Rectenna design optimized by binary genetic algorithm for hybrid energy harvesting applications across 5G sub-6 GHz band

Abstract

This paper presents a novel rectenna design for hybrid energy harvesting, optimized using a binary genetic algorithm (BGA) with binary coding to improve geometry, impedance matching, and radiation efficiency. The fabricated rectenna achieves reflection coefficients below −40 dB at 2.45 and 5.8 GHz, demonstrating excellent impedance matching. A commercial rectifier (Powercast P21XXCSR-EVB), employing a voltage doubler topology and Schottky diodes (Skyworks SMS7630 and Avago HSMS 285B), is integrated for RF-to-DC conversion. Peak efficiencies of 90% at 2.45 GHz and 52% at 5.8 GHz are recorded at 11 dBm input power, while efficiencies above 80% and 50%, respectively, are maintained at 0 dBm. The rectifier also exhibits wide impedance bandwidths, with reflection coefficients of − 23 dB and −18 dB at the respective frequencies. Outdoor testing yields DC output voltages of 92.6 mV (2.45 GHz) and 64 mV (5.8 GHz). The system's efficiency and adaptability under variable conditions make it ideal for low-power applications such as wireless sensor networks, Internet of Things devices, and remote monitoring. Its robust performance across environments highlights its potential for autonomous energy harvesting in 5G and sub-6 GHz networks.