Machine Learning-Assisted Decoupling Topology Design for Antenna Array Application

In modern communications, the mutual coupling between antenna elements will heavily degrade the overall performance of the system. In this work, a machine learning-assisted optimization (MLAO) method is introduced to design the decoupling topology. The MLAO method involves ML methods to build surrogate models between the decoupling topology and the array performance, therefore facilitate the optimization and design of the decoupling structure. Several practical designs have been given to validate the proposed MLAO method.