Radio Frequency Energy Transfer Research Articles

UAV-Enabled Mobile RAN and RF-Energy Transfer Protocol for Enabling Sustainable IoT in Energy-Constrained Networks

UAV-Enabled Mobile RAN and RF-Energy Transfer Protocol for Enabling Sustainable IoT in Energy-Constrained Networks

Transcutaneous Pulsed RF Energy Transfer Mitigates Tissue Heating in High Power Demand Implanted Device Applications: In Vivo and In Silico Models Results.

This article presents the development of a power loss emulation (PLE) system device to study and find ways of mitigating skin tissue heating effects in transcutaneous energy transmission systems (TETS) for existing and next generation left ventricular assist devices (LVADs). Skin thermal profile measurements were made using the PLE system prototype and also separately with a TETS in a porcine model. Subsequent data analysis and separate computer modelling studies permit understanding of the contribution of tissue blood perfusion towards cooling of the subcutaneous tissue around the electromagnetic coupling area. A 2-channel PLE system prototype and a 2-channel TETS prototype were implemented for this study. The heating effects resulting from power transmission inefficiency were investigated under varying conditions of power delivery levels for an implanted device. In the part of the study using the PLE setup, the implanted heating element was placed subcutaneously 6–8 mm below the body surface of in vivo porcine model skin. Two operating modes of transmission coupling power losses were emulated: (a) conventional continuous transmission, and (b) using our proposed pulsed transmission waveform protocols. Experimental skin tissue thermal profiles were studied for various levels of LVAD power. The heating coefficient was estimated from the porcine model measurements (an in vivo living model and a euthanised cadaver model without blood circulation at the end of the experiment). An in silico model to support data interpretation provided reliable experimental and numerical methods for effective wireless transdermal LVAD energization advanced solutions. In the separate second part of the study conducted with a separate set of pigs, a two-channel inductively coupled RF driving system implemented wireless power transfer (WPT) to a resistive LVAD model (50 Ω) to explore continuous versus pulsed RF transmission modes. The RF-transmission pulse duration ranged from 30 ms to 480 ms, and the idle time (no-transmission) from 5 s to 120 s. The results revealed that blood perfusion plays an important cooling role in reducing thermal tissue damage from TETS applications. In addition, the results analysis of the in vivo, cadaver (R1Sp2) model, and in silico studies confirmed that the tissue heating effect was significantly lower in the living model versus the cadaver model due to the presence of blood perfusion cooling effects.

Experimental Study on the Efficiency of RF Energy Transfer System

This paper presents a 915 MHz radio frequency (RF) wireless energy transfer system which contains RF energy transmitters and RF energy harvesting nodes. Firstly, Advanced Design System (ADS) is used to design and optimize the monopole voltage doubler rectifier circuit. Secondly, an energy harvesting node is designed by a commercial RF/DC rectifier and a 915 MHz antenna. Finally, the RF energy transfer experiment between RF energy transmitter and RF energy harvesting node is demonstrated. Experimental data fits well with theoretical analysis and the harvested energy show a non-linear relationship with the distance and angle between the receiving node antenna and the transmitter antenna. The experimental data is valuable for designing RF-powered nodes and optimizing the movement trajectory of the mobile RF energy transmitter, such as an unmanned aerial vehicle (UAV).

Beamforming-Based Mitigation of Hovering Inaccuracy in UAV-Aided RFET

Hovering inaccuracy of unmanned aerial vehicle (UAV) degrades the performance of UAV-aided radio frequency energy transfer (RFET). Such inaccuracy arises due to positioning error and rotational motion of UAV, which lead to localization mismatch (LM) and orientation mismatch (OM). In this paper, antenna array beam steering based UAV hovering inaccuracy mitigation strategy is presented. The antenna beam does not accurately point towards the field sensor node due to rotational motion of the UAV along with pitch, roll, and yaw, which leads to deviation in the elevation angle. An analytical framework is developed to model this deviation, and its variation is estimated using the data collected through an experimental setup. Closed-form expressions of received power at the field node are obtained for the four cases arising from LM and OM. An optimization problem to estimate the optimal system parameters (transmit power, UAV hovering altitude, and antenna steering parameter) is formulated. The problem is proven to be nonconvex. Therefore, an algorithm is proposed to solve this problem. Simulation results demonstrate that the proposed framework significantly mitigates the hovering inaccuracy; compared to reported state-of-the-art the same performance can be achieved with substantially less transmit power.

FLOC: Hesitant Fuzzy Linguistic Term Set Analysis in Energy Harvesting Opportunistic Clustering Using Relative Thermal Entropy and RF Energy Transfer

Limited energy resources and sensor nodes’ adaptability with the surrounding environment play a significant role in the sustainable Wireless Sensor Networks. This paper proposes a novel, dynamic, selforganizing opportunistic clustering using Hesitant Fuzzy Linguistic Term Analysis- based Multi-Criteria Decision Modeling methodology in order to overcome the CH decision-making problems and network lifetime bottlenecks. The asynchronous sleep/awake cycle strategy could be exploited to make an opportunistic connection between sensor nodes using opportunistic connection random graph. Every node in the network observe the node gain degree, energy welfare, relative thermal entropy, link connectivity, expected optimal hop, link quality factor etc. to form the criteria for Hesitant Fuzzy Linguistic Term Set. It makes the node to evaluate its current state and make the decision about the required action (‘CH’, ‘CM’ or ‘relay’). Our proposed scheme leads to an improvement in network lifetime, packet delivery ratio and overall energy consumption against existing benchmarks.

WiFED Mobile: WiFi Friendly Energy Delivery With Mobile Distributed Beamforming

Wireless RF energy transfer for indoor sensors is an emerging paradigm ensuring continuous operation without battery limitations. However, high power radiation within ISM band interferes with packet reception for existing WiFi devices. The paper proposes the first effort in merging RF energy transfer within a standards compliant 802.11 protocol, realizing practical and WiFi-friendly Energy Delivery with Mobile Transmitters (WiFED Mobile). WiFED Mobile architecture is composed of a centralized controller coordinating the actions of multiple energy transmitters (ETs), and deployed sensors that periodically requires charging. The paper first describes 802.11 supported protocol features that can be exploited by sensors to request energy and for ETs to participate in energy transfer. Second, it devises a controller-driven bipartite matching algorithm, assigning appropriate number of ETs to sensors for efficient energy delivery. Thirdly, it detects outlier sensors (OS), which have limited power reception from static ETs and utilizes mobile ETs (METs) to satisfy their charging cycles. The proposed in-band and protocol supported coexistence in WiFED Mobile is validated via simulations and partly in a software defined radio testbed, showing that METs reduce latency by 42% and improve throughput by 83% in scenarios where using only static ETs fails to satisfy charging cycles of OS.

Optimal UAV-Aided RFET System Design in Presence of Hovering Inaccuracy

In this paper, performance of unmanned aerial vehicle (UAV)-aided RF energy transfer (RFET) in presence of hovering inaccuracy is investigated. Hovering inaccuracy of UAV comprises of two types of mismatches: Localization mismatch (LM) and Orientation mismatch (OM) . Thus, a total of four combinations arise. Their impact on received power at ground deployed sensor node is characterized. For this purpose, a generalized radiation pattern of UAV-mounted transmitter antenna is considered. A closed-form expression of received power at the sensor node is obtained for each of these four cases. An optimization problem is formulated with the objective of optimizing the system parameters, such as transmit power, hovering altitude, and antenna exponent. This problem contains mixed nature of variables, i.e., continuous as well as discrete. To solve this problem, an algorithm, called Hovering Inaccuracy-aware Optimal Charging System Design (HI-OCSD) , is proposed to find the optimal system parameters. Through system simulations it is demonstrated that, hovering inaccuracy has notable impact on the performance, as received power at the sensor node reduces significantly in presence of hovering inaccuracy compared to ideal scenario. The effect of LM is more severe than that of OM . Further, a scenario with different level of hovering inaccuracy accounting for different deployment scenarios is considered, and the optimal system parameters are also evaluated. This study reveals that, UAV needs to hover at a relatively higher altitude to overcome the severity of hovering inaccuracy.

UAV-Assisted RFET: A Novel Framework for Sustainable WSN

Limited battery capacity is one of the major hurdles towards perpetual operation of wireless sensor networks. In this paper, a novel framework for charging the sensor nodes using unmanned aerial vehicle (UAV)-assisted radio frequency energy transfer (RFET) is presented. First, the notion of RFET zone is conceptualized and a closed-form expression for RFET zone radius is obtained. The sensor nodes located inside this zone can harvest energy from the transmitter mounted on UAV. The effective power harvested at the sensor node situated at different spatial locations is evaluated by considering the impact of shadowing statistics of path loss and non-linear RF-to-direct current conversion efficiency. With these findings on sensor nodes deployed in a given area, an optimization problem is formulated with the objective of minimizing the total time in a charging cycle, which is comprised of travel time and charging time. This problem is decomposed into two sub-problems and they are solved individually in sequential steps. The optimal solution of the first sub-problem, which provides the sequence of charging having minimum travel time, is a Traveling Salesman Problem (TSP). In the second sub-problem, the presence of Lambert function makes it analytically intractable, and hence, approximations are presented to solve this. Subsequently, to account for the health parameters of the sensor nodes in estimating the charging cycle, three variants of order of charging, namely, Voltage-aware Charging Sequence , Operational Time-aware Charging Sequence , and Iterative Charging Sequence , are proposed. Through system simulations it is demonstrated that, in a generalized setting, the charging sequence offered by the proposed variants perform increasingly better in comparison to the state-of-the-art TSP approach.

Impact of Hovering Inaccuracy on UAV-Aided RFET

In this letter, the impact of hovering inaccuracy on the performance of unmanned aerial vehicle (UAV)-aided RF energy transfer (RFET) is investigated. Hovering inaccuracy is measured by localization and orientation mismatch of UAV while it hovers above a sensor of interest. An analytical framework is presented that captures these mismatches, and its impact on the performance of UAV-aided RFET is studied. To evaluate the performance, a metric called mismatch index is defined as the ratio of loss in harvested power due to mismatch and harvested power without mismatch. A closed-form expression of the distribution of mismatch index is obtained. A UAV-based experimental setup is developed to collect the data of hovering inaccuracy parameters, and the performance is investigated for three antenna types with different radiation patterns. It is observed that, the optimal deployment height of UAV increases as the antenna becomes more directional.

Unintentional RF Energy Transfer During Tonsillectomy: An In Vitro Investigation

One-third of tonsillectomy patients experience post-operative taste disturbances (dysgeusia), yet the underlying cause is unknown. We hypothesize that unwanted radio-frequency (RF) energy couples to the metal-based mouth retractor during tonsillectomy and could be a possible cause of dysgeusia. To validate our hypothesis, in vitro studies are performed in a ground beef phantom with sensors measuring, first, the unwanted current coupled to the mouth retractor and, second, the unwanted temperature rise in the tissues that surround the retractor. The simulated surgery was performed using two separate surgical techniques: monopolar electrosurgery and coblation. Results indicate that unintentional RF energy transfer is indeed a real issue. During electrosurgery, peak-to-peak unwanted currents vary from 80.53 to 181.48 mA for typical power levels ranging from 10 to 30 W. Tissue temperature unintentionally increases by 1.3 °C and 1.8 °C, respectively. Coblation indicates smaller coupling effects, with peak-to-peak currents on the mouth retractor capped at 12.33 mA for a typical 7 W setting. Concurrently, tissue temperature is reduced by 0.73 °C, as attributed to the saline solution inherent to coblation. As the first of its kind, this study illuminates possible causes of post-tonsillectomy dysgeusia and intends to trigger future studies. The ultimate goal is safe and complication-free tonsillectomies.

Joint Network Admission Control, Mode Assignment, and Power Allocation in Energy Harvesting Aided D2D Communication

Green communication with sustainable energy is being considered for 5G cellular network and Internet of Things (IoT) mainly with focus on energy harvesting (EH) to prolong network lifetime. Moreover, device-to-device (D2D) communication on shared channels is also considered as a promising technology to achieve high data rates, ultralow latency communication, and high spectral efficiency. In this paper, we investigated resource allocation in EH-aided D2D communication underlying 5G cellular along with enabling IoT services. The objective is to maximize throughput of the network subject to the joint constraints on user performance, number of admitted users for equity and fair usage, mode assignment (cellular or D2D) as per available energy, and transmit power allocation along with EH techniques, which results in a mixed integer nonlinear programming problem. We have proposed a low complexity and efficient algorithm, adaptive resource allocation and energy sentient network (ARA-ESN) using branch–cut, branch–bound, and mesh adaptive direct search (MADs) solutions, where cellular or D2D communication is based on available energy and user performance criteria along with EH through ambient energy and radio frequency (RF) energy transfer techniques. We have applied the outer approximation based linearization technique that guarantees the convergence to the optimal solution. The results show that ARA-ESN branch–cut outperforms ARA-ESN branch–bound and ARA-ESN MADs. Moreover, we have also observed that ambient harvesting increases performance of network due to better acquisition of energy as compared to RF energy transfer.

Optimal Resource Allocation for Multiuser Internet of Things Network With Single Wireless-Powered Relay

Wireless powered communication (WPC), where the required energy for communication is obtained via radio frequency (RF) energy harvesting, is a promising technology for the upcoming self-sustainable Internet of Things (IoT) networks. In this paper, a multiuser IoT network is considered, where an energy-constrained relay assists the information transmission of a number of IoT devices to the access point (AP) using WPC. In particular, the relay acquires the energy needed for information forwarding from the RF energy transfer of the AP, which serves as a dedicated energy transmitter for the relay. The objective is to maximize the total network throughput by jointly optimizing the wireless energy transfer (WET) duration and the relay’s energy expenditure in each time slot, subject to the energy causality constraint, for both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols. We show that the optimization problems for both the AF- and DF-based systems are convex and thus can be solved using convex optimization techniques. Our analysis shows that the solution of the sum-throughput maximization problems depends on the scheduling order of the IoT devices and the optimal solution is derived for different ordering scenarios. Finally, numerical simulations are presented to corroborate our analysis.

Modelling and Performance Analysis of Wireless LAN Enabled by RF Energy Transfer

RF signals can be relied upon for transferring energy to those power-thirsty wireless devices. Thanks to the broadcast nature of wireless channels, dedicated RF signals for delivering information to specific devices can also be received by others for energy harvesting. Coordinating the conventional wireless information transfer and the wireless energy transfer (WET) requires a systematic design in all OSI layers, which yields data and energy integrated communication networks. Based on the classic carrier-sense-multiple-access with collision avoidance protocol, we originally propose a distributed multiple access protocol in the medium access control (MAC) layer for the indoor wireless-local-area-network (WLAN) powered by RF signal-based WET. The operation of our proposed protocol in the WET powered indoor WLAN is modeled by a multi-dimensional Markov chain, which is exploited for deriving the closed-form throughput of the WLAN studied. The simulation results demonstrate the accuracy of our theoretical analysis, which pave the way for the future optimization design in the MAC layer of WET powered indoor WLAN.

Path Loss Model for UAV-Assisted RFET

In this letter, we develop channel models for unmanned aerial vehicle-aided air-to-ground (AtG) radio frequency energy transfer (RFET). AtG path loss plays a key role in RFET-based recharging of field nodes. Representative field environments consist of different types of built-up areas, namely, suburban, urban, dense urban, urban high-rise, and rural agriculture deployment scenarios. For emulating the built-up areas, ITU-R recommendations are considered, whereas for rural agricultural field deployment scenario, dynamics of vegetation growth with time is considered. Accuracy of the proposed path loss models are validated by conducting real AtG radio frequency transmission experiments in emulated suburban and agricultural fields.

RF Energy Harvesting and Transfer for Spectrum Sharing Cellular IoT Communications in 5G Systems

This paper proposes an energy and spectrum efficient IoT network for 5G systems where spectrum is shared with the cellular system for spectrum efficiency and energy harvesting and energy transfer are utilized for energy efficiency. The IoT network, which consists of sensor nodes and a cluster head with a reliable energy source, reuses part of the cellular band whenever the cellular network does not utilize it. The cluster head performs spectrum sensing, random scheduling of the sensor nodes, and schedules some idle time for energy transfer. The sensor nodes harvest RF energy from the cellular traffic and the transferred energy from the cluster head. Provided the sensor nodes have sufficient energy, they transmit collected sensory data when scheduled. The inter-play between the cellular and IoT network introduces trade-offs between the spectrum availability, energy availability, information, and energy transfer. This paper shows that for the same cellular traffic level, as the number of sensor nodes in the network increases, the IoT network utilization increases resulting in a multi-user gain thanks to the broadcast nature of the energy transfer. The results offer insights into different operational regimes and exposes what type of IoT applications may be feasible with such networks.

RF Energy Transfer Channel Models for Sustainable IoT

Self-sustainability of wireless nodes in Internet-of-Things applications can be realized with the help of controlled radio frequency energy transfer (RF-ET). However, due to significant energy loss in wireless dissipation, there is a need for novel schemes to improve the end-to-end RF-ET efficiency. In this paper, first we propose a new channel model for accurately characterizing the harvested dc power at the receiver. This model incorporates the effects of nonline of sight (NLOS) component along with the other factors, such as radiation pattern of transmit and receive antennas, losses associated with different polarization of transmitting field, and efficiency of power harvester circuit. Accuracy of the model is verified via experimental studies in an anechoic chamber (a controlled environment). Supported by experiments in controlled environment, we also formulate an optimization problem by accounting for the effect of NLOS component to maximize the RF-ET efficiency, which cannot be captured by the Friis formula. To solve this nonconvex problem, we present a computationally efficient golden section-based iterative algorithm. Finally, through extensive RF-ET measurements in different practical field environments we obtain the statistical parameters for Rician fading as well as path loss factor associated with shadow fading model, which also asserts the fact that Rayleigh fading is not well suited for RF-ET due to presence of a strong line of sight component.

RF Energy Harvesting and Transfer in Cognitive Radio Sensor Networks: Opportunities and Challenges

By enabling sensor nodes to opportunistically access licensed channels, CRSN can provide a spectrum-efficient networking solution in the era of the Internet of Things. On the other hand, it also consumes extra energy for spectrum sensing and switching. This is a double-edged sword posing a dilemma between spectrum efficiency and energy efficiency. Recent advances in RF energy harvesting and transfer promote RF-powered CRSN in providing a promising way to address this challenge. In RF-powered CRSNs, sensor nodes can dynamically access the vacant licensed channels for interference-free data transmission and can also utilize the strong signals over the occupied licensed channels for energy harvesting. In this article, we investigate RF energy harvesting and transfer in CRSNs. We first introduce the architecture and advantages of RF-powered CRSN, typical applications, as well as the key challenges arising from applying RF energy harvesting and transfer into CRSN. We then propose a resource allocation framework to demonstrate how to jointly control the dynamic channel access and energy management to optimize network utility while guaranteeing network stability and sustainability. Some future directions are finally envisioned for further research.

Improved Energy Efficiency of Massive MIMO-OFDM in Battery-Limited IoT Networks

We investigate the feasibility of improving the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems applied to a battery-limited Internet of Things (IoT) networks. Improving EE is especially important for battery limited IoT devices. We observe the uplink and downlink aspects of massive MIMO-OFDM-based IoT networks and categorize some of the effective methods to consider. As uplink aspect, we consider the uplink reference signal (RS) power control. Reducing uplink RS power could induce the battery saving of IoT devices but could cause an increase in channel estimation error. As downlink aspect, we consider the peak-to-average power ratio reduction of the OFDM signal and downlink transmitter power control. These techniques are well-known as effective EE improvement methods, but there is little work showing the actual EE gain in system perspective. In addition, we also consider the utilization of radio frequency energy transfer using unmanned aerial vehicles to extend the operating time of battery-limited IoT devices. We derive the theoretical closed-form approximations of spectral efficiency and EE when applying these methods and provide EE gains for various scenarios. Numerical results show that the theoretical analysis is in good agreement with the simulation results and thus can be used as useful tools to improve EE.

Transmission Line and Electromagnetic Model of the Tubular Wave Coupler

This paper investigates the injection of RF energy onto wiring harness using a tubular wave coupler (TWC). In particular, a transmission line (TL) model of a commercial TWC mounted in the calibration fixture provided by the manufacturer is developed. The proposed model of the calibration setup provides accurate prediction of the measured insertion loss up to 2 GHz. Measurement data and outcomes of three-dimensional electromagnetic simulation of the TWC are used to obtain estimates of some of the involved model parameters, whose direct evaluation is not possible due to partial knowledge of the geometrical/electrical characteristics on the one side, and nonuniform distribution of current and voltage on the TWC cross section on the other. The proposed TL model is used to explain the fundamental phenomena responsible for RF-energy transfer through the TWC. Particularly, it is shown that, differently from bulk current injection probes where inductive coupling is the dominant phenomenon, injection through the TWC involves both inductive and capacitive coupling. This determines a certain amount of directivity of the injection device, and is expected to play a role in RF injection onto complex cable bundles.

Hybrid Power Combining Rectenna Array for Wide Incident Angle Coverage in RF Energy Transfer

This paper discusses a new design approach that uses hybrid power combining rectenna array in radio frequency (RF) energy transfer systems to receive more energy in a wide incident angle range. A beam-forming matrix and a dc power management network (PMN) are introduced to the hybrid power combining. The normalized dc output power of the proposed hybrid power combining array is compared to the conventional power combining methods with regard to the incident wave angle, and the average received dc power is also calculated and compared. To experimentally verify the proposed hybrid combining array performance, four suspended patch antennas are attached to RF energy receiving architecture. A $4 \times 4$ Butler matrix and quadrature hybrids are used for the beam-forming matrix in a hybrid power combining rectenna array. A reconfigurable voltage doubler rectifier with a dc PMN is used to convert RF energy to dc energy and delivers proper voltage to the load. The measured results of each component are presented. Moreover, an experimental verification using fabricated components for RF energy transfer is presented and the measured received dc output power of conventional and proposed structures is presented and compared.