Knowledge based neural network modeling of dual band PIFA

In this paper, a more compact dual band planar inverted-F antenna (PIFA) has been proposed. Dual band is achieved by inserting slots on the top radiating patch. The size of the patch is 15 × 12 mm
²
and finite ground plane size is 44 × 40 mm
²
which can easily be integrated inside the mobile phone. The proposed antenna is simulated using CST software and simulated S11, radiation patterns are presented. The broadside radiation characteristics are achieved at both the frequency bands. Finally surface current distributions are analyzed and parametric studies of the slots dimensions are done. Two degrees of freedom is achieved to tune both the frequencies. By parametric studies of the slot parameters, it can be used for DCS, PCS, UMTS, Bluetooth and additional band (4-5 GHz) applications. Finally, Knowledge based neural network (KBNN) is used to model the resonant frequencies of the compact dual-band PIFA. The KBNN results are compared with the CST simulation results and are found to be in good accord.