Study of Contention Window Adjustment for CSMA/CA by Using Machine Learning

Yen Wen Chen, Kuo Che Kao

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In IEEE 802.11, CSMA/CA protocol applies the exponential backoff scheme to relax the contention problems among different clients wishing to transmit data at the same time. A client shall randomly choose a number of time slots bounded by the contention window. As the size of initial contention window is fixed for each device without considering the congestion status of the network, it may worsen the congestion condition for smaller contention window size, or may waste radio resource for larger window size in traditional scheme. In this paper, we propose the reinforcement learning model rewarded by throughput to dynamically adjust the contention window periodically. The Q-learning model is utilized in the proposed scheme and the reward function is determined by the current throughput measured during a certain interval and which measured in previous interval. The simulation results were compared with the rule based approach used in current 802.11 networks. The results show that the proposed scheme can effectively decrease the collision rate and the system throughput increases significantly accordingly. We also change the number of clients during the simulation time to examine the adjustment capability of the proposed scheme. The results also show that the proposed scheme is still superior to the rule based scheme in such environment.

Original languageEnglish
Title of host publication2021 22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages206-209
Number of pages4
ISBN (Electronic)9784885523328
DOIs
StatePublished - 8 Sep 2021
Event22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021 - Virtual, Online, Taiwan
Duration: 8 Sep 202110 Sep 2021

Publication series

Name2021 22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021

Conference

Conference22nd Asia-Pacific Network Operations and Management Symposium, APNOMS 2021
Country/TerritoryTaiwan
CityVirtual, Online
Period8/09/2110/09/21

Keywords

  • Collision
  • Contention Window
  • CSMA/CA
  • Reinforcement Learning
  • Throughput

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