{"title":"Collaborative multi-UAV sensing in integrated sensing and communication networks","authors":"Xianzhe Xu, Rentuo Tao, Shikang Li, Yawei Chen, Linghao Xia, Yuhao Yang","doi":"10.1117/12.2691404","DOIUrl":null,"url":null,"abstract":"This paper studies the collaborative unmanned aerial vehicle (UAV) sensing in integrated sensing and communication (ISAC) networks. By equipping sensing and communication units on UAVs, they can execute sensing tasks and transmit the sensing information to the base station (BS) for environment sensing. Due to the mobility and dense deployment of UAVs, they can sense the environment with much lower cost compared to the BS sensing. We aim to minimize the network sensing cost by optimizing the UAV deployment and task assignment collaboratively. For this joint optimization problem, we propose an iterative mechanism to optimize the UAV deployment and task assignment iteratively. UAV deployment problem is modeled as a cluster problem and we utilize a K-means cluster algorithm to solve it efficiently. For task assignment problem, we propose a greedy algorithm to solve it with low complexity. Simulation results validate the effectiveness of our proposed method in different scenarios.","PeriodicalId":114868,"journal":{"name":"International Conference on Optoelectronic Information and Computer Engineering (OICE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Optoelectronic Information and Computer Engineering (OICE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2691404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper studies the collaborative unmanned aerial vehicle (UAV) sensing in integrated sensing and communication (ISAC) networks. By equipping sensing and communication units on UAVs, they can execute sensing tasks and transmit the sensing information to the base station (BS) for environment sensing. Due to the mobility and dense deployment of UAVs, they can sense the environment with much lower cost compared to the BS sensing. We aim to minimize the network sensing cost by optimizing the UAV deployment and task assignment collaboratively. For this joint optimization problem, we propose an iterative mechanism to optimize the UAV deployment and task assignment iteratively. UAV deployment problem is modeled as a cluster problem and we utilize a K-means cluster algorithm to solve it efficiently. For task assignment problem, we propose a greedy algorithm to solve it with low complexity. Simulation results validate the effectiveness of our proposed method in different scenarios.