Deep Reinforcement Learning Approach for Fairness-aware Scheduling in Wireless Networks

Minseok Kim, Sangwon Hwang, Inkyu Lee

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

1 Citation (Scopus)

Abstract

This paper studies a scheduling problem in wireless network systems which have combinatorial and time-varying properties. Although studies on efficient scheduling algorithms have been widely investigated, a huge trade-off between the performance and complexity still exists. Furthermore, it is becoming necessary to consider quality of service (QoS) and fairness constraints as growing demands on wireless networks. To this end, this paper propose a deep reinforcement learning (DRL) approach which can maximize system throughput while considering QoS and fairness by designing DRL structure according to the objective function and constraints. Numerical results demonstrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationICTC 2022 - 13th International Conference on Information and Communication Technology Convergence
Subtitle of host publicationAccelerating Digital Transformation with ICT Innovation
PublisherIEEE Computer Society
Pages1229-1232
Number of pages4
ISBN (Electronic)9781665499392
DOIs
Publication statusPublished - 2022
Event13th International Conference on Information and Communication Technology Convergence, ICTC 2022 - Jeju Island, Korea, Republic of
Duration: 2022 Oct 192022 Oct 21

Publication series

NameInternational Conference on ICT Convergence
Volume2022-October
ISSN (Print)2162-1233
ISSN (Electronic)2162-1241

Conference

Conference13th International Conference on Information and Communication Technology Convergence, ICTC 2022
Country/TerritoryKorea, Republic of
CityJeju Island
Period22/10/1922/10/21

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government (MSIT) (No. 2022R1A5A1027646).

Publisher Copyright:
© 2022 IEEE.

Keywords

  • Deep reinforcement learning
  • fairness-aware
  • scheduling algorithm

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications

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