Impact of Varying Radio Power Density on Wireless Communications of RF Energy Harvesting Systems

Abstract

Through field experiments, we observed a varying instantaneous charging capacity of the energy buffer with respect to the dynamic intensity of the incident RF signal in the RF energy harvesting system (RF-EHS). The dependency of charging capacity on the incident power of RF signal challenges existing RF energy harvesting models that assume constant charging capacity. In order to accurately describe the energy harvesting process in the real system, we propose a new energy clamp model. The new model reveals that RF intensity higher than the sensitivity of the harvester circuit cannot always guarantee successful energy reception, especially when the energy level of energy buffer is high while the intensity of the incident power is relatively weak. In order to improve the efficiencies of energy harvest and energy utilization in an RF-EHS, we develop new offline (i.e., non-causal) optimal and online (i.e., causal) suboptimal data transmission strategies based on the energy clamp model. Simulation results show that the new strategy can considerably improve the throughput after taking into account the varying instantaneous charging capacity caused by the dynamic RF power density in the air. Index Terms-RF energy harvesting system, varying RF power density, energy clamp model, transmission strategy * The 1.2 dB standard deviation in signal strength seems stable from communication point of view, which, however, is strong enough to cause 17.9% charging voltage dynamics in the RF energy harvesting system. The two strongest bands on 887.5 MHz and 739 MHz are the downlink signal from LTE base stations that are about 280 feet away. The eNB IDs of the two LTE base stations are 204758 and 204558, respectively [26]. The 1952.5 MHz and 2115 MHz bands are from other distant LTE base stations.

Secrecy Performance Maximization for Underlay CR Networks with an Energy Harvesting Jammer

“…We target to maximize the secrecy rate in (10), subject to the time constraint in (1), the transmit power constraints in ( 5) and (7), and the energy causality constraints in ( 4) and (6). The decision variables include the time allocation θ 1 and θ 2 , the transmit power allocation P SU at the SU, and the transmit power allocation P SJ at the SJ.…”

“…On the other hand, the explosion of wireless services and applications has also led to energy deficiency in the future wireless communications. Radio-frequency (RF) energy-harvesting technology is a good candidate solution for charging the low-power wireless devices [6][7][8][9][10], which can conquer the uncontrollability and intermittency of wireless devices powered by the renewable energy sources, such as wind, solar and vibrational energy. The harvest-then-transmit (HTT) protocol is proposed in [11] as one of the most common working mode of RF energy-harvesting technology, where the users first harvest energy from the RF energy source in the en-ergy transfer (ET) phase and then use the captured energy to transmit information to the destination in the information transfer (IT) phase.…”

“…Optimal time allocation and transmit power allocation for (P1) Input: P S , I Output: R sec according to(10); Initialize the DC programming iterations k to be 1 ; the increase of R sec is larger than M do the change of µ is larger than e do 10 Obtain P * SU using (23); θ 2 − ∆ ; 21 end…”

Optimal resource allocation method for energy harvesting based underlay Cognitive Radio networks

“…The EH efficiency is very low, but it is still suitable for low-power communication equipment. The source of RF energy includes dedicated RF source, ambient RF energy and self-power, among which dedicated RF energy has properties of continuity and stability and is more practical compared with the others [ 10 , 11 ]. In [ 12 ], a RF EH-CR sensor network is proposed, which can utilize the strong signals over the occupied licensed channels for EH.…”

A Dual-Polarized Omnidirectional Rectenna Array for RF Energy Harvesting

“…The energy consumption of these devices has attracted widespread attention. REH has become a suitable choice for these low-power electronics [ 5 , 6 ]. Compared with other types of energy in the ambience, such as solar energy, wind energy, etc., the ubiquitous ambient RF energy has its unique advantages [ 7 ].…”