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Reinforcement learning based energy efficient robot relay for unmanned aerial vehicles against smart jamming

Authors
  • Lu, Xiaozhen1
  • Jie, Jingfang1
  • Lin, Zihan1
  • Xiao, Liang1
  • Li, Jin2
  • Zhang, Yanyong3
  • 1 Xiamen University, Xiamen, 361005, China , Xiamen (China)
  • 2 Guangzhou University, Guangzhou, 510006, China , Guangzhou (China)
  • 3 University of Science and Technology of China, Hefei, 230027, China , Hefei (China)
Type
Published Article
Journal
Science China Information Sciences
Publisher
Science China Press
Publication Date
Dec 27, 2021
Volume
65
Issue
1
Identifiers
DOI: 10.1007/s11432-020-3170-2
Source
Springer Nature
Keywords
Disciplines
  • Research Paper
License
Yellow

Abstract

Unmanned aerial vehicles (UAVs) with limited energy resources, severe path loss, and shadowing to the ground base stations are vulnerable to smart jammers that aim to degrade the UAV communication performance and exhaust the UAV energy. The UAV anti-jamming communication performance, such as the outage probability, degrades if the robot relay is not aware of the jamming policies and the UAV network topology. In this paper, we propose a robot relay scheme for UAVs against smart jamming, which combines reinforcement learning with a function approximation approach named tile coding, to jointly optimize the robot moving distance and relay power with the unknown jamming channel states and locations. The robot mobility and relay policy are chosen based on the received jamming power, the robot received signal quality, location and energy consumption, and the bit error rate of the UAV messages. We also present a deep reinforcement learning version for the robot with sufficient computing resources. It uses three deep neural networks to choose the robot mobility and relay policy with reduced sample complexity, so as to avoid exploring dangerous policies that lead to the high outage probability of the UAV messages. The network architecture of the three networks is designed with fully connected layers instead of convolutional layers to reduce the computational complexity, which is analyzed by theoretical analyses. We provide the performance bound of the proposed schemes in terms of the bit error rate, robot energy consumption and utility based on a game-theoretic study. Simulation results show that the performance of our proposed relay schemes, including the bit error rate, the outage probability, and the robot energy consumption outperforms the existing schemes.

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