Lingfeng Shen;Huanran Zhang;Ning Wang;Ying Cui;Xiang Cheng;Xiaomin Mu
{"title":"Joint Clustering and 3-D UAV Deployment for Delay-Aware UAV-Enabled MTC Data Collection Networks","authors":"Lingfeng Shen;Huanran Zhang;Ning Wang;Ying Cui;Xiang Cheng;Xiaomin Mu","doi":"10.1109/LSENS.2024.3487009","DOIUrl":null,"url":null,"abstract":"The design of timely data collection for a machine-type communication (MTC) network by unmanned-aerial-vehicle (UAV) platform is investigated. The ground-based MTC devices are clustered for efficient service, and the UAV station's deployment in the 3-D space is optimized. The corresponding mission time minimization problem is formulated as a coupled mixed-integer nonlinear program. For tractability, the original problem is decomposed into two subproblems respectively dealing with clustering-hovering optimization and intercluster UAV traveling path minimization. An alternating clustering-hovering optimization (ACH) and ant colony optimization (ACO) solution approach is proposed accordingly. Simulations are conducted to validate the superiority of the proposed ACH–ACO scheme over the scheme based on \n<inline-formula><tex-math>$k$</tex-math></inline-formula>\n-means clustering.","PeriodicalId":13014,"journal":{"name":"IEEE Sensors Letters","volume":"8 12","pages":"1-4"},"PeriodicalIF":2.2000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Sensors Letters","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10736673/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0
Abstract
The design of timely data collection for a machine-type communication (MTC) network by unmanned-aerial-vehicle (UAV) platform is investigated. The ground-based MTC devices are clustered for efficient service, and the UAV station's deployment in the 3-D space is optimized. The corresponding mission time minimization problem is formulated as a coupled mixed-integer nonlinear program. For tractability, the original problem is decomposed into two subproblems respectively dealing with clustering-hovering optimization and intercluster UAV traveling path minimization. An alternating clustering-hovering optimization (ACH) and ant colony optimization (ACO) solution approach is proposed accordingly. Simulations are conducted to validate the superiority of the proposed ACH–ACO scheme over the scheme based on
$k$
-means clustering.