NO

N.B. Onat

6 records found

This paper examines how training data affects machine learning-assisted antenna pattern prediction under mutual coupling. For demonstration, a neural network-based approach is used to predict the embedded pattern of a central patch antenna element near randomly distributed patche ...
A novel ensemble prediction technique is introduced to enhance the accuracy of far-field embedded element pattern (EEP) prediction under mutual coupling (MC) effects, while relaxing the training data size challenge in neural network (NN)-based algorithms. The proposed method inte ...
The sunflower array topology concept is introduced, for the first time, to the constrained infinitesimal dipole modeling (IDM) technique to increase the computational efficiency and reduce the modeling errors. The concept is applied to embedded element pattern predictions via mat ...
The effects of multipath on the statistical cell-edge user service quality is for the first time investigated for mm-wave multi-user communication systems. The focus is given on setting the user spacing constraints and the transmit array topology via thinning, which can be used t ...

Efficient Embedded Element Pattern Prediction via Machine Learning

A Case Study with Planar Non-Uniform Sub-Arrays

Efficient prediction of embedded element patterns (EEPs) is including the mutual coupling (MC) effects in the optimization of irregular planar arrays is studied for the first time in the literature. An ANN-based methodology is used to predict the pattern of each element in the wh ...
The optimization of mode excitation coefficients in linear periodic arrays of multi-mode antenna elements is studied for grating lobe reduction. A novel beamforming architecture is proposed with a new optimization problem based on equi-amplitude element excitations for optimal po ...