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.
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。
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Z. ZHENG is supported by the National Natural Science Foundation of China (No. 61901033) and 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) and the Beijing Nova Program (No. Z201100006820121)
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Xinyao WANG and Zhong ZHENG designed the research. Xuyan BAO and Yuzhen HUANG processed the data. Xinyao WANG and Zhong ZHENG drafted the paper. Zesong FEI helped organize the paper. Xuyan BAO, Yuzhen HUANG, and Zesong FEI revised and finalized the paper.
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Xinyao WANG, Xuyan BAO, Yuzhen HUANG, Zhong ZHENG, and Zesong FEI declare that they have no conflict of interest.
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The data that support the findings of this study are available from the corresponding author upon reasonable request.
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Wang, X., Bao, X., Huang, Y. et al. On optimization of cooperative MIMO for underlaid secrecy Industrial Internet of Things. Front Inform Technol Electron Eng 24, 259–274 (2023). https://doi.org/10.1631/FITEE.2200188
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DOI: https://doi.org/10.1631/FITEE.2200188
Key words
- Cognitive radio network
- Physical layer security
- Cooperative multi-input multi-output (C-MIMO)
- Eigenspace-adaptive precoding
- Difference convex programming