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

作　　者：Xinyao WANG Xuyan BAO Yuzhen HUANG Zhong ZHENG Zesong FEI 

机构地区：[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

出　　处：《Frontiers of Information Technology & Electronic Engineering》2023年第2期259-274,共16页信息与电子工程前沿（英文版）

基　　金：Z.ZHENG is supported by the National Natural Science Foundation of China(No.61901033);the Natural Science Foundation of Beijing(No.L212031);X.Y.BAO is supported by the China Academy of Information and Communications Technology,Y.Z.HUANG is supported by the National Natural Science Foundation of China(No.61971474);the Beijing Nova Program(No.Z201100006820121)。

摘　　要：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.

关 键 词：Cognitive radio network Physical layer security Cooperative multi-input multi-output(C-MIMO) Eigenspace-adaptive precoding Difference convex programming 

分 类 号：TP399[自动化与计算机技术—计算机应用技术]