Intelligent security relay selection for full duplex wireless communications

Fang LIU; Yajuan WANG; Zhengrong LAI; Yuan’an LIU

doi:10.11959/j.issn.1000-0801.2020291

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Intelligent security relay selection for full duplex wireless communications

Topic:Intelligent Communication Technology | 更新时间：2024-06-05

- Intelligent security relay selection for full duplex wireless communications
- Telecommunications Science Vol. 36, Issue 10, Pages: 79-86(2020)
- 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：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2020291
  CLC： TP393
- Published Online：2020-10，
  
  Published：20 October 2020
- 稿件说明：
移动端阅览
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：

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

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