电信科学 ›› 2020, Vol. 36 ›› Issue (10): 79-86.doi: 10.11959/j.issn.1000-0801.2020291

• 专题:智能通信技术 • 上一篇    下一篇

全双工无线通信系统的智能安全中继选择策略

刘芳1,王亚娟2,赖峥嵘3,刘元安1   

  1. 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
  • 修回日期:2020-10-17 出版日期:2020-10-20 发布日期:2020-11-07
  • 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
  • 基金资助:
    广东省重点领域研发计划项目(2019B010157001);国家自然科学基金资助项目(61821001)

Intelligent security relay selection for full duplex wireless communications

Fang LIU1,Yajuan WANG2,Zhengrong LAI3,Yuan’an LIU1   

  1. 1 School of Electronic Engineering,Beijing University of Posts and Telecommunications,Beijing 100876,China
    2 Research Institute of China Mobile Communications Co.,Ltd.,Beijing 100032,China
    3 Guangdong Communications and Networks Institute,Guangzhou 510760,China
  • Revised:2020-10-17 Online:2020-10-20 Published:2020-11-07
  • Supported by:
    The Key Area Research and Development Program of Guangdong Province of China(2019B010157001);The National Natural Science Foundation of China(61821001)

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。

关键词: 全双工, 中继选择, 监督学习, 多分类器

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.

Key words: full-duplex, relay selection, supervised learning, multi-classifier

中图分类号: 

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