Adaptive Switching for Efficient Energy Harvesting in Energy Constraint IoT Devices

In recent years, Internet of Things (IoT) has attained considerable attention by the research community. IoT is an interconnected network of smart devices capable of sensing and communicating ubiquitously. Cognitive radio networks (CRN's) are recommended to increase capacity for next generation wireless networks for IoT applications. To prolong battery life of these unattended smart devices, energy harvesting is an obvious solution. RF Wireless energy harvesting (RFWEH), in which freely available ambient energy from RF sources is utilized to increase battery life, has gained much attention recently. In this paper, we propose a hybrid source switch-based RFWEH technique which adaptively switches between high-power RF sources, in contrast to previous works, in which low power sources are preferred. We show that high-power RF sources, such as TV and radio, are preferred over low power sources such as cell phones, Wi-Fi etc. Our simulation results show that RFWEH from radio antennas outperform RFWEH from TV antennas even though the former operates at a much lower transmit power. Furthermore, switch-based RFWEH gives better performance compared with single source RFWEH.