the optimal sensing node as the undersampling channel of DMWC, and provides a DMWC node selection method based on Markov random field

Method used

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  • DMWC Node Selection Method Based on Markov Random Field
  • DMWC Node Selection Method Based on Markov Random Field
  • DMWC Node Selection Method Based on Markov Random Field

Examples

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Embodiment Construction

[0017] Specific implementation examples are given below and the present invention is further described in conjunction with the accompanying drawings.

[0018] figure 1 is a flow chart of the DMWC node selection method based on Markov random field, the method includes the following steps:

[0019] Step 1: Determine the number of nodes, and determine the number of nodes that need to be increased according to the time-varying support set,

[0020] Reliable support set reconstruction requires a restriction on the number of undersampled channels, according to and , where m is the number of channels, N is the number of sub-bands, C is an independent constant integer, K is the degree of sparsity, it can be calculated that the time-varying support set N=6, when C=4, m is 50, that is, the number of nodes is 50 , minus the number of nodes at the previous moment, you can get the number of nodes that need to be added;

[0021] Step 2: Neighborhood system division, use the candidate ...

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Abstract

The invention relates to a DMWC node selection method based on a Markov random field for solving the problem of how to select an optimal sensing node to serve as an undersampled channel of DMWC by a fusion center. The method comprises the following steps: (1) determining the number of programs, and determining the number of to-be-added nodes according to a time varying support set; (2) dividing a neighborhood system, interacting prior knowledge with the fusion center by using a new candidate node, and paring neighbor nodes to accomplish neighborhood system division; (3) determining an energy function, calculating a self weight coefficient and an interaction weight coefficient of a center node by using the prior knowledge; and (4) judging whether the node is used as a DMWC sampling channel. The node selected by the method is used as the DMWC sampling channel, therefore the attenuation coefficient of the sampling channel can be improved, and then the reconstruction efficiency is improved.

Description

technical field [0001] The present invention relates to the field of collaborative electromagnetic spectrum sensing network and Markov random field intersection, in particular, relates to a method of using Markov random field in the sensing network to judge whether a node is used as a sampling channel of a distributed modulation broadband converter . Background technique [0002] Electromagnetic spectrum resources are a non-renewable resource. With the rapid growth of communication services, limited spectrum resources can no longer meet the needs of human beings. Seeking to improve the utilization of limited spectrum resources is the goal that humans are currently working on. Cognitive radio ( The emergence of CR) is a means to realize the effective utilization of spectrum resources. Compressed sensing (CS) breaks through the bottleneck of Nyquist sampling theorem, and can restore the original signal by using the undersampling method far lower than the Nyquist sampling rate...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04B17/382
CPCH04B17/382
Inventor 李智符博娟朱嘉微徐自勇
Owner SICHUAN UNIV