HYBRID PIFA-PATCH ANTENNA OPTIMIZED BY EVOLUTIONARY PROGRAMMING

In this paper we study the optimization process of a novel hybrid antenna, formed by a Planar Inverted-F Antenna (PIFA) and a coplanar patch in the same structure, and intended to be used in mobile communications and WIFI applications simultaneously. This hybrid device has been recently proposed and characterized in the literature, and it has been shown that it allows a bandwidth of 850 MHz (49%) in the lower band and 630 MHz (11.25%) in the upper band. In spite of these good performance results, the fine tuning of the joint PIFA-patch parameters in the hybrid antenna is a hard task, not easy to automatize. In this paper we propose the use of an Evolutionary Programming (EP) approach, an algorithm of the Evolutionary Computation family, which has been shown to be very effective in continuous optimization problems. We use a real encoding of the antennaʹs parameters and the CST Microwave Studio simulator to obtain the performance of the antenna. The simulator is therefore incorporated to the EP algorithm as a part of the antennaʹs evaluation process. We will show that the EP is able to obtain very good sets of parameters in terms of the designer necessities, usually a larger bandwidth at the design frequencies. In this case, the bandwidth of the EP optimized antenna results in 980 MHz (55%) for the lower band and 870 MHz (17%) for the upper band.