AI-based antenna design and optimization using MOZO algorithm

Abstract

Wireless communication has revolutionized technology in recent years performance and capacity are affected when new smart devices arrive. the 5G technology comes with high performance antenna solutions that can deliver faster data rates, lower latency, and enhanced reliability. Printed antennas due to their low cost, compact size and ease of fabrication are becoming an essential component in 5G wireless communication systems like (massive MIMO, mm Wave…) [1]. This papers will explores the optimization of printed antennas for 5G application , focusing on the use advanced MOZO [2]technique to enhance performance metrics like bandwidth, gain, efficiency and beamforming capabilities , we will present a comprehensive study of antenna design techniques , which can significantly improve the overall performance, a multi objective optimization approach is implemented to fine tune key parameters while meeting the stringent demands of 5G network, including mm Wave frequency Bands. The simulation validation demonstrates the effectiveness of this optimization technique in achieving optimal antenna performance for 5G communication systems. CST and MATLAB were used to perform and evaluate the antenna performance in terms of return loss and gain.