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全双工无线通信系统的智能安全中继选择策略
Intelligent security relay selection for full duplex wireless communications
- 电信科学 2020年36卷第10期 页码：79-86
- 作者机构：
1. 北京邮电大学电子工程学院，北京 100876
2. 中国移动通信有限公司研究院，北京 100053
3. 广东省新一代通信与网络创新研究院，广东 广州 510760
- 作者简介：
[ "刘芳（1974- ），女，北京邮电大学副教授，主要研究方向为宽带无线通信与智能网络" ]
[ "王亚娟（1993- ），女，中国移动通信有限公司研究院助理研究员，主要研究方向为6G无线通信中感知通信融合技术与多智能体交互技术" ]
[ "赖峥嵘（1971- ），男，广东省新一代通信与网络创新研究院研究员，主要研究方向为无线移动通信和人工智能" ]
[ "刘元安（1963- ），男，北京邮电大学教授，主要研究方向为无线通信与智慧微波" ]
- 基金信息：广东省科技厅重点项目;Science and Technology Key Project of Guang-dong Province(2019B010157001);国家自然科学基金资助项目;The National Natural Science Foundation of China(61821001)
DOI：10.11959/j.issn.1000-0801.2020291
中图分类号： TP393-
网络出版日期：2020-10，
纸质出版日期：2020-10-20
- 稿件说明：
移动端阅览
刘芳, 王亚娟, 赖峥嵘, 等. 全双工无线通信系统的智能安全中继选择策略[J]. 电信科学, 2020,36(10):79-86.
Fang LIU, Yajuan WANG, Zhengrong LAI, et al. Intelligent security relay selection for full duplex wireless communications[J]. Telecommunications science, 2020, 36(10): 79-86.
刘芳, 王亚娟, 赖峥嵘, 等. 全双工无线通信系统的智能安全中继选择策略[J]. 电信科学, 2020,36(10):79-86. DOI： 10.11959/j.issn.1000-0801.2020291.
Fang LIU, Yajuan WANG, Zhengrong LAI, et al. Intelligent security relay selection for full duplex wireless communications[J]. Telecommunications science, 2020, 36(10): 79-86. DOI： 10.11959/j.issn.1000-0801.2020291.
摘要
全双工技术理论上可以使频谱效率提升一倍，将其应用于双向中继系统，能进一步提升系统的频谱效率。考虑残余自干扰与信道环境，以安全容量最大化为目标进行中继选择，将该选择优化问题建模为多分类问题，提出了一种基于卷积神经网络（CNN）的智能中继选择策略。在设计分类模型时利用CNN提取信道的空间相关性，设置卷积核的维度与中继数目相关，为了保留输入特征的矩阵特性未使用池化层。仿真结果表明，在降低计算复杂度和减少反馈开销的情况下，基于CNN的分类器具有更高的分类准确率，能获得与传统最优中继选择方案一致的安全容量。
Abstract
Full-duplex can double the spectrum efficiency theoretically.Thus it can further improve the spectrum efficiency when it is used in the relay systems.Considering the residual self-interference and signal-to-noise ratio
a problem was set to maximize the security capacity by selecting the optimal relay.This optimization problem was transformed into multi-classification problem.Thus a convolutional neural network (CNN)-based intelligent relay selection scheme was proposed.In the design of the classification model
the CNN was used to extract the spatial correlation of the channel
and the dimension of the convolution kernel was related to the number of relays.The pooling layer was not used to preserve the matrix characteristics of the input features.The simulation results show that the proposed CNN-based intelligent selection classification model has high classification accuracy
and can obtain the same security performance as the traditional exhaustive search scheme
and the real-time performance is significantly improved.
关键词
Keywords
references
ZOU Y L , WANG X B , SHEN W M . Optimal relay selection for physical-layer security in cooperative wireless networks [J ] . IEEE Journal on Selected Areas in Communications , 2013 , 31 ( 10 ): 2099 - 2111 .
CUI C X , CUI Y M , YANG W W , et al . Average secrecy rate analysis with relay selection using decode-and-forward strategy in cooperative networks [C ] // Proceedings of International Conference on Wireless Communications ＆ Signal Processing . Piscataway:IEEE Press , 2013 .
DING X , SONG T , ZOU Y , et al . Security-reliability tradeoff analysis of artificial noise aided two-way opportunistic relay selection [J ] . IEEE Transactions on Vehicular Technology , 2016 , 66 ( 99 ):1.
CHEN G J , GONG Y , XIAO P , et al . Physical layer network security in the full-duplex relay system [J ] . IEEE Transactions on Information Forensics ＆ Security , 2015 , 10 ( 3 ): 574 - 583 .
ZHONG B , ZHANG Z . Secure full-duplex two-way relaying networks with optimal relay selection [J ] . IEEE Communications Letters , 2017 :1.
LIU F , LI J , LI S , et al . Physical layer security of full-duplex two-way AF relaying networks with optimal relay selection [C ] // Proceedings of 2018 IEEE Globecom Workshops (GC Wkshps) . Piscataway:IEEE Press , 2018 : 1 - 6 .
周巍 , 高锐锋 , 吉晓东 , 等 . 基于协作干扰的全双工中继系统混合安全传输协议 [J ] . 电信科学 , 2017 , 33 ( 1 ): 16 - 23 .
ZHOU W , GAO R F , JI X D , et al . A hybrid cooperative jamming protocol for full-duplex relay wiretap system [J ] . Telecommunications Science , 2017 , 33 ( 1 ): 16 - 23 .
JIANG C , ZHANG H , REN Y , et al . Machine learning paradigms for next-generation wireless networks [J ] . IEEE Wireless Communications , 2017 , 24 ( 2 ): 98 - 105 .
JOUNG J . Machine learning-based antenna selection in wireless communications [J ] . IEEE Communications Letters , 2016 , 20 ( 11 ): 2241 - 2244 .
HE D , LIU C , QUEK T Q , et al . Transmit antenna selection in MIMO wiretap channels:a machine learning approach [J ] . IEEE Wireless Communications Letters , 2018 , 7 ( 4 ): 634 - 637
YANG N , YEOH P L , ELKASHLAN M , et al . Transmit antenna selection for security enhancement in MIMO wiretap channels [J ] . IEEE Transactions on Communications , 2013 , 61 ( 1 ): 144 - 154 .
CAI J , LI Y , HU Y . Deep convolutional neural network based antenna selection in multiple-input multiple-output system [C ] // Proceedings of Young Scientists Forum 2017.[S.l.:s.n] . 2018 .
IBRAHIM M S , ZAMZAM A S , FU X , et al . Learning-based antenna selection for multicasting [C ] // Proceedings of 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) . Piscataway:IEEE Press , 2018 .
ELBIR A M , MISHRA K V , ELDAR Y C , et al . Cognitive radar antenna selection via deep learning [J ] . Iet Radar Sonar and Navigation , 2019 , 13 ( 6 ): 871 - 880 .
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