On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things

Xinyao WANG; Xuyan BAO; Yuzhen HUANG; Zhong ZHENG; Zesong FEI

doi:10.1631/FITEE.2200188

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On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things

Regular Papers | Updated：2023-02-27

- On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things
- 衬底式安全工业物联网中的协作MIMO优化研究
- Frontiers of Information Technology & Electronic Engineering Vol. 24, Issue 2, Pages: 259-274(2023)
- Affiliations：
  
  1.School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, China
  2.China Academy of Information and Communications Technology, Beijing 100191, China
  3.Academy of Military Sciences of PLA, Beijing 100091, China
- Author bio：
  
  ‡Corresponding author
- Funds：
- DOI：10.1631/FITEE.2200188
  CLC： TN92
- Received：05 May 2022，
  
  Accepted：10 October 2022，
  
  Published：0 February 2023
- Accepted：
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Xinyao WANG, Xuyan BAO, Yuzhen HUANG, et al. On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(2): 259-274.
DOI：

Xinyao WANG, Xuyan BAO, Yuzhen HUANG, et al. On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(2): 259-274. DOI： 10.1631/FITEE.2200188.

摘要

本文研究协作多输入多输出（cooperative multi-input multi-output，C-MIMO）系统中的物理层安全技术，该技术可以被用于主次用户共存的衬底式认知无线电网络，并通过提高次级C-MIMO接收机的安全速率同时减少对主用户的干扰来实现上述安全通信范式。该通信模型尤其适合应用于基于非授权频谱的工业互联网安全传输场景，可以实现频谱效率和安全速率的有效平衡和折衷。为此，我们提出一种特征空间自适应预编码（eigenspace-adaptive precoding，EAP）方法，并给出在单站发射功率约束和干扰功率约束下的安全速率优化问题。通过将原始优化问题分解为预编码特征空间选择和功率分配两个子问题，来实现安全预编码器的设计，其中，特征空间由发射机根据主用户和次级用户的信道条件进行自适应选择。此外，本文针对海量设备、大维天线系统提出一种简化的EAP方法，该方法充分利用大维天线的空间自由度来降低安全预编码优化的复杂度。仿真结果表明，在自适应选择的特征空间中传输信号和人工噪声，C-MIMO系统可以完全消除保密中断概率，获得相比固定特征空间预编码方案更高的安全速率。此外，针对大维C-MIMO提出的简化EAP方法可以显著提高安全速率。

Abstract

In this paper

physical layer security techniques are investigated for cooperative multi-input multi-output (C-MIMO)

which operates as an underlaid cognitive radio system that coexists with a primary user (PU). The underlaid secrecy paradigm is enabled by improving the secrecy rate towards the C-MIMO receiver and reducing the interference towards the PU. Such a communication model is especially suitable for implementing Industrial Internet of Things (IIoT) systems in the unlicensed spectrum

which can trade off spectral efficiency and information secrecy. To this end

we propose an eigenspace-adaptive precoding (EAP) method and formulate the secrecy rate optimization problem

which is subject to both the single device power constraint and the interference power constraint. This precoder design is enabled by decomposing the original optimization problem into eigenspace selection and power allocation sub-problems. Herein

the eigenvectors are adaptively selected by the transmitter according to the channel conditions of the underlaid users and the PUs. In addition

a simplified EAP method is proposed for large-dimensional C-MIMO transmission

exploiting the additional spatial degree of freedom for a low-complexity secrecy precoder design. Numerical results show that by transmitting signal and artificial noise in the properly selected eigenspace

C-MIMO can eliminate the secrecy outage and outperforms the fixed eigenspace precoding methods. Moreover

the proposed simplified EAP method for the large-dimensional C-MIMO can significantly improve the secrecy rate.

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