Applications Of Antenna Arrays To Mobile Communications, Part I: Performance Improvement, Feasibility, And System Considerations

1997 ◽  
Vol 85 (7) ◽  
pp. 1029-1030 ◽  
Keyword(s):  
Performance Improvement ◽  
Mobile Communications ◽  
Antenna Arrays

Miniaturisation of antenna arrays for mobile communications

2005 ◽  
Author(s):  
J. Weber ◽  
Ch. Volmer ◽  
K. Blau ◽  
R. Stephan ◽  
M.A. Hein
Keyword(s):  
Mobile Communications ◽  
Antenna Arrays

scholarly journals Deep Learning-Based Beamforming for Millimeter-Wave Systems Using Parametric ReLU Activation Function

2021 ◽  
Author(s):  
Alshimaa Hamdy ◽  
Tarek Abed Soliman ◽  
Mohamed Rihan ◽  
Moawad I. Dessouky
Keyword(s):  
Deep Learning ◽  
Performance Improvement ◽  
Millimeter Wave ◽  
Antenna Arrays ◽  
Activation Function ◽  
Model Accuracy ◽  
Learning Network ◽  
Parametric Rectified Linear Unit ◽  
Complexity Cost ◽  
Deep Learning Network

Abstract Beamforming design is a crucial stage in millimeter-wave systems with massive antenna arrays. We propose a deep learning network for the design of the precoder and combiner in hybrid architectures. The proposed network employs a parametric rectified linear unit (PReLU) activation function which improves model accuracy with almost no complexity cost compared to other functions. The proposed network accepts practical channel estimation input and can be trained to enhance spectral efficiency considering the hardware limitation of the hybrid design. Simulation shows that the proposed network achieves small performance improvement when compared to the same network with the ReLU activation function.

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