Comparative Study of Optimization Algorithms on the Design of Broadband Antennas

Abstract

Broadband antennas find many applications in modern communication systems, such as Wi-Fi, 5G, and SatCom. Multiple competing optimization methods are available for the application to antenna design, while it would be preferable to know in advance if any method is superior. Here, an application of the cross-entropy method, along with particle swarm optimization and covariance matrix adaptation evolutionary strategy, to the design of broadband antennas is presented. The first example is an aperture-coupled microstrip patch antenna that has 9.5 dBi peak directivity and 53% bandwidth after optimization. It is then used as a feed in a high-gain broadband resonant cavity antenna. Using an all-dielectric superstrate with a transverse permittivity gradient, a compact thin resonant cavity antenna with a peak directivity of 19 dBi and 40% 3-dB bandwidth was designed. A comparative analysis of the cross-entropy method, particle swarm optimization, and covariance matrix adaptation evolutionary strategy applied to these two problems was carried out to provide the basis for further optimization of antennas in radio frequency and microwave frequency bands. We found that although all three methods reached a similar solution, the cross-entropy method has a speed advantage. It improves our ability to optimize existing designs and has wider applicability beyond antenna engineering.