Adhoc mobile power connectivity using a wireless power transmission grid

Wireless charging of devices has significant outcomes for mobile devices, IoT devices and wearables. Existing technologies consider using Point to Point type wireless transfer from a transmitter Tx (node that is sending Power) to a receiver Rx (node that receives power), which limits the area of coverage for devices. As a result, existing systems are forced to use near field coupling to charge such devices. Fundamental limitation is also that such methods limit charging to a small hotspot. In partnership with Wireless Electrical Grid LANs (WiGL pronounced “wiggle”), we demonstrate patented Ad-hoc mesh networking method(s) to provide wireless recharging at over 5 feet from the source, while allowing significant lateral movement of the receiver on the WiGL (Wireless Grid LAN or local area network). The transmitter network method leverages a series of panels, operating as a mesh of transmitters that can be miniaturized or hidden in walls or furniture for an ergonomic use. This disruptive technology holds the unique advantage of being able to provide recharging of moving targets similar to the cellular concept used in WiLAN, as opposed to prior wireless charging attempts, which only allow a hotspot-based charging. Specifically, we demonstrate the charging of a popular smartphone using the proposed system in the radiating near field zone of the transmitter antennas, while the user is free to move in the space on the meshed network. The averaged received power of 10 dBm is demonstrated using 1W RF-transmitter(s), operating in the 2.4 GHz ISM band. The proposed hardware consists of antennas arrays, rectennas, power management and USB 2.0 interfaces for maintaining a voltage between 4.2 and 5.3 V and smooth charging. We also show extending the wireless grid coverage with the use of multiple transmitting antennas, and mechanical beam-steering even further an increased coverage using the proposed system

Power Beacon’s deployment optimization for wirelessly powering massive Internet of Things networks

Abstract. The fifth-generation (5G) and beyond wireless cellular networks promise the native support to, among other use cases, the so-called Internet of Things (IoT). Different from human-based cellular services, IoT networks implement a novel vision where ordinary machines possess the ability to autonomously sense, actuate, compute, and communicate throughout the Internet. However, as the number of connected devices grows larger, an urgent demand for energy-efficient communication technologies arises. A key challenge related to IoT devices is that their very small form factor allows them to carry just a tiny battery that might not be even possible to replace due to installation conditions, or too costly in terms of maintenance because of the massiveness of the network. This issue limits the lifetime of the network and compromises its reliability. Wireless energy transfer (WET) has emerged as a potential candidate to replenish sensors’ batteries or to sustain the operation of battery-free devices, as it provides a controllable source of energy over-the-air. Therefore, WET eliminates the need for regular maintenance, allows sensors’ form factor reduction, and reduces the battery disposal that contributes to the environment pollution. In this thesis, we review some WET-enabled scenarios and state-of-the-art techniques for implementing WET in IoT networks. In particular, we focus our attention on the deployment optimization of the so-called power beacons (PBs), which are the energy transmitters for charging a massive IoT deployment subject to a network-wide probabilistic energy outage constraint. We assume that IoT sensors’ positions are unknown at the PBs, and hence we maximize the average incident power on the worst network location. We propose a linear-time complexity algorithm for optimizing the PBs’ positions that outperforms benchmark methods in terms of minimum average incident power and computation time. Then, we also present some insights on the maximum coverage area under certain propagation conditions

UAV-enabled wireless-powered Iot wireless sensor networks

Future massive internet of thing (IoT) networks will enable the vision of smart cities, where it is anticipated that a massive number of sensor devices, in the order of tens of millions devices, ubiquitously deployed to monitor the environment. Main challenges in such a network are how to improve the network lifetime and design an e cient data aggregation process. To improve the lifetime, using low-power passive sensor devices have recently shown great potential. Ambient backscattering is a novel technology which provides low-power long-range wireless communication expanding the network lifetime signi cantly. On the other hand, in order to collect the sensed data from sensor devices deployed over a wide area, unmanned aerial vehicles (UAVs) has been considered as a promising technology, by leveraging the UAV's high mobility and line-of-sight (LOS) dominated air-ground channels. The UAV can act as data aggregator collecting sensed data from all sensors. In this thesis, we consider medium-access control (MAC) policies for two sensor data collection scenarios. First, the objective is to collect individual sensor data from the eld. The challenge in this case is to determine how a large number of sensors should access the medium so that data aggregation process performed in a fast and reliable fashion. Utilizing conventional orthogonal medium access schemes (e.g., time-division vi multiple access (TDMA) and frequency-division multiple access (FDMA)), is highly energy consuming and spectrally ine cient. Hence, we employ non-orthogonal multiple access (NOMA) which is envisaged as an essential enabling technology for 5G wireless networks especially for uncoordinated transmissions. In Chapter 2, we develop a framework where the UAV is used as a replacement to conventional terrestrial data collectors in order to increase the e ciency of collecting data from a eld of passive backscatter sensors, and simultaneously it acts as a mobile RF carrier emitter to activate backscatter sensors. In the MAC layer, we employ uplink power-domain NOMA scheme to e ectively serve a large number of passive backscatter sensors. Our objective is to optimize the path, altitude, and beamwidth of the UAV such that the network throughput is maximized. In Chapter 3, we consider the scenario where there are a separate data collector and RF carrier emitter such that the former is a gateway on the ground and the latter is a single UAV hovering over the eld of backscatter sensors. Secondly, we consider a case where only a function of sensed data is of interest rather than individual sensor values. A new challenge arises where the problem is to design a communication policy to improve the accuracy of the estimated function. Recently, over-the-air computation (AirComp) has emerged to be a promising solution to enable merging computation and communication by utilizing the superposition property of wireless channels, when a function of measurements are desired rather than individual in massive IoT sensor networks. One of the key challenges in AirComp is to compensate the e ects of channel. Motivated by this, in Chapter 4, we propose a UAV assisted communication framework to tackle this problem by a simple to implement sampling-then-mapping mechanism

Fundamentals of Wireless Information and Power Transfer: From RF Energy Harvester Models to Signal and System Designs

Radio waves carry both energy and information simultaneously. Nevertheless, Radio-Frequency (RF) transmission of these quantities have traditionally been treated separately. Currently, we are experiencing a paradigm shift in wireless network design, namely unifying wireless transmission of information and power so as to make the best use of the RF spectrum and radiations as well as the network infrastructure for the dual purpose of communicating and energizing. In this paper, we review and discuss recent progress on laying the foundations of the envisioned dual purpose networks by establishing a signal theory and design for Wireless Information and Power Transmission (WIPT) and identifying the fundamental tradeoff between conveying information and power wirelessly. We start with an overview of WIPT challenges and technologies, namely Simultaneous Wireless Information and Power Transfer (SWIPT),Wirelessly Powered Communication Network (WPCN), and Wirelessly Powered Backscatter Communication (WPBC). We then characterize energy harvesters and show how WIPT signal and system designs crucially revolve around the underlying energy harvester model. To that end, we highlight three different energy harvester models, namely one linear model and two nonlinear models, and show how WIPT designs differ for each of them in single-user and multi-user deployments. Topics discussed include rate-energy region characterization, transmitter and receiver architecture, waveform design, modulation, beamforming and input distribution optimizations, resource allocation, and RF spectrum use. We discuss and check the validity of the different energy harvester models and the resulting signal theory and design based on circuit simulations, prototyping and experimentation. We also point out numerous directions that are promising for future research.Comment: guest editor-authored tutorial paper submitted to IEEE JSAC special issue on wireless transmission of information and powe

Energy-Efficient Wireless Connectivity and Wireless Charging For Internet-of-Things (IoT) Applications

During the recent years, the Internet-of-Things (IoT) has been rapidly evolving. It is indeed the future of communication that has transformed Things of the real world into smarter devices. To date, the world has deployed billions of “smart” connected things. Predictions say there will be 10’s of billions of connected devices by 2025 and in our lifetime we will experience life with a trillion-node network. However, battery lifespan exhibits a critical barrier to scaling IoT devices. Replacing batteries on a trillion-sensor scale is a logistically prohibitive feat. Self-powered IoT devices seems to be the right direction to stand up to that challenge. The main objective of this thesis is to develop solutions to achieve energy-efficient wireless-connectivity and wireless-charging for IoT applications. In the first part of the thesis, I introduce ultra-low power radios that are compatible with the Bluetooth Low-Energy (BLE) standard. BLE is considered as the preeminent protocol for short-range communications that support transmission ranges up to 10’s of meters. Number of low power BLE transmitter (TX) and receiver (RX) architectures have been designed, fabricated and tested in different planar CMOS and FinFET technologies. The low power operation is achieved by combining low power techniques in both the network and physical layers, namely: backchannel communication, duty-cycling, open-loop transmission/reception, PLL-less architectures, and mixer-first architectures. Further novel techniques have been proposed to further reduce the power the consumption of the radio design, including: a fast startup time and low startup energy crystal oscillators, an antenna-chip co-design approach for quadrature generation in the RF path, an ultra-low power discrete-time differentiator-based Gaussian Frequency Shift Keying (GFSK) demodulation scheme, an oversampling GFSK modulation/demodulation scheme for open loop transmission/reception and packet synchronization, and a cell-based design approach that allows automation in the design of BLE digital architectures. The implemented BLE TXs transmit fully-compliant BLE advertising packet that can be received by commercial smartphone. In the second part of the thesis, I introduce passive nonlinear resonant circuits to achieve wide-band RF energy harvesting and robust wireless power transfer circuits. Nonlinear resonant circuits modeled by the Duffing nonlinear differential equation exhibit interesting hysteresis characteristics in their frequency and amplitude responses that are exploited in designing self-adaptive wireless charging systems. In the magnetic-resonance wireless power transfer scenario, coupled nonlinear resonators are proposed to maintain the power transfer level and efficiency over a range of coupling factors without active feedback control circuitry. Coupling factor depends on the transmission distance, lateral, and angular misalignments between the charging pad and the device. Therefore, nonlinear resonance extends the efficient charging zones of a wireless charger without the requirement for a precise alignment.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169842/1/omaratty_1.pd