OFDMA Based UAVs Communication for Ensuring QoS

Muhammet Ali Karabulut, A. F.M. Shahen Shah, Md Baharul Islam, Muhammad Ehsan Rana

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

2 Citations (Scopus)

Abstract

Unmanned aerial vehicles (UAV), more often familiar as drone, has been widely used both in civilian activities and military missions. UAV ad-hoc networks, also known as flying ad-hoc networks, are ad-hoc multi-UAV systems (FANETs). The FANET’s medium access control (MAC) and physical (PHY) layer specifications are defined by the IEEE 802.11 standard, which uses the enhanced distributed channel access function (EDCAF) to assure the quality of service (QoS) in the MAC layer. Because it suffers from collisions, carrier sensing multiple access with collision avoidance (CSMA/CA) is useless when a high data rate is required. As a result, the use of orthogonal frequency division multiple access (OFDMA) is advised. By lowering the collision probability, OFDMA increases performance and reduces latency. This study develops an analytical model for assessing IEEE 802.11 EDCAF performance for OFDMA-based UAV communication. A new channel contention method that combines EDCAF and OFDMA is suggested. Firstly, EDCA based prioritized channel contention is done. Then, channel access and transmission are done using OFDMA. We undertake a theoretical study based on the Markov chain model, which gives throughput, packet drop rate (PDR), and delay expressions. The simulation results verify the model performance and show that the proposed technique ensures strict delay requirements and supports QoS.

Original languageEnglish
Title of host publicationApplications of Artificial Intelligence and Machine Learning - Select Proceedings of ICAAAIML 2021
EditorsBhuvan Unhelker, Hari Mohan Pandey, Gaurav Raj
PublisherSpringer Science and Business Media Deutschland GmbH
Pages331-342
Number of pages12
ISBN (Print)9789811948305
DOIs
Publication statusPublished - 2022
Externally publishedYes
EventInternational Conference on Advances and Applications of Artificial Intelligence and Machine Learning, ICAAAIML 2021 - Virtual, Online
Duration: 31 Jul 202131 Jul 2021

Publication series

NameLecture Notes in Electrical Engineering
Volume925
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference on Advances and Applications of Artificial Intelligence and Machine Learning, ICAAAIML 2021
CityVirtual, Online
Period31/07/2131/07/21

Keywords

  • Enhanced Distributed Channel Access Function (EDCAF)
  • Flying Ad-hoc Networks (FANETs)
  • IEEE 802.11
  • Orthogonal Frequency Division Multiple Access (OFDMA)

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