Z. Hou, Jin Chen, Guoxin Li, Yu-zhen Huang, Yifan Xu, Yuhua Xu
{"title":"Matching Design in Multi-IRS-UAV-assisted Multi-pair Anti-jamming Communication Networks","authors":"Z. Hou, Jin Chen, Guoxin Li, Yu-zhen Huang, Yifan Xu, Yuhua Xu","doi":"10.1109/IEEECONF52377.2022.10013344","DOIUrl":null,"url":null,"abstract":"This paper studies the matching optimization problem in multi-IRS-UAV-assisted multi-pair anti-jamming communication networks. The matching relationship between the transmitters and IRS-UAVs is formed to improve the overall anti-jamming performance, and we formulate it as a non-substitutable many-to-many matching problem. To solve this problem, we propose a low-complexity distributed matching-based optimization algorithm. Numerical results show that the proposed algorithm has a significant performance improvement than the random matching algorithm and is even close to optimal performance.","PeriodicalId":193681,"journal":{"name":"2021 International Conference on Advanced Computing and Endogenous Security","volume":"119 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Advanced Computing and Endogenous Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEECONF52377.2022.10013344","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper studies the matching optimization problem in multi-IRS-UAV-assisted multi-pair anti-jamming communication networks. The matching relationship between the transmitters and IRS-UAVs is formed to improve the overall anti-jamming performance, and we formulate it as a non-substitutable many-to-many matching problem. To solve this problem, we propose a low-complexity distributed matching-based optimization algorithm. Numerical results show that the proposed algorithm has a significant performance improvement than the random matching algorithm and is even close to optimal performance.