空中 RIS 辅助物理层安全:优化部署和分区

IF 7.4 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-04-23 DOI:10.1109/TCCN.2024.3392798
Sultangali Arzykulov;Abdulkadir Celik;Galymzhan Nauryzbayev;Ahmed M. Eltawil
{"title":"空中 RIS 辅助物理层安全:优化部署和分区","authors":"Sultangali Arzykulov;Abdulkadir Celik;Galymzhan Nauryzbayev;Ahmed M. Eltawil","doi":"10.1109/TCCN.2024.3392798","DOIUrl":null,"url":null,"abstract":"We propose a novel approach for enhancing physical layer security (PLS) in wireless networks by utilizing a combination of reconfigurable intelligent surfaces (RIS) and artificial noise (AN). The proposed aerial RIS (A-RIS) concept utilizes a RIS-attached unmanned aerial vehicle (UAV) that hovers over the network area to improve the signal quality for legitimate users and jam that of illegitimate ones. We propose a method of virtually partitioning the RIS, such that the partition phase shifts are configured to improve the intended signal at a legitimate user while simultaneously increasing the impact of AN on illegitimate users. Closed-form (CF) expressions for legitimate and illegitimate users’ ergodic secrecy capacity (ESC) are derived and validated. Then, optimization problems are formulated to maximize network ESC by optimizing the 3D deployment of the A-RIS and RIS portions for users subject to predefined quality-of-service constraints. Simulation results validate CF solutions and demonstrate that the proposed joint A-RIS deployment and partitioning framework can significantly improve network security compared to benchmarks where RIS and AN are separately used without deployment optimization. Additionally, the proposed deployment approaches converge in less than a second using CF optimal RIS portions, making it suitable for dynamic A-RIS deployment.","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"10 5","pages":"1867-1882"},"PeriodicalIF":7.4000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Aerial RIS-Aided Physical Layer Security: Optimal Deployment and Partitioning\",\"authors\":\"Sultangali Arzykulov;Abdulkadir Celik;Galymzhan Nauryzbayev;Ahmed M. Eltawil\",\"doi\":\"10.1109/TCCN.2024.3392798\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose a novel approach for enhancing physical layer security (PLS) in wireless networks by utilizing a combination of reconfigurable intelligent surfaces (RIS) and artificial noise (AN). The proposed aerial RIS (A-RIS) concept utilizes a RIS-attached unmanned aerial vehicle (UAV) that hovers over the network area to improve the signal quality for legitimate users and jam that of illegitimate ones. We propose a method of virtually partitioning the RIS, such that the partition phase shifts are configured to improve the intended signal at a legitimate user while simultaneously increasing the impact of AN on illegitimate users. Closed-form (CF) expressions for legitimate and illegitimate users’ ergodic secrecy capacity (ESC) are derived and validated. Then, optimization problems are formulated to maximize network ESC by optimizing the 3D deployment of the A-RIS and RIS portions for users subject to predefined quality-of-service constraints. Simulation results validate CF solutions and demonstrate that the proposed joint A-RIS deployment and partitioning framework can significantly improve network security compared to benchmarks where RIS and AN are separately used without deployment optimization. Additionally, the proposed deployment approaches converge in less than a second using CF optimal RIS portions, making it suitable for dynamic A-RIS deployment.\",\"PeriodicalId\":13069,\"journal\":{\"name\":\"IEEE Transactions on Cognitive Communications and Networking\",\"volume\":\"10 5\",\"pages\":\"1867-1882\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2024-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Cognitive Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10507188/\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cognitive Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10507188/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

我们提出了一种利用可重构智能表面(RIS)和人工噪音(AN)相结合来增强无线网络物理层安全性(PLS)的新方法。所提出的空中 RIS(A-RIS)概念利用了一个附着 RIS 的无人飞行器(UAV),该飞行器在网络区域上空盘旋,以提高合法用户的信号质量,并干扰非法用户的信号质量。我们提出了一种虚拟分区 RIS 的方法,通过配置分区相移来改善合法用户的预期信号,同时增加 AN 对非法用户的影响。我们推导并验证了合法用户和非法用户的ergodic secrecy capacity (ESC) 的闭式 (CF) 表达式。然后,在预定义的服务质量约束条件下,通过优化用户 A-RIS 和 RIS 部分的 3D 部署,提出了最大化网络 ESC 的优化问题。仿真结果验证了 CF 解决方案,并证明与单独使用 RIS 和 AN 而不进行部署优化的基准相比,所提出的 A-RIS 联合部署和分区框架可显著提高网络安全性。此外,使用 CF 最佳 RIS 部分,所提出的部署方法可在不到一秒的时间内收敛,因此适用于动态 A-RIS 部署。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Aerial RIS-Aided Physical Layer Security: Optimal Deployment and Partitioning
We propose a novel approach for enhancing physical layer security (PLS) in wireless networks by utilizing a combination of reconfigurable intelligent surfaces (RIS) and artificial noise (AN). The proposed aerial RIS (A-RIS) concept utilizes a RIS-attached unmanned aerial vehicle (UAV) that hovers over the network area to improve the signal quality for legitimate users and jam that of illegitimate ones. We propose a method of virtually partitioning the RIS, such that the partition phase shifts are configured to improve the intended signal at a legitimate user while simultaneously increasing the impact of AN on illegitimate users. Closed-form (CF) expressions for legitimate and illegitimate users’ ergodic secrecy capacity (ESC) are derived and validated. Then, optimization problems are formulated to maximize network ESC by optimizing the 3D deployment of the A-RIS and RIS portions for users subject to predefined quality-of-service constraints. Simulation results validate CF solutions and demonstrate that the proposed joint A-RIS deployment and partitioning framework can significantly improve network security compared to benchmarks where RIS and AN are separately used without deployment optimization. Additionally, the proposed deployment approaches converge in less than a second using CF optimal RIS portions, making it suitable for dynamic A-RIS deployment.
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
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
期刊最新文献
Intelligent Resource Adaptation for Diversified Service Requirements in Industrial IoT Real Field Error Correction for Coded Distributed Computing based Training Adaptive PCI Allocation in Heterogeneous Networks: A DRL-Driven Framework With Hash Table, FAGA, and Guiding Policies Generative AI on SpectrumNet: An Open Benchmark of Multiband 3D Radio Maps LiveStream Meta-DAMS: Multipath Scheduler Using Hybrid Meta Reinforcement Learning for Live Video Streaming
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1