Scholarlink

<p>Recently, UAV-mounted mobile base stations (UAVs-MBS) have gained significant attention as an effective solution for providing essential wireless communication services and connectivity to ground users (GUs) in various environments. Smart antenna technologies are vital for both current and next-generation communication networks, particularly in 5&#xa0;G and beyond. However, implementing smart antenna-assisted UAVs-MBS networks presents a complex multi-objective optimization problem, and traditional techniques often fall short in efficiency and inclusivity. In this study, we propose a viable hybrid method to tackle the challenge of minimizing the number of smart antenna-enabled UAVs-MBS required to achieve higher Line-of-Sight probabilities and coverage levels, while also determining the optimal 3D coordinates for a group of dispersed GUs. Our approach utilizes a low-complexity multi-objective algorithm called SERAPH, which incorporates a novel two-stage hybrid evolutionary algorithm alongside a multi-criteria decision-making method. Additionally, SERAPH features 3D multi-beamforming and coordination mechanisms to enhance wireless coverage and effectively extend the system’s lifespan. We validate the effectiveness of SERAPH through comprehensive comparative analyses with various state-of-the-art algorithms. Our results demonstrate that the proposed method significantly outperforms existing approaches in terms of accuracy and efficiency.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Seraph: a stochastic operational approach for the deployment of multi-antenna UAV-assisted networks

  • 期刊论文

  • 发表日期：

    2025年6月16日

查看全文
  • Mohamadi Houssem Eddine,
  • Lahlou Laaziz,
  • Gherbi Abdelouahed,
  • Kara Nadjia

摘要

Recently, UAV-mounted mobile base stations (UAVs-MBS) have gained significant attention as an effective solution for providing essential wireless communication services and connectivity to ground users (GUs) in various environments. Smart antenna technologies are vital for both current and next-generation communication networks, particularly in 5 G and beyond. However, implementing smart antenna-assisted UAVs-MBS networks presents a complex multi-objective optimization problem, and traditional techniques often fall short in efficiency and inclusivity. In this study, we propose a viable hybrid method to tackle the challenge of minimizing the number of smart antenna-enabled UAVs-MBS required to achieve higher Line-of-Sight probabilities and coverage levels, while also determining the optimal 3D coordinates for a group of dispersed GUs. Our approach utilizes a low-complexity multi-objective algorithm called SERAPH, which incorporates a novel two-stage hybrid evolutionary algorithm alongside a multi-criteria decision-making method. Additionally, SERAPH features 3D multi-beamforming and coordination mechanisms to enhance wireless coverage and effectively extend the system’s lifespan. We validate the effectiveness of SERAPH through comprehensive comparative analyses with various state-of-the-art algorithms. Our results demonstrate that the proposed method significantly outperforms existing approaches in terms of accuracy and efficiency.