A Multi-Level Optimization Method Using PSO for the Optimal Design of an L-Shaped Folded Monopole Antenna Array

Abstract

This study presents a multi-level optimization (MLO) method applied in particle swarm optimization (PSO) to solve a 3-objective optimization problem for an antenna array design consisting of two L-shaped folded monopole antennas (LFMAs) operating in the IEEE 802.11 b/g WLAN band (2400-2484 MHz). The method incorporates a simple concept whereby three sub-objective functions, representing the reflection coefficient S 11, the mutual coupling S 21, and the entire antenna volume of the LFMA array, are minimized one by one in the PSO to obtain an optimal LFMA array configuration that provides reduced size and higher antenna performance. The advantages of the proposed method, both in terms of deriving appropriate optimization results and reducing computational cost for the optimization problem, are demonstrated by comparing its performance with that of a conventional weighted aggregation (CWA) method, and a method using the concept of Pareto dominance (PD). The optimal LFMA array configuration obtained by the proposed method has a 10% resonant bandwidth ( S 11 ≤ -10 dB for 2.32-2.57 GHz), S 21 reduced to less than -15 dB in this band, and an antenna volume that was markedly decreased, to 28.5% of that of the original design.