Multi-Objective Hybrid Optimization Algorithm for Design a Printed MIMO Antenna With n78-5G NR Frequency Band Applications

This study introduces a novel multi-objective optimization algorithm integrating Customized Mutated Particle Swarm Optimization (CM-PSO) and an innovative modified Genetic Algorithm (GA) using an unexplored merged chaotic map. The hybrid algorithm converges to desired results faster than CM-PSO and modified GA without trapping in local minima. Validation is conducted by designing a single-element and simple-structure dipole antenna so that its optimized S11 is better than-30 dB at the resonance frequency and covers the 3.3 to 3.8 GHz frequency band with S-11 < -10 dB. Certainly, the-30 dB and covering frequency band criteria can be modified in the proposed algorithm. In the algorithm, the isolation between elements of a quad-Multiple-Input/Multiple-Output antenna, constructed using optimized dipole antennas, is set to be less than-20 dB (changeable criteria) so that the smallest size can be achieved. Computer Simulation Technology (CST) Studio Suite carries out electromagnetic and high-frequency simulations, and the novel developed optimization algorithm in MATLAB determines what and how much parameter values need to be changed by CM-PSO or an innovative modified GA in order to enhance the antenna's S-11 result and its Impedance Bandwidth (IBW). The input parameters of the algorithm are the dimensions of the proposed antenna's elements, which significantly influence its performance.