A hidden anti-jamming method based on deep reinforcement learning

12/23/2020
by   Xin Liu, et al.
0

Most of the current anti-jamming algorithms for wireless communications only consider how to avoid jamming attacks, but ignore that the communication waveform or frequency action may be obtained by the jammers. Although existing anti-jamming methods can guarantee temporary communication effects, the long-term performance of these anti-jamming methods may be depressed when intelligent jammers are capable of learning from historical communication activities. Aiming at this issue, a hidden anti-jamming method based on the idea of reducing the jammer's sense probability is proposed. Firstly, the sensing probability of the jammer is obtained by calculating the correlation between the actions of the jammer and the user. Later, a deep reinforcement learning framework is designed, which aims at not only maximizing the communication throughput but also minimizing the action's correlation between the jammer and the user. Finally, a hidden anti-jamming algorithm is proposed, which links the instantaneous return with the communication quality of users and the correlation between users and jammer. The simulation result shows that the proposed algorithm not only avoids being sensed by the jammer but also improves its anti-jamming performance compared to the current algorithm that only considers jamming avoidance.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
02/13/2020

Fast Reinforcement Learning for Anti-jamming Communications

This letter presents a fast reinforcement learning algorithm for anti-ja...
research
03/25/2021

Reinforcement Learning for Deceiving Reactive Jammers in Wireless Networks

Conventional anti-jamming method mostly rely on frequency hopping to hid...
research
06/20/2022

Game-theoretic Learning Anti-jamming Approaches in Wireless Networks

In this article, the anti-jamming communication problem is investigated ...
research
09/12/2018

A Collaborative Multi-agent Reinforcement Learning Anti-jamming Algorithm in Wireless Networks

In this letter, we investigate the anti-jamming defense problem in multi...
research
08/19/2022

Recurrent Neural Network-based Anti-jamming Framework for Defense Against Multiple Jamming Policies

Conventional anti-jamming methods mainly focus on preventing single jamm...
research
12/19/2021

Jamming Pattern Recognition over Multi-Channel Networks: A Deep Learning Approach

With the advent of intelligent jammers, jamming attacks have become a mo...
research
05/13/2020

DeepFake: Deep Dueling-based Deception Strategy to Defeat Reactive Jammers

In this paper, we introduce DeepFake, a novel deep reinforcement learnin...

Please sign up or login with your details

Forgot password? Click here to reset