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Smart Multi‐Objective Unmanned Aerial Vehicles as Base Stations Placement in 6G Cellular Telecommunication Networks Using NSGA‐II Optimisation Algorithm.

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Title: Smart Multi‐Objective Unmanned Aerial Vehicles as Base Stations Placement in 6G Cellular Telecommunication Networks Using NSGA‐II Optimisation Algorithm.
Authors: Fahem, Ahmed Qabel, Jihad, Huda Ajel, Niya, Javad Musevi, Asadpour, Mohammad
Source: IET Networks (Wiley-Blackwell); Jan2025, Vol. 14 Issue 1, p1-16, 16p
Subject Terms: 6G networks, MULTI-objective optimization, OPTIMIZATION algorithms, DRONE aircraft, RADIO antennas, NETWORK performance, CELL phone systems
Abstract: The deployment of unmanned aerial vehicles (UAVs) as aerial base stations in cellular networks presents a dynamic solution to meet the demands of high and fluctuating traffic patterns. Efficient placement of UAVs is crucial to harness their benefits and adapt intelligently to environmental changes. This paper introduces a multi‐objective optimisation model aimed at maximising user coverage and minimising overlap among drone‐based base stations in 6G networks. To address this optimisation issue, the Nondominated Sorting Genetic Algorithm II (NSGA‐II) is deployed, enabling the identification of Pareto optimal solutions that strike a balance between conflicting objectives. Through simulations conducted under various scenarios, the proposed model demonstrated significant improvements in user coverage and reduction of overlap among base stations compared to existing techniques. The findings reveal the effectiveness of the proposed model in balancing the objectives of coverage and overlap, resulting in an enhanced 6G network design. The method achieves an average coverage probability of 98.39% and an average overlap improvement percentage (OIP) of 92.39%, validated through 50 experimental runs. These results underscore the robustness and superiority of the proposed NSGA‐II‐based strategy in optimising DBS placement, contributing to the advancement of 6G cellular networks. [ABSTRACT FROM AUTHOR]
Copyright of IET Networks (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Smart Multi‐Objective Unmanned Aerial Vehicles as Base Stations Placement in 6G Cellular Telecommunication Networks Using NSGA‐II Optimisation Algorithm.
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  Data: <searchLink fieldCode="AR" term="%22Fahem%2C+Ahmed+Qabel%22">Fahem, Ahmed Qabel</searchLink><br /><searchLink fieldCode="AR" term="%22Jihad%2C+Huda+Ajel%22">Jihad, Huda Ajel</searchLink><br /><searchLink fieldCode="AR" term="%22Niya%2C+Javad+Musevi%22">Niya, Javad Musevi</searchLink><br /><searchLink fieldCode="AR" term="%22Asadpour%2C+Mohammad%22">Asadpour, Mohammad</searchLink>
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  Data: IET Networks (Wiley-Blackwell); Jan2025, Vol. 14 Issue 1, p1-16, 16p
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  Data: <searchLink fieldCode="DE" term="%226G+networks%22">6G networks</searchLink><br /><searchLink fieldCode="DE" term="%22MULTI-objective+optimization%22">MULTI-objective optimization</searchLink><br /><searchLink fieldCode="DE" term="%22OPTIMIZATION+algorithms%22">OPTIMIZATION algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22DRONE+aircraft%22">DRONE aircraft</searchLink><br /><searchLink fieldCode="DE" term="%22RADIO+antennas%22">RADIO antennas</searchLink><br /><searchLink fieldCode="DE" term="%22NETWORK+performance%22">NETWORK performance</searchLink><br /><searchLink fieldCode="DE" term="%22CELL+phone+systems%22">CELL phone systems</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The deployment of unmanned aerial vehicles (UAVs) as aerial base stations in cellular networks presents a dynamic solution to meet the demands of high and fluctuating traffic patterns. Efficient placement of UAVs is crucial to harness their benefits and adapt intelligently to environmental changes. This paper introduces a multi‐objective optimisation model aimed at maximising user coverage and minimising overlap among drone‐based base stations in 6G networks. To address this optimisation issue, the Nondominated Sorting Genetic Algorithm II (NSGA‐II) is deployed, enabling the identification of Pareto optimal solutions that strike a balance between conflicting objectives. Through simulations conducted under various scenarios, the proposed model demonstrated significant improvements in user coverage and reduction of overlap among base stations compared to existing techniques. The findings reveal the effectiveness of the proposed model in balancing the objectives of coverage and overlap, resulting in an enhanced 6G network design. The method achieves an average coverage probability of 98.39% and an average overlap improvement percentage (OIP) of 92.39%, validated through 50 experimental runs. These results underscore the robustness and superiority of the proposed NSGA‐II‐based strategy in optimising DBS placement, contributing to the advancement of 6G cellular networks. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of IET Networks (Wiley-Blackwell) is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1049/ntw2.70017
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 16
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      – SubjectFull: 6G networks
        Type: general
      – SubjectFull: MULTI-objective optimization
        Type: general
      – SubjectFull: OPTIMIZATION algorithms
        Type: general
      – SubjectFull: DRONE aircraft
        Type: general
      – SubjectFull: RADIO antennas
        Type: general
      – SubjectFull: NETWORK performance
        Type: general
      – SubjectFull: CELL phone systems
        Type: general
    Titles:
      – TitleFull: Smart Multi‐Objective Unmanned Aerial Vehicles as Base Stations Placement in 6G Cellular Telecommunication Networks Using NSGA‐II Optimisation Algorithm.
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            NameFull: Fahem, Ahmed Qabel
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            NameFull: Jihad, Huda Ajel
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            – D: 01
              M: 01
              Text: Jan2025
              Type: published
              Y: 2025
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