Powering IoT Sensors with RF Energy Harvesting

There is a need to power Internet of Things (IoT) applications that require frequent, expensive, and/or dangerous battery replacements. Radio-frequency energy harvesting (RFEH) is a possible alternative source of power for select IoT sensor applications. In comparison to other methods of energy harvesting, RFEH has the smallest incident power densities and therefore comes with many design challenges. In this project we implement a novel RFEH system powered via a dedicated transmitter. A planar inverted-F antenna (PIFA) and voltage doubler circuit form the designed rectenna (rectifier + antenna) and the system is implemented on a custom PCB to carry out RF-to-DC conversion. The system’s feasibility is demonstrated by powering a commercial power management unit (PMU) and temperature sensor over a test duration of eight hours

Integrating Sensing, Communication, and Power Transfer: From Theory to Practice

To support the development of internet-of-things applications, an enormous population of low-power devices are expected to be incorporated in wireless networks performing sensing and communication tasks. As a key technology for improving the data collection efficiency, integrated sensing and communication (ISAC) enables simultaneous data transmission and radar sensing by reusing the same radio signals. In addition to information carriers, wireless signals can also serve as energy delivers, which enables simultaneous wireless information and power transfer (SWIPT). To improve the energy and spectrum efficiency, the advantages of ISAC and SWIPT are expected to be exploited, leading to the emerging technology of integrating sensing, communication, and power transfer (ISCPT). In this article, a timely overview of ISCPT is provided with the description of the fundamentals, the characterization of the theoretical boundary, the discussion on the key technologies, and the demonstration of the implementation platform.Comment: This paper has been submitted to IEEE for possible publicatio

Joint energy harvesting time allocation and beamforming in two-way relaying network

Abstract. A two-way relaying system with amplify-and-forward technique, where relay stations (RSs) acquire the energy from transmission signal and interferences, is considered. The RSs use the energy to amplify the signal received from the transmitter and forward it to the receiver. Particularly, energy harvesting (EH) and time switching (TS) are deployed. Based on the TS architecture, we divide transmission time into two time slots, which are EH phase and information transmission (IT) phase. In the EH phase, the RSs harvest the energy from the received radio frequency (RF) signal. In the IT phase, the RSs process and forward the transmission signal to the destination by energy harvesting during the EH phase. From such a transmission scheme, we investigate the optimal time ratio of the EH and IT phase as well as the beamforming at RSs in order to acquire the sum rate maximization. Since the sum-rate maximization problem is nonconvex, we develop an iterative algorithm based on the majorization-minimization (MM) technique to solve the problem. Furthermore, we deployed two schemes to overcome the self-interference to see the efficiency of each scheme related to sum-rate performance. The results show that power transmission and a number of relay station have a major impact on the sum rate performance of the two-way relay system

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 Wireless Power and Data Transfer : Experiment-driven Analysis and Waveform Design

The brisk deployment of the fifth generation (5G) mobile technology across the globe has accelerated the adoption of Internet of Things (IoT) networks. While 5G provides the necessary bandwidth and latency to connect the trillions of IoT sensors to the internet, the challenge of powering such a multitude of sensors with a replenishable energy source remains. Far-field radio frequency (RF) wireless power transfer (WPT) is a promising technology to address this issue. Conventionally, the RF WPT concepts have been deemed inadequate to deliver wireless power due to the undeniably huge over-the-air propagation losses. Nonetheless, the radical decline in the energy requirement of simple sensing and computing devices over the last few decades has rekindled the interest in RF WPT as a feasible solution for wireless power delivery to IoT sensors. The primary goal in any RF WPT system is to maximize the harvested direct current (DC) power from the minuscule incident RF power. As a result, optimizing the receiver power efficiency is pivotal for an RF WPT system. On similar lines, it is essential to minimize the power losses at the transmitter in order to achieve a sustainable and economically viable RF WPT system. In this regard, this thesis explores the system-level study of an RF WPT system using a digital radio transmitter for applications where alternative analog transmit circuits are impractical. A prototype test-bed comprising low-cost software-defined radio (SDR) transmitter and an off-the-shelf RF energy-harvesting (EH) receiver is developed to experimentally analyze the impact of clipping and nonlinear amplification at the digital radio transmitter on digital baseband waveform. The use of an SDR allows leveraging the test-bed for the research on RF simultaneous wireless information and power transfer (SWIPT); the true potential of this technology can be realized by utilizing the RF spectrum to transport data and power together. The experimental results indicate that a digital radio severely distorts high peak-to-average power ratio (PAPR) signals, thereby reducing their average output power and rendering them futile for RF WPT. On similar lines, another test-bed is developed to assess the impact of different waveforms, input impedance mismatch, incident RF power, and load on the receiver power efficiency of an RF WPT system. The experimental results provide the foundation and notion to develop a novel mathematical model for an RF EH receiver. The parametric model relates the harvested DC power to the power distribution of the envelope signal of the incident waveform, which is characterized by the amplitude, phase and frequency of the baseband waveform. The novel receiver model is independent of the receiver circuit’s matching network, rectifier configuration, number of diodes, load as well as input frequency. The efficacy of the model in accurately predicting the output DC power for any given power-level distribution is verified experimentally. Since the novel receiver model associates the output DC power to the parameters of the incident waveform, it is further leveraged to design optimal transmit wave-forms for RF WPT and SWIPT. The optimization problem reveals that a constant envelope signal with varying duty cycle is optimal for maximizing the harvested DC power. Consequently, a pulsed RF waveform is optimal for RF WPT, whereas a continuous phase modulated pulsed RF signal is suitable for RF SWIPT. The superior WPT performance of pulsed RF waveforms over multisine signals is demonstrated experimentally. Similarly, the pulsed phase-shift keying (PSK) signals exhibit superior receiver power efficiency than other communication signals. Nonetheless, varying the duty-cycle of pulsed PSK waveform leads to an efficiency—throughput trade-off in RF SWIPT. Finally, the SDR test-bed is used to evaluate the overall end-to-end power efficiency of different digital baseband waveforms through wireless measurements. The results indicate a 4-PSK modulated signal to be suitable for RF WPT considering the overall power efficiency of the system. The corresponding transmitter, channel and receiver power efficiencies are evaluated as well. The results demonstrate the transmitter power efficiency to be lower than the receiver power efficiency

Signal and System Design for Wireless Power Transfer : Prototype, Experiment and Validation

A new line of research on communications and signals design for Wireless Power Transfer (WPT) has recently emerged in the communication literature. Promising signal strategies to maximize the power transfer efficiency of WPT rely on (energy) beamforming, waveform, modulation and transmit diversity, and a combination thereof. To a great extent, the study of those strategies has so far been limited to theoretical performance analysis. In this paper, we study the real over-the-air performance of all the aforementioned signal strategies for WPT. To that end, we have designed, prototyped and experimented an innovative radiative WPT architecture based on Software-Defined Radio (SDR) that can operate in open-loop and closed-loop (with channel acquisition at the transmitter) modes. The prototype consists of three important blocks, namely the channel estimator, the signal generator, and the energy harvester. The experiments have been conducted in a variety of deployments, including frequency flat and frequency selective channels, under static and mobility conditions. Experiments highlight that a channeladaptive WPT architecture based on joint beamforming and waveform design offers significant performance improvements in harvested DC power over conventional single-antenna/multiantenna continuous wave systems. The experimental results fully validate the observations predicted from the theoretical signal designs and confirm the crucial and beneficial role played by the energy harvester nonlinearity.Comment: Accepted to IEEE Transactions on Wireless Communication

Q-learning Channel Access Methods for Wireless Powered Internet of Things Networks

The Internet of Things (IoT) is becoming critical in our daily life. A key technology of interest in this thesis is Radio Frequency (RF) charging. The ability to charge devices wirelessly creates so called RF-energy harvesting IoT networks. In particular, there is a hybrid access point (HAP) that provides energy in an on-demand manner to RF-energy harvesting devices. These devices then collect data and transmit it to the HAP. In this respect, a key issue is ensuring devices have a high number of successful transmissions. There are a number of issues to consider when scheduling the transmissions of devices in the said network. First, the channel gain to/from devices varies over time. This means the efficiency to deliver energy to devices and to transmit the same amount of data is different over time. Second, during channel access, devices are not aware of the energy level of other devices nor whether they will transmit data. Third, devices have non-causal knowledge of their energy arrivals and channel gain information. Consequently, they do not know whether they should delay their transmissions in hope of better channel conditions or less contention in future time slots or doing so would result in energy overflow