Efficient Security Architecture for Physical Layer in Mmwave Communication Systems
Employing mmWave is a good way to achieve the data demands for the new and future generations of communication systems. In order to decrease power consumption and complexity of hardware, hybrid precoding is implemented for mmWave systems with large scale antenna. Lack of secure communication paths i...
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| Published in: | IEEE access Vol. 10; p. 1 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Piscataway
IEEE
2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 2169-3536, 2169-3536 |
| Online Access: | Get full text |
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| Summary: | Employing mmWave is a good way to achieve the data demands for the new and future generations of communication systems. In order to decrease power consumption and complexity of hardware, hybrid precoding is implemented for mmWave systems with large scale antenna. Lack of secure communication paths in mmWave multiple-input multiple-output (MIMO) systems leads to attack and degrade the system efficiency. For secure communications, this paper proposes a deep and secure hybrid precoder and decoder design for mmWave MIMO systems to maximize the secrecy rate. Lack of secure communication paths being eavesdropped by Eves is illustrated and the scatterer sharing channel model is assumed. The proposed algorithm consists of two convolutional neural networks for calculating the secure RF analog precoder, and then obtains the digital precoder that can further improve the security. In addition, singular value decomposition technique based physical layer security is implemented to determine digital precoders. Results showed that the secrecy performance improvement of the proposed algorithm in comparison to the benchmark algorithms and algorithms based on optimization methods. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2169-3536 2169-3536 |
| DOI: | 10.1109/ACCESS.2022.3217244 |