Integrated Data and Energy Communication Network: A Comprehensive Survey

OAPA In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice

RF Systems Design for Simultaneous Wireless Information and Power Transfer (SWIPT) in Automation and Transportation

This work presents some recent solutions that exploit the wireless power transfer (WPT) technology for energizing moving vehicles and machinery tools. Such technology is currently experiencing unprecedented interests in non-traditional RF/microwave sectors fields, such the industrial automation and the railway transportation safety. Near-field electromagnetic coupling solutions are presented showing that, in order to obtain efficient performances for broad ranges of operating conditions, the nonlinear electromagnetic co-design of the entire WPT system, from the energy source to the receiver load, needs to be carried out. This technology can be combined with wireless data transfer, thus realizing integrated systems able to simultaneously control the energy transfer and the transmission of data. The adopted operating frequencies are in the MHz range, which is only recently considered for this kind of applications. In particular this work focuses on three different systems: the first one demonstrates the constant powering of “on the move” industrial charts at 6.78 MHz, regardless of the relative position of the transmitter and the receiver sub-systems; the second one presents a novel design of a balise transportation system adopting a high efficiency GaN-based transmitter designed to keep its performance over a wide range of loading conditions; the last one consists of the simultaneous wireless power and data transfer, to a rotating machinery tool, automatically controlled by the powering system based on the coexistence of frequency-diverse inductive and capacitive couplings

Energy-Efficient Circuit Designs for Miniaturized Internet of Things and Wireless Neural Recording

Internet of Things (IoT) have become omnipresent over various territories including healthcare, smart building, agriculture, and environmental and industrial monitoring. Today, IoT are getting miniaturized, but at the same time, they are becoming more intelligent along with the explosive growth of machine learning. Not only do IoT sense and collect data and communicate, but they also edge-compute and extract useful information within the small form factor. A main challenge of such miniaturized and intelligent IoT is to operate continuously for long lifetime within its low battery capacity. Energy efficiency of circuits and systems is key to addressing this challenge. This dissertation presents two different energy-efficient circuit designs: a 224pW 260ppm/°C gate-leakage-based timer for wireless sensor nodes (WSNs) for the IoT and an energy-efficient all analog machine learning accelerator with 1.2 µJ/inference of energy consumption for the CIFAR-10 and SVHN datasets. Wireless neural interface is another area that demands miniaturized and energy-efficient circuits and systems for safe long-term monitoring of brain activity. Historically, implantable systems have used wires for data communication and power, increasing risks of tissue damage. Therefore, it has been a long-standing goal to distribute sub-mm-scale true floating and wireless implants throughout the brain and to record single-neuron-level activities. This dissertation presents a 0.19×0.17mm2 0.74µW wireless neural recording IC with near-infrared (NIR) power and data telemetry and a 0.19×0.28mm2 0.57µW light tolerant wireless neural recording IC.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169712/1/jongyup_1.pd

Radio frequency energy harvesting for autonomous systems

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyRadio Frequency Energy Harvesting (RFEH) is a technology which enables wireless power delivery to multiple devices from a single energy source. The main components of this technology are the antenna and the rectifying circuitry that converts the RF signal into DC power. The devices which are using Radio Frequency (RF) power may be integrated into Wireless Sensor Networks (WSN), Radio Frequency Identification (RFID), biomedical implants, Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), smart meters, telemetry systems and may even be used to charge mobile phones. Aside from autonomous systems such as WSNs and RFID, the multi-billion portable electronics market – from GSM phones to MP3 players – would be an attractive application for RF energy harvesting if the power requirements are met. To investigate the potential for ambient RFEH, several RF site surveys were conducted around London. Using the results from these surveys, various harvesters were designed and tested for different frequency bands from the RF sources with the highest power density within the Medium Wave (MW), ultra- and super-high (UHF and SHF) frequency spectrum. Prototypes were fabricated and tested for each of the bands and proved that a large urban area around Brookmans park radio centre is suitable location for harvesting ambient RF energy. Although the RFEH offers very good efficiency performance, if a single antenna is considered, the maximum power delivered is generally not enough to power all the elements of an autonomous system. In this thesis we present techniques for optimising the power efficiency of the RFEH device under demanding conditions such as ultra-low power densities, arbitrary polarisation and diverse load impedances. Subsequently, an energy harvesting ferrite rod rectenna is designed to power up a wireless sensor and its transmitter, generating dedicated Medium Wave (MW) signals in an indoor environment. Harvested power management, application scenarios and practical results are also presented

Practical Waveform-to-Energy Harvesting Model and Transmit Waveform Optimization for RF Wireless Power Transfer Systems

The received radio-frequency (RF) power in far-field RF wireless power transfer (WPT)—with or without simultaneous information transfer—is minuscule due to large propagation loss in wireless media. In such scenarios, adapting to the receiver characteristics by transmit waveform optimization is essential for maximizing the harvested direct current (dc) and, thus, the end-to-end efficiency of an RF WPT system. The receiver efficiency in RF WPT is governed by the RF-to-dc efficiency of the rectifier as well as the impedance mismatch at the antenna and load. In this article, we study the receiver efficiency for any fixed load and, subsequently, present a novel rectifier model that relates the average harvested dc power to the distribution, that is, the histogram, of the instantaneous power levels of the RF signal’s envelope over time. The proposed waveform-to-energy harvesting (EH) model enables us to anticipate the average harvested dc power for any waveform, including communication signals as well, given the knowledge of the power-level distribution. Consequently, we conduct rigorous waveform optimization to maximize the average harvested dc power and determine the digital baseband signal at the transmitter that does so, namely prove that a pulsed tone at appropriate frequency is optimal for RF WPT. We present a multiband test-bed for determining the receiver efficiency for any digital baseband waveform. The efficacy of the proposed model is corroborated through experiments as well as simulations, which confirm that it is operational as well as accurate in practice and that single-sine pulses yield higher efficiency than basic multisine waveforms, while a pulsed phase shift keying (PSK) is preferable for simultaneous wireless information and power transfer (SWIPT).Peer reviewe

Towards Battery-Free Internet of Things (IoT) Sensors: Far-Field Wireless Power Transfer and Harmonic Backscattering

RÉSUMÉ Notre vie tend à être plus agréable, plus facile et plus efficace grâce à l'évolution rapide de la technologie de l'Internet des objets (IoT). La clef de voute de cette technologie repose essentiellement sur la quantité de capteurs IoT interconnectés, que l’on est en mesure de déployer dans notre environnement. Malheureusement, l’électronique conventionnelle fonctionnant sur piles ou relié au réseau électrique ne peut pas constituer une solution durable en raison des aspects de coût, de faisabilité et d'impact environnemental. Pendant ce temps, le changement climatique dû à la consommation excessive de combustibles fossiles continue de s'aggraver. Il devient donc urgent de trouver une solution pour l’alimentation électrique des capteurs IoT géographiquement répartis à grande échelle, afin de simultanément soutenir la mise en oeuvre de nombreux capteurs IoT tout en limitant leur poids environnemental. L'énergie radiofréquence (RF) ambiante, qui sert de support à l'information sans fil, est non seulement capitale pour notre société, mais aussi omniprésente dans les zones urbaines et suburbaines. Elle permet de réaliser des communications et des détections sans fil. Cependant, l'énergie RF ambiante est majoritairement « gaspillée » car seule une toute petite partie de la puissance transmise est effectivement reçu ou « consommée » par le destinataire. C'est pourquoi le recyclage de l'énergie RF ambiante est une solution prometteuse pour alimenter les capteurs IoT. Pour certains capteurs IoT consommant une puissance plus élevée, l’apport d'énergie sans fil pourra similairement se faire par des centrales électriques spécialisées, suivant le même schéma d’alimentation sans fil. Pour utiliser et récupérer cette énergie RF, cette thèse présente deux techniques principales : la récupération/réception de puissance sans fil en champ lointain (wireless power transfer: WPT) et la rétrodiffusion d'harmoniques. Le chapitre 2 aborde les différents mécanismes de conversion de fréquence entre le WPT en champ lointain et la rétrodiffusion d'harmoniques. La récupération de WPT en champ lointain consiste à convertir l'énergie RF en puissance continue. En revanche, la rétrodiffusion d'harmoniques a pour but de convertir l'énergie RF dans une autre fréquence, dans la plupart des cas, la composante harmonique de rang 2. A titre d'étape préliminaire de recherche et d'étude de faisabilité, une cartographie de la densité de l'énergie RF ambiante dans les zones centrales de l'île de Montréal est résumée au chapitre 3. Contrairement aux mesures traditionnelles précédentes effectuées à des endroits fixes, cette mesure dynamique a été réalisée le long des rues, des routes, des avenues et des autoroutes pour couvrir une large zone.----------ABSTRACT Our life is becoming more convenient, efficient, and intelligent with the aid of fast-evolving Internet of Things (IoT) technology. One essential foundation of IoT technology is the development of numerous interrelated IoT sensors that are distributed extensively in our environment. However, conventional batteries/cords-based powering solutions are certainly not an acceptable long-term solution, considering the incurred cost, feasibility, most of all, environmental impact. Meanwhile, climate change due to excessive consumption of fossil fuels is worsening day by day. Therefore, a transformative powering solution for such large-scale and geographically scattered IoT sensors is of extreme importance in support of such extensive IoT sensors implementation while simultaneously mitigating its environmental burden. Serving as a critical information carrier, ambient radiofrequency (RF) energy is pervasive in urban and suburban areas to realize wireless communication and sensing. However, part of ambient RF energy is dissipated due to path loss if not fully consumed by end-users. Hence, recycling the wasted ambient RF energy to power IoT sensors is a promising solution. The concept of harnessing wireless energy for powering IoT sensors requiring a higher power supply is also feasible through the dedicated wireless power delivery from specialized power stations, which can be an effective supplement. To realize the RF power scavenging, this thesis research introduces two mainstream techniques: far-field wireless power transfer (WPT) and harmonic backscattering. Chapter 2 discusses the different frequency conversion mechanisms applied for far-field or ambient WPT harvesting and harmonic backscattering. Far-field WPT harvesting converts RF energy into dc power (zeroth harmonic). In contrast, harmonic backscattering upconverts RF energy into its harmonics, in most cases, the second harmonic component. As a preliminary research step and a feasibility study, a survey of ambient RF energy density in the core areas on Montreal Island is summarized in Chapter 3. Different from the previously published traditional measurements at fixed locations, this dynamic measurement is carried out along streets, roads, avenues, and highways to cover a large area. Also, a stationary measurement in Downtown Montreal is to reveal whether human activities are able to bring visible change to ambient RF energy levels. This work demonstrates how much ambient RF energy is available in free space and acts as a significant reference for researchers and engineers designing ambient RF energy harvesting circuits/systems for practical applications