Providing an energy efficient UAV BS positioning mechanism to improve wireless connectivity
As wireless communication continues to advance, the move towards Sixth-Generation (6G) networks has heightened the need for faster data speeds and reliable connections, prompting new approaches to connectivity. In scenarios such as natural disasters, where Ground Base Stations (GBSs) may be compromi...
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| Vydáno v: | Ad hoc networks Ročník 170; s. 103767 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier B.V
01.04.2025
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| ISSN: | 1570-8705, 1570-8713 |
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| Abstract | As wireless communication continues to advance, the move towards Sixth-Generation (6G) networks has heightened the need for faster data speeds and reliable connections, prompting new approaches to connectivity. In scenarios such as natural disasters, where Ground Base Stations (GBSs) may be compromised, the use of Unmanned Aerial Vehicles (UAVs) has become increasingly important. A promising approach is to deploy low-altitude UAVs equipped with compact Base Stations (BSs) to reestablish essential communication networks and offer temporary coverage. However, identifying the optimal locations for these UAV-BSs presents a complex challenge. This paper proposes an innovative solution using UAVs as base stations (UAV-BSs) and introduces a Mixed-Integer Non-Linear Programming (MINLP) optimization model to position UAV-BSs based on real-time demand and network conditions. Traditional methods struggle with the complexity of UAV-BS deployment, so a novel algorithm combining the JAYA optimization technique is used. Extensive experiments show this approach maximizes network coverage and connectivity while minimizing UAV-BS power consumption, outperforming other methods in placement accuracy, power usage, packet loss, and latency. The algorithm also adapts to varying network conditions, making it a valuable tool for optimizing UAV-BS locations in dynamic environments. |
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| AbstractList | As wireless communication continues to advance, the move towards Sixth-Generation (6G) networks has heightened the need for faster data speeds and reliable connections, prompting new approaches to connectivity. In scenarios such as natural disasters, where Ground Base Stations (GBSs) may be compromised, the use of Unmanned Aerial Vehicles (UAVs) has become increasingly important. A promising approach is to deploy low-altitude UAVs equipped with compact Base Stations (BSs) to reestablish essential communication networks and offer temporary coverage. However, identifying the optimal locations for these UAV-BSs presents a complex challenge. This paper proposes an innovative solution using UAVs as base stations (UAV-BSs) and introduces a Mixed-Integer Non-Linear Programming (MINLP) optimization model to position UAV-BSs based on real-time demand and network conditions. Traditional methods struggle with the complexity of UAV-BS deployment, so a novel algorithm combining the JAYA optimization technique is used. Extensive experiments show this approach maximizes network coverage and connectivity while minimizing UAV-BS power consumption, outperforming other methods in placement accuracy, power usage, packet loss, and latency. The algorithm also adapts to varying network conditions, making it a valuable tool for optimizing UAV-BS locations in dynamic environments. © 2025 The Authors As wireless communication continues to advance, the move towards Sixth-Generation (6G) networks has heightened the need for faster data speeds and reliable connections, prompting new approaches to connectivity. In scenarios such as natural disasters, where Ground Base Stations (GBSs) may be compromised, the use of Unmanned Aerial Vehicles (UAVs) has become increasingly important. A promising approach is to deploy low-altitude UAVs equipped with compact Base Stations (BSs) to reestablish essential communication networks and offer temporary coverage. However, identifying the optimal locations for these UAV-BSs presents a complex challenge. This paper proposes an innovative solution using UAVs as base stations (UAV-BSs) and introduces a Mixed-Integer Non-Linear Programming (MINLP) optimization model to position UAV-BSs based on real-time demand and network conditions. Traditional methods struggle with the complexity of UAV-BS deployment, so a novel algorithm combining the JAYA optimization technique is used. Extensive experiments show this approach maximizes network coverage and connectivity while minimizing UAV-BS power consumption, outperforming other methods in placement accuracy, power usage, packet loss, and latency. The algorithm also adapts to varying network conditions, making it a valuable tool for optimizing UAV-BS locations in dynamic environments. |
| ArticleNumber | 103767 |
| Author | Valle de Lima, Daniel Javidi da Costa, João Paulo Najafzadeh, Alireza Pignaton de Freitas, Edison Almeida Santos, Giovanni Pasandideh, Faezeh |
| Author_xml | – sequence: 1 givenname: Faezeh orcidid: 0000-0002-2797-3828 surname: Pasandideh fullname: Pasandideh, Faezeh email: faezeh.pasandideh@inf.ufrgs.br organization: Department of Computer Science, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil – sequence: 2 givenname: Alireza surname: Najafzadeh fullname: Najafzadeh, Alireza email: alireza_najafzadeh@vu.iust.ac.ir organization: School of Computer Engineering, Iran University of Science and Technology (IUST), Iran – sequence: 3 givenname: João Paulo surname: Javidi da Costa fullname: Javidi da Costa, João Paulo email: joaopaulo.dacosta@hshl.de organization: Department 2 Lippstadt, Hamm-Lippstadt University of Applied Sciences, Lippstadt, Germany – sequence: 4 givenname: Giovanni orcidid: 0000-0002-0189-7361 surname: Almeida Santos fullname: Almeida Santos, Giovanni email: giovanni.almeidasantos@hshl.de organization: Department 2 Lippstadt, Hamm-Lippstadt University of Applied Sciences, Lippstadt, Germany – sequence: 5 givenname: Daniel surname: Valle de Lima fullname: Valle de Lima, Daniel email: daniel.vallelima@gmail.com organization: Postgraduate Program in Telecommunications Engineering (PPGET), IFCE, Fortaleza, Brazil – sequence: 6 givenname: Edison orcidid: 0000-0003-4655-8889 surname: Pignaton de Freitas fullname: Pignaton de Freitas, Edison email: edison.pignaton@inf.ufrgs.br, edison.pignaton@hh.se organization: Department of Computer Science, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil |
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| Keywords | JAYA optimization algorithm UAV base station Deployment problem Non-linear optimization |
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