一种用于灾区三维多无人机部署的系统和速率最大化和干扰最小化的改进亲和传播方法

IF 1.3 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
IET Networks Pub Date : 2025-01-24 DOI:10.1049/ntw2.12143
Nooshin Boroumand Jazi, Farhad Faghani, Mahmoud Daneshvar Farzanegan
{"title":"一种用于灾区三维多无人机部署的系统和速率最大化和干扰最小化的改进亲和传播方法","authors":"Nooshin Boroumand Jazi,&nbsp;Farhad Faghani,&nbsp;Mahmoud Daneshvar Farzanegan","doi":"10.1049/ntw2.12143","DOIUrl":null,"url":null,"abstract":"<p>In emergencies where several ground base stations (GBS) are no longer available, mobile base stations based on unmanned aerial vehicles (UAVs) can efficiently resolve coverage issues in remote areas due to their cost-effectiveness and versatility. Natural disasters, such as a deluge, cause damage to the terrestrial wireless infrastructure. The main challenge in these systems is to determine the optimal 3D placement of UAVs to meet the dynamic demand of users and minimise interference. Various mathematical frameworks and efficient algorithms are suggested for designing, optimising, and deploying UAV-based communication systems. This paper investigates the challenges of 3D UAV placement through machine learning (ML) and enhanced affinity propagation (EAP). Lastly, the simulation results indicate that the proposed approach improves the system sum rate, interference, and coverage performance compared to DBSCAN, k-means, and k-means++ methods. Therefore, this paper identifies UAVs' most effective 3D placement, including minimising the number of UAVs, maximising the number of covered users, and maximising the system sum rate for an arbitrary distribution of users in the disaster area. Additionally, this paper addresses the issue of interference minimisation.</p>","PeriodicalId":46240,"journal":{"name":"IET Networks","volume":"14 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2025-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.12143","citationCount":"0","resultStr":"{\"title\":\"An improved affinity propagation method for maximising system sum rate and minimising interference for 3D multi-UAV placement in disaster area\",\"authors\":\"Nooshin Boroumand Jazi,&nbsp;Farhad Faghani,&nbsp;Mahmoud Daneshvar Farzanegan\",\"doi\":\"10.1049/ntw2.12143\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In emergencies where several ground base stations (GBS) are no longer available, mobile base stations based on unmanned aerial vehicles (UAVs) can efficiently resolve coverage issues in remote areas due to their cost-effectiveness and versatility. Natural disasters, such as a deluge, cause damage to the terrestrial wireless infrastructure. The main challenge in these systems is to determine the optimal 3D placement of UAVs to meet the dynamic demand of users and minimise interference. Various mathematical frameworks and efficient algorithms are suggested for designing, optimising, and deploying UAV-based communication systems. This paper investigates the challenges of 3D UAV placement through machine learning (ML) and enhanced affinity propagation (EAP). Lastly, the simulation results indicate that the proposed approach improves the system sum rate, interference, and coverage performance compared to DBSCAN, k-means, and k-means++ methods. Therefore, this paper identifies UAVs' most effective 3D placement, including minimising the number of UAVs, maximising the number of covered users, and maximising the system sum rate for an arbitrary distribution of users in the disaster area. Additionally, this paper addresses the issue of interference minimisation.</p>\",\"PeriodicalId\":46240,\"journal\":{\"name\":\"IET Networks\",\"volume\":\"14 1\",\"pages\":\"\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2025-01-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1049/ntw2.12143\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/ntw2.12143\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Networks","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/ntw2.12143","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

在多个地面基站(GBS)不再可用的紧急情况下,基于无人机(uav)的移动基站由于其成本效益和多功能性,可以有效地解决偏远地区的覆盖问题。洪水等自然灾害会对地面无线基础设施造成破坏。这些系统的主要挑战是确定无人机的最佳3D位置,以满足用户的动态需求并最大限度地减少干扰。为设计、优化和部署基于无人机的通信系统,提出了各种数学框架和有效算法。本文通过机器学习(ML)和增强亲和力传播(EAP)研究了3D无人机放置的挑战。最后,仿真结果表明,与DBSCAN、k-means和k-means++方法相比,该方法提高了系统的和速率、干扰和覆盖性能。因此,本文确定了无人机最有效的3D布局,包括最小化无人机数量,最大化覆盖用户数量,最大化灾区用户任意分布的系统总和率。此外,本文还讨论了干扰最小化的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

An improved affinity propagation method for maximising system sum rate and minimising interference for 3D multi-UAV placement in disaster area

An improved affinity propagation method for maximising system sum rate and minimising interference for 3D multi-UAV placement in disaster area

In emergencies where several ground base stations (GBS) are no longer available, mobile base stations based on unmanned aerial vehicles (UAVs) can efficiently resolve coverage issues in remote areas due to their cost-effectiveness and versatility. Natural disasters, such as a deluge, cause damage to the terrestrial wireless infrastructure. The main challenge in these systems is to determine the optimal 3D placement of UAVs to meet the dynamic demand of users and minimise interference. Various mathematical frameworks and efficient algorithms are suggested for designing, optimising, and deploying UAV-based communication systems. This paper investigates the challenges of 3D UAV placement through machine learning (ML) and enhanced affinity propagation (EAP). Lastly, the simulation results indicate that the proposed approach improves the system sum rate, interference, and coverage performance compared to DBSCAN, k-means, and k-means++ methods. Therefore, this paper identifies UAVs' most effective 3D placement, including minimising the number of UAVs, maximising the number of covered users, and maximising the system sum rate for an arbitrary distribution of users in the disaster area. Additionally, this paper addresses the issue of interference minimisation.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
IET Networks
IET Networks COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
5.00
自引率
0.00%
发文量
41
审稿时长
33 weeks
期刊介绍: IET Networks covers the fundamental developments and advancing methodologies to achieve higher performance, optimized and dependable future networks. IET Networks is particularly interested in new ideas and superior solutions to the known and arising technological development bottlenecks at all levels of networking such as topologies, protocols, routing, relaying and resource-allocation for more efficient and more reliable provision of network services. Topics include, but are not limited to: Network Architecture, Design and Planning, Network Protocol, Software, Analysis, Simulation and Experiment, Network Technologies, Applications and Services, Network Security, Operation and Management.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信