RF Designs and Simulations

Over the past few year, machine learning has attracted the attention of antenna engineers. Generally, the process of antenna design requires to find out the EM characteristics of antenna by observing the current distributions through simulations. These EM properties are then used for the parameters optimization. Machine learning (ML) can be combined with simulations to design an antenna. The inclusion of artificial intelligence (AI) can give promising results in the field of antenna designing. In recent years, antenna synthesis or design optimization through evolutionary algorithms (EAs) has been applied widely. At present, differential evolution (DE) and particle swarm optimization (PSO) are top two popular algorithms in the antenna synthesis area. In smart antenna array, the objective of the gracefully degradation of the beamforming and beamsteering performance, can be achieved by reconfiguring the array when an element is found to be defective. This reconfiguration can be obtain