{"title":"利用地形特征优化航空基站布局","authors":"Yeonwoo Cho;Jonghyeon Won;Do-Yup Kim;Jang-Won Lee","doi":"10.1109/JIOT.2025.3545125","DOIUrl":null,"url":null,"abstract":"In aerial base station (ABS) placement studies, leveraging information on topographic features for air-to-ground (A2G) channel analysis has been considered a promising approach. Recently, this approach has been studied in several works. However, these studies have predominantly focused on simplistic 3-D cuboid representations of topographic features, which do not adequately capture the complexity of real-world environments, thereby impeding accurate A2G channel analysis. In this article, we propose a more advanced strategy by generalizing the shapes and arrangements of topographic features to enable their realistic and accurate representations. Utilizing these generalized topographic models, we study the problem of finding the ABS location for coverage maximization. To solve this problem, we identify so-called line-of-sight (LoS) and non-LoS (NLoS) zones formed by these generalized topographic features through geometric analysis and obtain straightforward derivations of the coverage area for any given ABS location. Building upon this foundation, we develop a new ABS placement strategy, termed the polygonal feature-aware ABS placement algorithm (FA-poly). Our simulation results demonstrate that the proposed FA-poly significantly outperforms existing baseline methods in terms of the coverage area, as it accurately identifies channel conditions by leveraging information on generalized topographic features and obtains the coverage area based on them.","PeriodicalId":54347,"journal":{"name":"IEEE Internet of Things Journal","volume":"12 12","pages":"19882-19900"},"PeriodicalIF":8.9000,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal Placement of Aerial Base Station Utilizing Topographic Features\",\"authors\":\"Yeonwoo Cho;Jonghyeon Won;Do-Yup Kim;Jang-Won Lee\",\"doi\":\"10.1109/JIOT.2025.3545125\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In aerial base station (ABS) placement studies, leveraging information on topographic features for air-to-ground (A2G) channel analysis has been considered a promising approach. Recently, this approach has been studied in several works. However, these studies have predominantly focused on simplistic 3-D cuboid representations of topographic features, which do not adequately capture the complexity of real-world environments, thereby impeding accurate A2G channel analysis. In this article, we propose a more advanced strategy by generalizing the shapes and arrangements of topographic features to enable their realistic and accurate representations. Utilizing these generalized topographic models, we study the problem of finding the ABS location for coverage maximization. To solve this problem, we identify so-called line-of-sight (LoS) and non-LoS (NLoS) zones formed by these generalized topographic features through geometric analysis and obtain straightforward derivations of the coverage area for any given ABS location. Building upon this foundation, we develop a new ABS placement strategy, termed the polygonal feature-aware ABS placement algorithm (FA-poly). Our simulation results demonstrate that the proposed FA-poly significantly outperforms existing baseline methods in terms of the coverage area, as it accurately identifies channel conditions by leveraging information on generalized topographic features and obtains the coverage area based on them.\",\"PeriodicalId\":54347,\"journal\":{\"name\":\"IEEE Internet of Things Journal\",\"volume\":\"12 12\",\"pages\":\"19882-19900\"},\"PeriodicalIF\":8.9000,\"publicationDate\":\"2025-02-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Internet of Things Journal\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10902115/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Internet of Things Journal","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10902115/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Optimal Placement of Aerial Base Station Utilizing Topographic Features
In aerial base station (ABS) placement studies, leveraging information on topographic features for air-to-ground (A2G) channel analysis has been considered a promising approach. Recently, this approach has been studied in several works. However, these studies have predominantly focused on simplistic 3-D cuboid representations of topographic features, which do not adequately capture the complexity of real-world environments, thereby impeding accurate A2G channel analysis. In this article, we propose a more advanced strategy by generalizing the shapes and arrangements of topographic features to enable their realistic and accurate representations. Utilizing these generalized topographic models, we study the problem of finding the ABS location for coverage maximization. To solve this problem, we identify so-called line-of-sight (LoS) and non-LoS (NLoS) zones formed by these generalized topographic features through geometric analysis and obtain straightforward derivations of the coverage area for any given ABS location. Building upon this foundation, we develop a new ABS placement strategy, termed the polygonal feature-aware ABS placement algorithm (FA-poly). Our simulation results demonstrate that the proposed FA-poly significantly outperforms existing baseline methods in terms of the coverage area, as it accurately identifies channel conditions by leveraging information on generalized topographic features and obtains the coverage area based on them.
期刊介绍:
The EEE Internet of Things (IoT) Journal publishes articles and review articles covering various aspects of IoT, including IoT system architecture, IoT enabling technologies, IoT communication and networking protocols such as network coding, and IoT services and applications. Topics encompass IoT's impacts on sensor technologies, big data management, and future internet design for applications like smart cities and smart homes. Fields of interest include IoT architecture such as things-centric, data-centric, service-oriented IoT architecture; IoT enabling technologies and systematic integration such as sensor technologies, big sensor data management, and future Internet design for IoT; IoT services, applications, and test-beds such as IoT service middleware, IoT application programming interface (API), IoT application design, and IoT trials/experiments; IoT standardization activities and technology development in different standard development organizations (SDO) such as IEEE, IETF, ITU, 3GPP, ETSI, etc.