Design of Neural-Network-Based Mutual Coupling Compensators for Printed Planar Antenna Arrays

We propose a methodology to compensate the effect of mutual coupling in planar antenna array arrangements using a novel electromagnetic machine learning (ML) technique. The electromagnetic behavior of the array elements and their mutual coupling interactions are described via the antenna current Green's function (ACGF). A ML artificial neural network (ANN) procedure is then applied and combined with the ACGF to optimize array ports and mitigate for mutual coupling effects.