English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Employing mmWave is a good way to achieve the data demands for the new and future generations of communication systems. In order to decrease hardware power consumption and complexity, hybrid precoding is implemented for mmWave communication 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 schemes 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 (CNNs) 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.

Efficient Security Architecture for Physical Layer in mmWave Communication Systems