Design Parameter Optimization of Ultra-wideband Antenna Using Quantum-behaved Particle Swarm Optimization

The Ultra-Wideband (UWB) antenna, as core device in high-speed wireless communication, is widely applied to cell phones, wireless internet, internet of things, and almost all kinds of hand-held and wearable mobile communication equipments. Faced with a plethora of constraints, such as compact size, low power consumption, high bandwidth, and cost-effective manufacture, etc., the design of UWB antenna is essentially a complicated problem of multi-objective optimization. As a variant of the family of particle swarm optimization (PSO), the quantum-behaved particle swarm optimization (QPSO) adopts the potential well of quantum mechanics to mimic the movement of particles and the length of potential well as the measurement of the particle swarm diversity, and the diversity-controlling strategy is adopted to help particle swarm jump out of the local space where the fitness stagnates so as to improve global optimization. The aforementioned properties make QPSO a potential method in the design parameter optimization of UWB antenna. Nevertheless, up to now, there are very few such reports and QPSO haven't gotten enough attention in antenna design. In this report, design parameters of a CPW-fed elliptic UWB antenna are optimized using QPSO combined with the electromagnetic field solver and different diversity-controlling strategies are devised and employed to improve global optimization. The simulation results demonstrate the ratio bandwidth is broadened by 54% while the overall size remains the same. Besides, the PSO with dynamic inertial coefficient is also applied to the same antenna design. Comparison shows the QPSO with diversity-controlling strategy achieves better design results for this UWB antenna meanwhile converges much faster.