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

Skip spectrum sensing method based on reinforcement learning

A spectrum sensing and reinforcement learning technology, applied in machine learning, transmission monitoring, instruments, etc., can solve problems such as reducing transmission data time and affecting transmission effectiveness, and achieve the effect of reducing perception overhead, low perception overhead, and high transmission efficiency

Active Publication Date: 2021-02-12
DALIAN UNIV OF TECH
View PDF5 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Sensing before each time slot transmission can effectively control the interference of secondary users to primary users, but frequent spectrum sensing will reduce the time of data transmission, affect the effectiveness of transmission, and also bring huge energy consumption for perception overhead

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
  • Skip spectrum sensing method based on reinforcement learning
  • Skip spectrum sensing method based on reinforcement learning
  • Skip spectrum sensing method based on reinforcement learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0025] The specific implementation of the present invention will be described in detail below in conjunction with specific examples, and the method of the present invention is not limited to the specific examples. Consider a time-slot system composed of a pair of cognitive radio transceivers. There are 4 channels for dynamic access, and the transmitter can select 2 channels for data transmission. Set the maximum number of skipped slots to 5. The concrete steps of the inventive method are as follows:

[0026] 1. Establish a Q table for all "state-action" pairs, initialize all values ​​in the Q table to 0, and set the initial state as 4 channels are all idle;

[0027] 2. Select 2 channels to access, and the selection method is as follows: select the action with the largest Q value among all actions in the state s corresponding to the Q table with probability 1-ε, that is, An action is randomly chosen with probability ε. This operation is performed twice, and when it is perfo...

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 skip spectrum sensing method based on reinforcement learning, belongs to the field of wireless communication, particularly relates to a cognitive radio technology, and provides a low-overhead and intelligent spectrum sensing method for dynamic access of a spectrum. In consideration of the continuous characteristic of the idle state of the frequency spectrum, the method allows the equipment to skip part of sensing time slots when accessing a channel, and compared with the traditional periodic sensing strategy, the method can reduce the sensing overhead and improve the transmission efficiency. According to the method, a reinforcement learning algorithm is adopted, a channel occupation condition is taken as a state, channel selection and sensing skip time slot are taken as actions, and different actions in different states are evaluated, so that the equipment can intelligently make an optimal strategy. The method does not depend on a specific spectrum state statistical model, and the equipment can determine the optimal access and perception strategy in a self-adaptive manner through the learning of the environment.

Description

technical field [0001] The invention belongs to the technical field of wireless communication, and relates to a hopping spectrum sensing method based on a reinforcement learning algorithm, in particular to cognitive radio and dynamic spectrum access. Background technique [0002] In recent years, with the rapid development of the Internet of Things, the amount of data that mobile wireless networks need to carry is increasing day by day, and spectrum has gradually become a scarce and important natural resource. Cognitive radio technology can use spectrum sensing and dynamic spectrum access to allow secondary users to access vacant frequency bands without affecting the use of spectrum owners (primary users), so as to effectively use vacant spectrum resources, improve spectrum utilization efficiency, and expand Network capacity is regarded as one of the important enabling technologies for mobile wireless networks in the future. [0003] Spectrum sensing is an important part of...

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): H04B17/382H04W72/04G06N20/00
CPCH04B17/382H04W72/0453G06N20/00H04W72/53
Inventor 李轩衡董一锋张雨浩孙弘毅张仁浩丁海川
Owner DALIAN UNIV OF TECH
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