Bandwidth Optimization of Spline-Based Planar Sensor Using GA, PSO, and CMA-ES for EMC Testing and Wireless Communications

The expansion of communication technology and the increasing usage of the frequency spectrum drive the need for compatible device testing. Wideband antennas play a crucial role in supporting modern communication systems and applications, including those used as the sensors in electromagnetic compatibility (EMC) testing. Optimization techniques, such as genetic algorithm (GA), particle swarm optimization (PSO), and covariance matrix adaptation–evolution strategy (CMA-ES), are widely applied to enhance the bandwidth of electromagnetic devices. However, most studies focus on individual algorithms or limited comparisons, resulting in a lack of systematic evaluation within a unified framework. This paper fills that gap by directly comparing GA, PSO, and CMA-ES on the same planar sensor design, assessing their effectiveness in achieving the widest bandwidth. The planar sensor had a basic spline-based configuration using quadratic Bezier equation. A performance comparison based on a simulation showed that the planar sensor configuration with the best bandwidth was 17.77 GHz, spanning a frequency range from 2.23 GHz to 20 GHz, which was limited by the highest observation frequency of the available measuring instrument. Furthermore, verification of the realized planar sensor showed that the bandwidth reached 17.86 GHz, from 2.14 GHz to 20 GHz, with a geometric bandwidth of 273%.