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AirWave: Enhancing UAV Connectivity in Cellular Networks through an Integrated Simulation Framework

  • Emirhan Zor*
  • , Yusuf Taskiran
  • , Fares A. Dael
  • , Ibraheem Shayea
  • , Leila Rzayeva
  • , Zuleikha Syzdykova
  • *Corresponding author for this work
  • Istanbul Technical University
  • Izmir Bakircay University
  • Astana IT University

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

3 Citations (Scopus)

Abstract

This study presents AirWave, an innovative modeling framework tailored to address the challenges associated with integrating Unmanned Aerial Vehicles (UAVs) into 5G and future cellular networks. With the rising prominence of UAVs across various industries, ensuring uninterrupted connectivity and efficient mobility management within cellular networks becomes paramount. AirWave offers a comprehensive simulation environment, amalgamating network and physics simulations using ns-3 for network simulation, Gazebo for physics simulation, and integrating PX4 autopilot for realistic UAV flight dynamics. This framework facilitates in-depth investigations into UAV mobility and handover management, including a trajectory optimization technique based on reinforcement learning for cellular-connected drones. Extensive simulations demonstrate the versatility and effectiveness of AirWave, showcasing notable improvements in UAV range, connectivity, and management within cellular networks. These findings hold significant promise for advancing research and practical applications in UAV communications.

Original languageEnglish
Title of host publication2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages295-302
Number of pages8
ISBN (Electronic)9798350374100
DOIs
Publication statusPublished - 2024
Event2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024 - Bhopal, India
Duration: 24 Feb 202425 Feb 2024

Publication series

Name2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024

Conference

Conference2024 IEEE International Conference on Big Data and Machine Learning, ICBDML 2024
Country/TerritoryIndia
CityBhopal
Period24/02/2425/02/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

UN SDGs

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

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

Keywords

  • 5G and beyond
  • Handover management
  • Reinforcement learning
  • UAV communications
  • machine learning

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