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Energy Efficient Resource Allocation in UAV-based Heterogeneous Networks

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

18 Citations (Scopus)

Abstract

Recently, the deployment of unmanned aerial vehicles (UAVs) in the wireless networks has gained attention to achieve a better quality of service (QoS) for the mobile nodes. This paper studies the use of UAV network to assist the terrestrial network to meet the QoS requirements of the mobile nodes. However, such cellular traffic offloading to the energy constrained UAVs is not trivial. Therefore, we propose a weighted power allocation scheme in the UAV assisted heterogeneous networks (UAV-HetNets) where both UAV and terrestrial networks are efficiently utilized to meet the QoS requirements of the mobile nodes. For that purpose, the weighted energy minimization problem is formulated under the QoS constraints of the mobile node. Simulation results are drawn to show the significance of the proposed energy efficient resource allocation scheme.

Original languageEnglish
Title of host publication2019 20th Asia-Pacific Network Operations and Management Symposium
Subtitle of host publicationManagement in a Cyber-Physical World, APNOMS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9784885523205
DOIs
Publication statusPublished - Sept 2019
Event20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019 - Matsue, Japan
Duration: 18 Sept 201920 Sept 2019

Publication series

Name2019 20th Asia-Pacific Network Operations and Management Symposium: Management in a Cyber-Physical World, APNOMS 2019

Conference

Conference20th Asia-Pacific Network Operations and Management Symposium, APNOMS 2019
Country/TerritoryJapan
CityMatsue
Period18/09/1920/09/19

Bibliographical note

Publisher Copyright:
© 2019 IEICE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Energy Efficiency
  • Resource Allocation
  • Unmanned Aerial Vehicles

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