Secure MIMO Communication Relying on Movable Antennas

IF 8.3 2区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Communications Pub Date : 2024-09-20 DOI:10.1109/TCOMM.2024.3465369
Jun Tang;Cunhua Pan;Yang Zhang;Hong Ren;Kezhi Wang
{"title":"Secure MIMO Communication Relying on Movable Antennas","authors":"Jun Tang;Cunhua Pan;Yang Zhang;Hong Ren;Kezhi Wang","doi":"10.1109/TCOMM.2024.3465369","DOIUrl":null,"url":null,"abstract":"This paper considers a movable antenna (MA)-aided secure multiple-input multiple-output (MIMO) communication system consisting of a base station (BS), a legitimate information receiver (IR) and an eavesdropper (Eve), where the BS is equipped with MAs to enhance the system’s physical layer security (PLS). Specifically, we aim to maximize the secrecy rate (SR) by jointly optimizing the transmit precoding (TPC) matrix, the artificial noise (AN) covariance matrix and the MAs’ positions under the constraints of the maximum transmit power and the minimum spacing between MAs. To solve this non-convex problem with highly coupled optimization variables, the block coordinate descent (BCD) method is applied to alternately update the variables. Specifically, we first reformulate the SR into a tractable form, and derive the optimal TPC matrix and the AN covariance matrix with fixed MAs’ positions by applying the Lagrangian multiplier method in semi-closed forms. Then, the majorization-minimization (MM) algorithm is employed to iteratively optimize each MA’s position while keeping others fixed. We also extend this work to the more general multicast scenario. Finally, simulation results are provided to demonstrate the effectiveness of the proposed algorithms and the significant advantages of the MAs over conventional fixed position antennas (FPAs) in enhancing system’s security.","PeriodicalId":13041,"journal":{"name":"IEEE Transactions on Communications","volume":"73 4","pages":"2159-2175"},"PeriodicalIF":8.3000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Communications","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10684758/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

Abstract

This paper considers a movable antenna (MA)-aided secure multiple-input multiple-output (MIMO) communication system consisting of a base station (BS), a legitimate information receiver (IR) and an eavesdropper (Eve), where the BS is equipped with MAs to enhance the system’s physical layer security (PLS). Specifically, we aim to maximize the secrecy rate (SR) by jointly optimizing the transmit precoding (TPC) matrix, the artificial noise (AN) covariance matrix and the MAs’ positions under the constraints of the maximum transmit power and the minimum spacing between MAs. To solve this non-convex problem with highly coupled optimization variables, the block coordinate descent (BCD) method is applied to alternately update the variables. Specifically, we first reformulate the SR into a tractable form, and derive the optimal TPC matrix and the AN covariance matrix with fixed MAs’ positions by applying the Lagrangian multiplier method in semi-closed forms. Then, the majorization-minimization (MM) algorithm is employed to iteratively optimize each MA’s position while keeping others fixed. We also extend this work to the more general multicast scenario. Finally, simulation results are provided to demonstrate the effectiveness of the proposed algorithms and the significant advantages of the MAs over conventional fixed position antennas (FPAs) in enhancing system’s security.
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
依靠可移动天线的安全多输入多输出(MIMO)通信
本文研究了一种由基站(BS)、合法信息接收器(IR)和窃听器(Eve)组成的可移动天线(MA)辅助安全多输入多输出(MIMO)通信系统,其中基站配备可移动天线以增强系统的物理层安全性(PLS)。具体而言,我们的目标是在最大发射功率和最小MAs间距的约束下,通过联合优化发射预编码(TPC)矩阵、人工噪声(AN)协方差矩阵和MAs的位置来最大化保密率(SR)。为了解决这一具有高度耦合优化变量的非凸问题,采用块坐标下降法交替更新变量。具体而言,我们首先将SR重新表述为可处理的形式,并在半封闭形式下应用拉格朗日乘子法推导出最优TPC矩阵和固定MAs位置的AN协方差矩阵。然后,采用最大-最小(MM)算法迭代优化每个MA的位置,同时保持其他MA的位置不变。我们还将这项工作扩展到更通用的多播场景。最后,仿真结果证明了算法的有效性,以及MAs相对于传统固定位置天线(fpa)在提高系统安全性方面的显著优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
IEEE Transactions on Communications
IEEE Transactions on Communications 工程技术-电信学
CiteScore
16.10
自引率
8.40%
发文量
528
审稿时长
4.1 months
期刊介绍: The IEEE Transactions on Communications is dedicated to publishing high-quality manuscripts that showcase advancements in the state-of-the-art of telecommunications. Our scope encompasses all aspects of telecommunications, including telephone, telegraphy, facsimile, and television, facilitated by electromagnetic propagation methods such as radio, wire, aerial, underground, coaxial, and submarine cables, as well as waveguides, communication satellites, and lasers. We cover telecommunications in various settings, including marine, aeronautical, space, and fixed station services, addressing topics such as repeaters, radio relaying, signal storage, regeneration, error detection and correction, multiplexing, carrier techniques, communication switching systems, data communications, and communication theory. Join us in advancing the field of telecommunications through groundbreaking research and innovation.
期刊最新文献
Moving or Predicting? RoleAware-MAPP: A Role-Aware Transformer Framework for Movable Antenna Position Prediction to Secure Wireless Communications Enhancing Spatial Multiplexing and Interference Suppression for Near- and Far-Field Communications with Sparse MIMO Designing Unimodular Arrays With Low Correlation Sidelobes for Omnidirectional Transmission in Massive MIMO Systems Random Matrix Analysis of Secrecy Outage Probability for MISO Systems with RZF Precoding Start-of-Packet Detection Using Machine Learning
×
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:604180095
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