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المؤلفChkirbene, Zina
المؤلفGouissem, Ala
المؤلفHamila, Ridha
المؤلفUnal, Devrim
تاريخ الإتاحة2024-08-21T09:49:57Z
تاريخ النشر2024
اسم المنشور2024 IEEE 8th Energy Conference, ENERGYCON 2024 - Proceedings
المصدرScopus
معرّف المصادر الموحدhttp://dx.doi.org/10.1109/ENERGYCON58629.2024.10488785
معرّف المصادر الموحدhttp://hdl.handle.net/10576/57843
الملخصThe advent of Intelligent Reflecting Surfaces (IRS) and Unmanned Aerial Vehicles (UAVs) is setting a new benchmark in the field of wireless communications. IRS, with their groundbreaking ability to manipulate electromagnetic waves, have opened avenues for substantial enhancements in signal quality, network efficiency, and spectral usage. These surfaces dynamically reconfigure the propagation environment, leading to optimized signal paths and reduced interference. Concurrently, UAVs have emerged as dynamic, versatile elements within communication networks, offering high mobility and the ability to access and enhance coverage in areas where traditional, fixed infrastructure falls short. This paper presents a comprehensive survey on the synergistic integration of IRS and UAVs in wireless networks, highlighting how this innovative combination substantially boosts network performance, particularly in terms of security, energy efficiency, and reliability. The versatility of UAVs, combined with the signal-manipulating prowess of IRS, creates a potent solution for overcoming the limitations of conventional communication setups, especially in challenging and underserved environments. Furthermore, the survey delves into the cutting-edge realm of Machine Learning (ML), exploring its role in the strategic deployment and operational optimization of UAVs equipped with IRS. The paper also underscores the latest research and practical advancements in this field, providing insights into real-world applications and experimental setups. It concludes by discussing the future prospects and potential directions for this emerging technology, positioning the IRS-UAV integration as a transformative force in the landscape of next-generation wireless communications.
راعي المشروعThis work was supported by Qatar University Internal Grant IRCC-2023-237. The statements made herein are solely the responsibility of the author[s].
اللغةen
الناشرIEEE
الموضوعenergy
Index- UAV
IRS
machine learning
security
wireless communication systems
العنوانThe Future of Aerial Communications: A Survey of IRS-Enhanced UAV Communication Technologies
النوعConference
الصفحات1-6
dc.accessType Full Text


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