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UAV-BS Integration with Urban Infrastructure: An Energy Efficiency Perspective

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F24%3APU152707" target="_blank" >RIV/00216305:26220/24:PU152707 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/abstract/document/10742573" target="_blank" >https://ieeexplore.ieee.org/abstract/document/10742573</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/MCOM.001.2400247" target="_blank" >10.1109/MCOM.001.2400247</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    UAV-BS Integration with Urban Infrastructure: An Energy Efficiency Perspective

  • Original language description

    The integration of uncrewed aerial vehicles (UAVs) with fifth-generation (5G) cellular networks has been a prominent research focus in recent years and continues to attract significant interest in the context of sixth-generation (6G) wireless networks. UAVs can serve as aerial wireless platforms to provide on-demand coverage, mobile edge computing, and enhanced sensing and communication services. However, UAV-assisted networks present new opportunities and challenges due to the inherent size, weight, and power constraints of UAVs, their controllable mobility, and the line-ofsight (LoS) characteristics of communication channels. This article discusses these opportunities and challenges from the viewpoint of mobile network operators (MNOs), and offers a novel perspective on efficiently utilizing modern city infrastructures for UAV deployment in typical urban scenarios. In these scenarios, UAV-mounted base stations (UAV-BSs) can significantly improve service continuity and network energy efficiency. We compare system performance in terms of user satisfaction and energy efficiency between conventional UAV deployment, which follows demand dynamics, and an alternative approach where UAVs land on urban infrastructure equipped with charging stations. To identify the preferred UAV locations, while considering the limited availability of such stations and environmental dynamics, we employ a data-driven genetic algorithm. This algorithm closely approximates the true optimal locations subject to a moderate computational budget.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    20200 - Electrical engineering, Electronic engineering, Information engineering

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    IEEE COMMUNICATIONS MAGAZINE

  • ISSN

    0163-6804

  • e-ISSN

    1558-1896

  • Volume of the periodical

    62

  • Issue of the periodical within the volume

    11

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    7

  • Pages from-to

    01-07

  • UT code for WoS article

    001351566800001

  • EID of the result in the Scopus database