Optimal Decision on Placement of an Auxiliary Aerial Wireless Base Station Using the Artificial Bee Colony Algorithm

Tahat, Ashraf; Edwan, Talal A.; Mbaideen, Dana; Murrar, Nada; Al-Qutob, Ola; Ayman, Leen

doi:10.1109/commnet.2019.8742386

Cited by 3 publications

(9 citation statements)

References 11 publications

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“…Tahat et al 55 Optimal solution using ABC algorithm for 3D placement of UAV Savkin and Huang 58 By minimizing average distance between user and UAV, based on local information Lai et al 62 UAV deployment by maintaining guaranteed data rate Qin et al 64 Placement of base station by checking the optimal altitude and coverage of users Sun and Masouros 65 Placement algorithm based on K-means clustering. Li et al 67 Computes optimal altitude and maximize throughput ABC: artificial bee colony; UAV: unmanned aerial vehicle.…”

Section: Reference Main Contributionmentioning

confidence: 99%

“…Tahat et al 55 UAV deployment Optimal solution using ABC algorithm for 3D placement of UAV Savkin and Huang 58 UAV deployment By minimizing average distance between user and UAV, based on local information Sharafeddine and Islambouli 59 Traffic off-loading, network recovery Greedy algorithm-based method to deploy base stations Chandrasekharan et al 60…”

Section: Reference Objective Descriptionmentioning

confidence: 99%

“…94 The ABC algorithm applied in BS deployment is studied in Tahat et al, 55 Li et al, 67 Karaboga and Basturk, 94 and Zhang et al 95 By enhancing the coverage and maximizing the users served, the UAV deployment can be optimized via the ABC algorithm. The work of Tahat et al 55 discusses the UAV-BS 3D deployment problem. The ABC algorithm outputs a global optimum.…”

Section: Abc Algorithmmentioning

confidence: 99%

“…Deployment of UAVs is a function of three coordinates resulting it as a 3D problem. Tahat et al, 55 Savkin and Huang, 58 Sharafeddine and Islambouli, 59 Chandrasekharan et al, 60 Kang et al, 61 Lai et al, 62 Romero and Leus, 63 Qin et al, 64 Sun and Masouros, 65 Zhai et al, 66 and Li et al 67 have looked deeply into strategizing the deployment of AirBSs for the cellular network. An optimal placement algorithm based on ABC algorithm is discussed in Tahat et al 55 and considered it as a non-convex problem.…”

Section: Fifth Generation Cellular Networkmentioning

confidence: 99%

“…53,54 UAV-based services in 5G are discussed in section “Fifth generation cellular networks.” Countless applications of aerial drones in wireless communications are explicitly studied by researchers. Tahat et al, 55 Mozaffari et al, 56 Wu et al, 57 Savkin and Huang, 58 and Sharafeddine and Islambouli 59 developed algorithms for the optimal placement of UAVs. When multiple UAVs are deployed, there must be cooperation among the drones for faster operation.…”

Section: Introductionmentioning

confidence: 99%

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Unmanned aerial vehicles: Applications, techniques, and challenges as aerial base stations

Rolly

Malarvezhi

Λάγκας

2022

International Journal of Distributed Sensor Networks

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Next generation wireless networks are expected to be greatly supported by unmanned aerial vehicles, which can act as aerial base stations and constitute a promising solution for the exorbitant rise in user demands. This is possible because of unmanned aerial vehicle characteristics such as mobility, flexibility, increased line-of-sight probability, and their ability to access unreachable locations. Extensive research is now widely performed on the deployment, performance analysis, resource management, trajectory optimization, and channel modeling in such networks. This survey article focuses on the different applications and the related algorithms for realizing aerial base stations by thoroughly reviewing each related research area. In a nutshell, this article provides key applications, challenges, and the technology used for the design and analysis of unmanned aerial vehicles as base stations.

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Section: Reference Main Contributionmentioning

confidence: 99%

Section: Reference Objective Descriptionmentioning

confidence: 99%

Section: Abc Algorithmmentioning

confidence: 99%

Section: Fifth Generation Cellular Networkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Unmanned aerial vehicles: Applications, techniques, and challenges as aerial base stations

Rolly

Malarvezhi

Λάγκας

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International Journal of Distributed Sensor Networks

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UAV Placement and Resource Management in Public Safety Networks: An Overview

Shahzadi

Ali

Naeem

2022

Intelligent Unmanned Air Vehicles Communications for Public Safety Networks

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3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

Carvajal-Rodríguez,

Guamán,

Tipantuña

et al. 2024

IEEE Open J. Veh. Technol.

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Unmanned aerial vehicles (UAVs) have seen remarkable improvements in their flight capabilities and computational power. Their applications span various domains, such as agriculture, military, and communications. To improve communication quality and coverage in UAV-enabled systems, understanding effective placement techniques is crucial. While research has explored optimal UAV placement in two dimensions, there is a need for a comprehensive three-dimensional (3D) analysis, particularly for resource optimization. This article presents a systematic mapping study on 3D placement in UAV-enabled communication systems, incorporating a threat analysis for the reliability of the results. It provides valuable insights for future research on 3D placement optimization techniques, specifically examining optimization objectives, model system features, problem types, and solution strategies. Our research reveals, on one hand, an emphasis on optimizing data rate throughput, power transmission, and ground coverage, and a predominant use of large-scale fading in the air-to-ground channel model; on the other hand, heuristic algorithms prevail as the solution strategy. Moreover, we identify gaps in achieving critical objectives such as the probability of outage, deployment costs, quality of experience, and spectrum optimization. This highlights the need for further exploration in the formulation aspects of the system, which includes small-scale fading, access techniques, and interference management.

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Optimal Decision on Placement of an Auxiliary Aerial Wireless Base Station Using the Artificial Bee Colony Algorithm

Cited by 3 publications

References 11 publications

Unmanned aerial vehicles: Applications, techniques, and challenges as aerial base stations

Unmanned aerial vehicles: Applications, techniques, and challenges as aerial base stations

UAV Placement and Resource Management in Public Safety Networks: An Overview

3D Placement Optimization in UAV-Enabled Communications: A Systematic Mapping Study

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