Triple-band Inverted-F Antenna Using QR-OBL TLBO Algorithm for RF Energy Harvesting Applications

Radio Frequency Energy Harvesting (RF EH) is one of the popular emerging techniques in wireless sensor networks that can sufficiently supply low power electronic circuits. With the evolution of Internet of Things (IoT) technology, which exhibits an exponentially positive growth rate over the last years, RF EH can play a primary role in the next-generation wireless networks. In this paper, we apply an optimization technique by utilizing the Quasi-Reflected (QR) variant of Opposition Based Learning (OBL) technique in Teaching Learning Based Optimization (TLBO) algorithm to design a triple-band Inverted-F antenna (IFA) for RF energy harvesting applications. The proposed antenna is operating in the cellular communication frequency bands of EGSM-900 and GSM-1800, as well as at the Long Term Evolution (LTE) telecommunication networks frequency band of LTE-2600. Simulation results demonstrate that the designed antenna has features of operation which make it suitable for RF EH applications.