This paper explores the application of Artificial Intelligence (AI) algorithms to control the radiation pattern of smart antennas in high-mobility contexts, such as drones, 5G, and automotive applications. The authors present an AI-based method that employs a feed-forward Artificial Neural Network (ANN) to steer the beam towards a desired direction by modifying the radiation pattern according to specific angular input values. To enhance efficiency and minimize computational complexity, the network structure is carefully designed. The proposed method is evaluated on two arrays of specifically designed 18 GHz antennas, illustrating its compatibility with various applications. The results show that the approach is efficient, with a reconfigurability time suitable for high-mobility scenarios. The method is also user-friendly and scalable, making it a viable option for diverse applications.
An AI-based Model for Smart Control of High-Mobility Phased Arrays
Catarinucci, Luca;Colella, Riccardo
2023-01-01
Abstract
This paper explores the application of Artificial Intelligence (AI) algorithms to control the radiation pattern of smart antennas in high-mobility contexts, such as drones, 5G, and automotive applications. The authors present an AI-based method that employs a feed-forward Artificial Neural Network (ANN) to steer the beam towards a desired direction by modifying the radiation pattern according to specific angular input values. To enhance efficiency and minimize computational complexity, the network structure is carefully designed. The proposed method is evaluated on two arrays of specifically designed 18 GHz antennas, illustrating its compatibility with various applications. The results show that the approach is efficient, with a reconfigurability time suitable for high-mobility scenarios. The method is also user-friendly and scalable, making it a viable option for diverse applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
