Attention-based reinforcement learning for real-time UAV semantic communication

Won Joon Yun, Byungju Lim, Soyi Jung, Young Chai Ko, Jihong Park, Joongheon Kim, Mehdi Bennis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Citations (Scopus)

Abstract

In this article, we study the problem of air-to-ground ultra-reliable and low-latency communication (URLLC) for a moving ground user. This is done by controlling multiple unmanned aerial vehicles (UAVs) in real time while avoiding inter-UAV collisions. To this end, we propose a novel multiagent deep reinforcement learning (MADRL) framework, coined a graph attention exchange network (GAXNet). In GAXNet, each UAV constructs an attention graph locally measuring the level of attention to its neighboring UAVs, while exchanging the attention weights with other UAVs so as to reduce the attention mismatch between them. Simulation results corroborates that GAXNet achieves up to 4.5x higher rewards during training. At execution, without incurring inter-UAV collisions, G2ANet improves reliability of air-to-ground network in terms of latency and error rate.

Original languageEnglish
Title of host publication2021 17th International Symposium on Wireless Communication Systems, ISWCS 2021
PublisherVDE Verlag GmbH
ISBN (Electronic)9781728174327
DOIs
Publication statusPublished - 2021 Sept 6
Event17th International Symposium on Wireless Communication Systems, ISWCS 2021 - Berlin, Germany
Duration: 2021 Sept 62021 Sept 9

Publication series

NameProceedings of the International Symposium on Wireless Communication Systems
Volume2021-September
ISSN (Print)2154-0217
ISSN (Electronic)2154-0225

Conference

Conference17th International Symposium on Wireless Communication Systems, ISWCS 2021
Country/TerritoryGermany
CityBerlin
Period21/9/621/9/9

Bibliographical note

Funding Information:
This research was supported by Institute for Information & Communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No.2018-0-00170, Virtual Presence in Moving Objects through 5G) and the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1A4A1030775).

Publisher Copyright:
© 2021 IEEE

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering
  • Communication

Fingerprint

Dive into the research topics of 'Attention-based reinforcement learning for real-time UAV semantic communication'. Together they form a unique fingerprint.

Cite this