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

Waveform Optimization and Beam Focusing for Near-field Wireless Power Transfer with Dynamic Metasurface Antennas and Non-linear Energy Harvesters

Radio frequency (RF) wireless power transfer (WPT) is a promising technology for future wireless systems. However, the low power transfer efficiency (PTE) is a critical challenge for practical implementations. One of the main inefficiency sources is the power consumption and loss introduced by key components such as high-power amplifier (HPA) and rectenna, thus they must be carefully considered for PTE optimization. Herein, we consider a near-field RF-WPT system with the emerging dynamic metasurface antenna (DMA) at the transmitter and non-linear energy harvesters. We provide a mathematical framework to calculate the power consumption and harvested power from multi-tone signal transmissions. Then, we propose an approach relying on alternating optimization and successive convex approximation for waveform optimization and beam focusing to minimize power consumption while meeting energy harvesting requirements. Numerical results show that increasing the transmit tones reduces the power consumption by leveraging the rectifier's non-linearity. Moreover, it is demonstrated that increasing the antenna length improves the performance, while both DMA and fully-digital architectures may be favorable depending on the setup. Finally, our results verify that the transmitter generates accurate energy beams pointed to devices located in the near-field, while energy beams are formed in devices' direction in the far-field region.Comment: 13 pages, 12 figure

Prototyping and Experimentation of a Closed-Loop Wireless Power Transmission with Channel Acquisition and Waveform Optimization

A systematic design of adaptive waveform for Wireless Power Transfer (WPT) has recently been proposed and shown through simulations to lead to significant performance benefits compared to traditional non-adaptive and heuristic waveforms. In this study, we design the first prototype of a closed-loop wireless power transfer system with adaptive waveform optimization based on Channel State Information acquisition. The prototype consists of three important blocks, namely the channel estimator, the waveform optimizer, and the energy harvester. Software Defined Radio (SDR) prototyping tools are used to implement a wireless power transmitter and a channel estimator, and a voltage doubler rectenna is designed to work as an energy harvester. A channel adaptive waveform with 8 sinewaves is shown through experiments to improve the average harvested DC power at the rectenna output by 9.8% to 36.8% over a non-adaptive design with the same number of sinewaves.Comment: accepted for publication in IEEE WPTC 201

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

Waveform Optimization for Large-Scale Multi-Antenna Multi-Sine Wireless Power Transfer

Wireless power transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, machine-to-machine communications and radio frequency identification networks. Although there has been some progress towards multi-antenna multi-sine WPT design, the large-scale design of WPT, reminiscent of massive multiple-input multiple-output (MIMO) in communications, remains an open problem. Considering the nonlinear rectifier model, a multiuser waveform optimization algorithm is derived based on successive convex approximation (SCA). A lower-complexity algorithm is derived based on asymptotic analysis and sequential approximation (SA). It is shown that the difference between the average output voltage achieved by the two algorithms can be negligible provided the number of antennas is large enough. The performance gain of the nonlinear model based design over the linear model based design can be large, in the presence of a large number of tones.Comment: To appear in the 17th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC 2016

Waveform Optimization for Wireless Power Transfer with Nonlinear Energy Harvester Modeling

Far-field Wireless Power Transfer (WPT) and Simultaneous Wireless Information and Power Transfer (SWIPT) have attracted significant attention in the RF and communication communities. Despite the rapid progress, the problem of waveform design to enhance the output DC power of wireless energy harvester has received limited attention so far. In this paper, we bridge communication and RF design and derive novel multisine waveforms for multi-antenna wireless power transfer. The waveforms are adaptive to the channel state information and result from a posynomial maximization problem that originates from the non-linearity of the energy harvester. They are shown through realistic simulations to provide significant gains (in terms of harvested DC power) over state-of-the-art waveforms under a fixed transmit power constraint.Comment: paper to be presented at IEEE International Symposium on Wireless Communication Systems (ISWCS 2015

Wirelessly Powered Backscatter Communications: Waveform Design and SNR-Energy Tradeoff

This paper shows that wirelessly powered backscatter communications is subject to a fundamental tradeoff between the harvested energy at the tag and the reliability of the backscatter communication, measured in terms of SNR at the reader. Assuming the RF transmit signal is a multisine waveform adaptive to the channel state information, we derive a systematic approach to optimize the transmit waveform weights (amplitudes and phases) in order to enlarge as much as possible the SNRenergy region. Performance evaluations confirm the significant benefits of using multiple frequency components in the adaptive transmit multisine waveform to exploit the nonlinearity of the rectifier and a frequency diversity gain.Comment: submitted for publicatio