多用户点对点无线中继网络鲁棒安全传输设计

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Distributed Sensor Networks Pub Date : 2022-06-01 DOI:10.1177/15501329221107582
Dongmei Yang, Hongjun Li, Baoquan Ren, Xudong Zhong
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引用次数: 0

摘要

在本文中,我们研究了多用户对等中继网络的鲁棒安全传输设计,在该网络中,所有用户都要求安全通信,而窃听者是被动的。尽管先前的研究已经设计了在完美信道状态信息下的物理层安全方案,但本研究侧重于研究在存在被动窃听器的情况下的鲁棒传输设计。我们的目标是最大限度地提高人工噪声功率,以迷惑被动窃听者,并在有界球面区域下,对所有用户进行最坏情况的信干噪比约束,以确定从中继站到目的地的信道状态信息误差向量的范数和所有中继节点的单个功率约束。在数学上,原有的鲁棒问题由于其非线性和非凸性而难以求解。我们建议采用S-过程和秩松弛技术将其转化为半定规划凸问题。数值结果表明了该方法的优越性。
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Robust security transmission design for multi-user peer-to-peer wireless relay networks
In this article, we studied the robust security transmission design for multi-user peer-to-peer relay networks, where all users demand secure communication and the eavesdropper is passive. Although the previous researches have designed the physical-layer security schemes under perfect channel state information, this study focuses on investigating the robust transmission design in the presence of a passive eavesdropper. Our goal is to maximize the artificial noise power to confuse the passive eavesdropper and subject to the worst-case signal-to-interference-noise-ratio constraints for all users under a bounded spherical region for the norm of the channel state information error vector from the relays to the destinations and the individual power constraints of all relay nodes. Mathematically, the original robust problem is difficult to solve due to its non-linearity and non-convexity. We propose to adopt S-Procedure and rank relaxation techniques to convert it to a semidefinite programming convex problem. The numerical results show the advantage of the proposed robust method.
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来源期刊
CiteScore
6.50
自引率
4.30%
发文量
94
审稿时长
3.6 months
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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