A Cognitive Anti-jamming Communication Method Based on Reinforcement Learning Algorithm

A communication method and reinforcement learning technology, applied in wireless communication, transmission monitoring, network traffic/resource management, etc., can solve problems such as difficulty in learning effective anti-interference strategies, and achieve the effect of maximizing throughput

Active Publication Date: 2021-05-14
BEIJING UNIV OF TECH
View PDF5 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, in the proposed Q-learning anti-jamming technology, it is difficult to learn an effective anti-jamming strategy in a large-scale frequency domain-power domain candidate set

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 Cognitive Anti-jamming Communication Method Based on Reinforcement Learning Algorithm
  • A Cognitive Anti-jamming Communication Method Based on Reinforcement Learning Algorithm
  • A Cognitive Anti-jamming Communication Method Based on Reinforcement Learning Algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] Step (1): Set iteration time t = 0, time range T = 20000, according to perceived interference-free channels {1, 2} and power {4, 8, 12, 16}, form different frequency channels and transmit power combined subset {f u ,p v}, where f u ∈{1,2},f v ∈{4,8,12,16}, the index of each subset is marked as k∈{1,...,8}, all subsets constitute the set {{1,4},...,{2,16 }};

[0031] Step (2): At the initial time t=0, for any wireless network node j, traverse all subsets, calculate the metric value of wireless network node j for each subset, and obtain all subset metric values ​​corresponding to wireless network node j collection of

[0032] As an example, calculating the metric value of the k=1th subset of wireless network nodes j=1 The specific steps are as follows:

[0033] Step (2.1), first calculate the signal-to-interference-noise ratio of the k=1 subset selected by the wireless network node j=1 according to the selected channel and power Among them, the wireless network...

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 cognitive anti-jamming communication method based on a reinforcement learning algorithm. First, use spectrum sensing to obtain interference-free channels and power, form subsets composed of different frequency channels and transmit power, and mark the index values ​​of each subset, all these subsets constitute a candidate resource set; then, at the initial moment, Each node traverses all subsets, calculates the node's metric value for each subset, and obtains the set of all subset metric values ​​corresponding to the node; again, the node selects a subset corresponding to the maximum metric value from the set of corresponding metric values Set, update the metric value corresponding to the subset; finally, iteratively calculate the metric value within the time range T, and the subset corresponding to the largest metric value can maximize the node throughput. The present invention learns an optimal strategy by using a reinforcement learning algorithm, and each node independently adjusts channel selection and power distribution, so as to maximize the throughput of the anti-interference communication system and achieve the purpose of anti-interference.

Description

technical field [0001] The invention relates to the field of wireless communication, and relates to a communication anti-interference method for improving the capacity of a cognitive wireless network. Background technique [0002] At present, high-density, multi-band deployed wireless communication systems have brought serious electromagnetic interference. Therefore, while pursuing higher speed, longer distance and better service quality, the wireless communication system needs to greatly improve its anti-interference ability. [0003] Generally, spread spectrum anti-jamming and adaptive antenna technology are widely used in communication systems. Spread spectrum anti-interference is usually divided into direct sequence spread spectrum and frequency hopping. The anti-interference principle is to expand the signal spectrum in the frequency domain, thereby reducing the power density of the spectrum, so that useful signals are submerged in interference and environmental noise....

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): H04B17/309H04B17/336H04B17/382H04W28/02H04W28/20
CPCH04W28/0236H04W28/20H04B17/309H04B17/336H04B17/382
Inventor 黎海涛罗佳伟
Owner BEIJING UNIV OF TECH
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