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

A performance optimization method and system for cognitive network

A technology of cognitive network and optimization method, applied in the directions of transmission system, energy consumption reduction, climate sustainability, etc., can solve the problems of main user network and cognitive network interference, harmful interference of main user communication, etc., and achieves a low probability of interruption. , the effect of improving the accuracy of the estimation

Active Publication Date: 2021-05-11
江苏移动信息系统集成有限公司 +1
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In practical applications, due to the existence of adverse factors such as noise, temperature, and wireless fading, missed detection and false alarms lead to mutual interference between the primary user network and the cognitive network, causing harmful interference to the primary user communication

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
  • A performance optimization method and system for cognitive network
  • A performance optimization method and system for cognitive network
  • A performance optimization method and system for cognitive network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0084] The cognitive network-oriented performance optimization method specifically includes the following steps: first, establish a cognitive network scene model; second, construct a spectrum sensing model of the node cluster according to the local perception of the node cluster, analyze signal changes in data transmission, and optimize Interruption performance; again, considering the influence of power allocation and node cluster head position on the interruption performance, the joint optimization of power allocation and node cluster head position is carried out. When there is an obstacle in the optimal node cluster head position, the surrounding performance is used The node cluster head assists in communication; secondly, model construction and analysis of the energy loss of the cognitive network, and introduce gamma distribution to improve the accuracy rate; finally, according to the comprehensive analysis results, select the corresponding optimization scheme.

Embodiment 2

[0086] On the basis of Embodiment 1, when each node cluster head can perform local perception, the local perception of the i-th node cluster head is:

[0087] In the formula, Indicates that the current primary user node is inactive, Indicates that the i-th cluster head receives the n-th sampling signal, Represents independent and identically distributed Gaussian noise;

[0088]

[0089] In the formula, Indicates that the primary user node is using the authorized channel, Indicates the power of the primary user node, Indicates the nth sampling signal sent by the primary user node, Indicates the complex channel gain of the sensing channel between the primary user node and the i-th secondary user node, Represents independent and identically distributed Gaussian noise.

[0090] According to spectrum sensing, nodes in a cognitive network can detect spectrum holes not occupied by primary user nodes, and then communicate data through the perceived spectrum holes. ...

Embodiment 3

[0094] On the basis of Embodiment 2, the interruption analysis in different situations is further divided into three situations. The first interruption situation occurs from the secondary user node to the node cluster head and then to the destination node, and the channel from the secondary user node to the destination node Both go through the stage of deep fading. At this time, the primary user node is inactive and the detection result of the secondary user node is correct, and the channel capacity is lower than the data transmission rate. The primary user node is inactive, and the judgment result of the secondary user node is wrong; the third interruption occurs in the stage of missing detection, at this time, the primary user node is active, and the secondary user node judges that the primary user node does not exist, And the channel capacity is lower than the data transmission rate.

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 embodiment of the present invention proposes a cognitive network-oriented performance optimization method and system. Through the joint optimization scheme of spectrum sensing, power allocation, and energy loss, the cooperation technology is adopted to effectively improve the cognitive network interruption performance and reduce the cognitive network performance. Outage probability, with the aim of improving the energy efficiency of cognitive networks. Wherein, the system implementing the method includes: a spectrum sensing module, an interruption performance optimization module, a transmission performance optimization module, and an energy consumption optimization module. In the energy consumption optimization module, through the statistical analysis of the energy in the cognitive network, as well as the distribution probability and energy estimation of the nodes, the optimal number of hops and the appropriate number of secondary users are selected to achieve the goal of optimizing network energy consumption.

Description

technical field [0001] The invention relates to a cognitive network-oriented performance optimization method and system, in particular to the technical field of H04W wireless communication networks. Background technique [0002] The definition of a cognitive network is a network that has cognitive capabilities, can perceive the current network environment, and make analysis, decision, and action based on these conditions. It has the ability to adapt to the network environment, and at the same time, it has the ability to judge the previous decision and learn the future decision with the end-to-end network as the goal. The cognitive radio network, like the traditional wireless network, contains at least one cognitive node, which can realize dynamic spectrum access, so that cognitive users can use the idle licensed spectrum. At the same time, network cognitive nodes can make full use of spectrum resources and alleviate the problem of wireless communication spectrum shortage by...

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 Patents(China)
IPC IPC(8): H04W40/02H04W40/22H04W40/32H04W40/12H04W40/20H04W52/02H04W72/04H04W72/08H04B17/382
CPCH04W40/02H04W40/22H04W40/32H04W40/12H04W40/20H04W52/02H04W72/0473H04B17/382H04W72/542Y02D30/70
Inventor 郭永安钟耀慧孙洪波孙天文罗浩姚洁陈筱丰
Owner 江苏移动信息系统集成有限公司
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com