wireless energy transfer and harvesting introduction … · wireless energy transfer and harvesting...
TRANSCRIPT
03. November 2016
Wireless Energy Transfer and Harvesting
Introduction and Future Perspectives
Marco Maso
Mathematical and Algorithmic Sciences Lab, Huawei France Research Center
Why is energy efficiency important?
Care for the planet and the “networkoperator’s wallet”
Electricity bill is approximately 20% of
operational expenditure of mobile
operators
Increasing energy cost trends
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Source: EARTH Project.
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Increasing Energy Efficiency by Combination Renewable and Grid Energy Sources
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M. Ismail, W. Zhuang, E. Serpedin, and K. Qaraqe, “A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users”, IEEE Communications Surveys & Tutorials, Early Access, Nov 2014.
A hybrid charging system used to overcome the intermittent nature of
renewable energy sources
MAIN IDEA
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Major energy harvesting technologies
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Our environment provides several virtually cost-free sources of energy that can be harvested if appropriate devices are adoptedIntuition
Energy harvesting communications have recently emerged as a promising paradigm to supply power to network terminals by letting them scavenge energy from external resources
These sources are already exploited to scavenge power for human activities, hence it seems legit to envision their exploitation in the
context of wireless communications as well
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Photovoltaic Energy Harvesting
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• The electrons in a silicon cell can be excited by sunlight in the presence of impurities in the silicon, e.g., phosphorus.
• As a result of the excitation electrons break free and flow through the silicon surface in the form direct current electricity.
• Under certain conditions, this may offer a virtually unfailing source of energy with little or no adverse environmental impact.
Photovoltaic effect
This energy can be harvested both indoor and outdoor, even though with different
efficiencies
Source: Trevor Barcelo | Linear Technology
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Vibrational Energy Harvesting
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• Mechanical stimuli and vibrations of different amplitude and frequency are observed as direct or indirect product of several events in many operating environments.
• In this context, energy can be harvested in two major ways, i.e., electromagnetic and piezoelectrictransduction.
• The oscillation of a mass (magnetic or not) is tuned to the operating environment's dominant mechanical frequency.
Transduction
This energy can be harvested if the device is subject to movement or external stimuli
Source: http://www.piezo.com
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Thermoelectric Energy Harvesting
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• A thermal gradient across an object or between two dissimilar conductors produces a voltage and can thus be exploited to scavenge electric energy.
• The amount of energy that can be obtained is bounded by the fundamental limit given by the Carnot thermodynamic cycle efficiency.
Carnot Cycle
The physical constraint is counterbalanced by the excellent longevity of
thermoelectric energy harvesters thanks to the absence of any moving parts
Source: Dave Koester | Electronic Design
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Wind Energy Harvesting
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• One of the most widespread approaches to energy harvesting in the last decade.
• In general, wind can be used to power electrical generator by letting it flow through appropriately designed devices.
• It can be classified into variable-speed and fixed-speed devices.
Wind flow
Energy can then be harvested in many different ways, e.g., by means of
electromagnetic, piezoelectric mechanisms
Source: Don Scansen | Electronic Products
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Microwave Enabled Wireless Energy Transfer
Nikola Tesla (1856-1943)
In the very early days of electricity before the electric grid was deployed, Tesla was very interested in developing a scheme to transmit electricity wirelessly over long distances.
It ran into some financial troubles and that work was never completed
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The Invention of Rectennas for Microwave Power Transmission
The Microwave powered Helicopter by William C. Brown in1960s
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Solar Satellite with Microwave Power Transmission
1968’s idea for Solar Power Satellites proposed by Peter Glaser Solar power from the satellite is sent to Earth using a microwave transmitter
Received at a “rectenna” located on Earth
Target at GW-level power transfer with more than50% efficiency.
NASA Suntower
Rectenna: Magic carpet pegged to the ground
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RF-based Transfer: Why?
At first glance RF-based Wireless Energy Transfer (WET) does not seem the mostpromising approach for integrating WET functionalities into future wirelessnetworks, regardless of the frequency of the radiation.
HOWEVER
It allows transfers in one direction in a service-like fashion.
It can be continuous and controllable (whereas ambient RF and otherenvironment energy harvesting are intermittent and random).
It has promising potential applications: mobile device or sensor charging, etc.
It paves the way towards energy recycling strategies to increase the energyefficiency of the network.
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Energy flow
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How efficient are state-of-the-art RF-EH circuits if single-carrier signal is received and no optimization is performed at the transmitter side?
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Rectenna Efficiency
Wireless Sensing Platform Utilizing Ambient RF Energy (University of Washington)
Ambient RF-powered prototype, measures temperature and light level and wirelessly transmits these measurements.
RF input power required for sensor operation:-18 dBm (15.8 uW) (6 dBi receive antenna)
Operates at a distance of:
10.4 km (1 MW UHF television transmitter).@ 7 bit/s **
200 m (cellular base transceiver station).
** Throughput metric does not fully make sense, since EH does not strongly correlate with TX capabilities.
1 MW transmitter in Seattle (2 dBi TX gain, 6 dBi RX gain at 539 MHz). Dotted line
indicates the 10.4 km radius tested.
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Practical Results (I)
Wi-Fi Powered Camera(University of Washington)
Wi-Fi band (2.401–2.473 GHz)
“PoWiFi” (Adapted broadcast traffic for improved power transmission)
Enables applications where low-rate camera can be left without the need for replacing battery (leakage and structural integrity detection)
@ 50 bit/s
@ 300 bit/s
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Practical Results (II)
Simultaneous Wireless Information and Power Transfer (SWIPT)
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By means of appropriate signal processing, both information and energy can be transmitted to receivers of any kind, simultaneously.
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Advantages and Applications
SWIPT Applications
Cellular Internet of Things in general and Sensor applications in particular: o Wirelessly connected “battery free” devices.
• Sealed environments (medical devices, moving parts, etc.).• Small size (as before + security).
o Trickle Charging, High-function RFID.o Wearable devices.
SWIPT Advantages
TECHNICAL: Radiative far-field transfer of information and energy, thus it allows both data decoding and more efficient RF Energy Harvesting (EH) at the same time:o Directed RF energy from BS improves efficiency as compared to Ambient RF EH.o Same antenna(s), or different antennas can be used at both TX and RX side.
PRACTICAL: It allows to multiplex information and energy in a fully controllable way for the source/base station.o Several applications can be envisioned at the TX side to increase the efficiency of the RF-WET without severely compromising the spectral efficiency of the links.o Acting at the TX side allows to minimize hardware inefficiencies at the RX.
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Time switching design
• The receiver switches betweendecoding the information andharvesting energy at any time
Power splitting design
• The receiver splits the incoming signals into two portions of different power for decoding information and harvesting energy separately
Integrated design
• Both time switching and powersplitting are implemented in anintegrated architecture (RF FlowController)
Information Receiver
Energy ReceiverTime Switcher
Rx
Information Receiver
Energy ReceiverPower Splitter
Rx
Figure source: RF Energy Harvesting for Wireless Devices, R. Sandhya Lakshmi, International Journal of Engineering Research and Development e-ISSN: 2278-067X, ISSN: 2278-800X, www.ijerd.com Volume 11, Issue 04 (April 2015), PP.39-52
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Splitting Paradigms
SWIPT for the Internet of Everything
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WiFi
UtilityDevices
The variety of devices that could profit from the adoption of optimized SWIPT/RF-WET transceiver and algorithm design at the transmitter/receiver is huge...
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State of the art: Energy Focusing System Based on Path Reversal
Commercially available solution named Cota©
Adoption of large antenna arrays at transmitter for energy focusing techniques based on path reversal allows received power in the order of the W.
The Cota charger can deliver up to 1 W of power safely to devices worn on the body up to 10ft away;
More power can be delivered to devices that are not worn on the body. The average usable energy is about 72 Wh for a 24-hour period.
The TX uses about 8 W to deliver 1 W of power to a device.
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Energy Spatial Multiplexing
Energy Spatial Multiplexing (ESM): Key enabler for performing a meaningful RF-WET towards portable/wearable/low-power devices and prolong their battery lifetime, using 4.5G / 5G SDMA precoding capabilities.
Additional diversity gain in fading channel.
If full channel state information (CSI) is available at the transmitter, the full MIMO arraygain can be exploited and path-loss can be mitigated effectively, hence even future networks consumer electronics can benefit from EH (see following slide).
RxTx
…
FUNDAMENTAL QUESTIONS:
What will happen to the Power Density in Cellular Networks? Will RF-WET coupled with ESM necessitate a change in the current regulationsfor spectrum usage/allocation?
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Waveform Design (I)
GENERAL GOAL of the Waveform Design
Move away from the conventional linear model anddesign a waveform so as to maximize the DC outputpower, given a certain input.The rectifier is a heavily nonlinear
component
RECTIFIERResponsible for RF-to-DC
conversion
TAYLOR EXPANSION
DRAWBACKS of linear model
• Only accounts for second order term of Taylor expansion.• Yields Adaptive Single Sinewave (ASS) strategy that
allocates all power to the (single) sinewave that corresponds to the strongest channel.
Classic approaches in SWIPT literature are based on linear approximations of the operations performed
by the rectifier.
IDEAL GOAL
• Guarantee maximum RF-to-DC conversionefficiency, e.g., ~100%.
• Target spectral efficiency maximization, in ordernot to compromise on the performance of theinformation transfer.
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RESULTS
• Globally optimal phases obtained in closed-form.
However
• Only locally optimal amplitudes result of a non-convex polynomial maximization problem. Formulate as a Reverse Geometric Program and solve iteratively.
B. Clerckx and E. Bayguzina, “Waveform design for wireless power transfer,” IEEE Transactions on Signal Processing, vol. PP, 2016.
ASSUMPTIONS
• The rectifier static characteristics 𝑘𝑖 are known at thetransmitter either by construction or by one-time userreporting.
• Non-linear model that accounts for any order in the rectifierTaylor expansion is adopted.
And
• Frequency response of the channel is available in a widesense (the better the quality of the estimation the moreoptimal the designed waveform).
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Waveform Design (II)
Sensors need around 10 μW DC (cfr. PsiKick’s Fully Integrated Wireless SOC sensors)
Large-scale multi-carriers multi-antenna waveforms are optimal for WET.
Think big: up to thousands of subcarriers and hundreds of antennas/TX in 5G (OFDM/Massive MIMO)
Average DC power as a function of (N,M) for different
waveforms (brown is optimal)
Parameter Value
Carrier 5.18 GHz
Bandwidth 10 MHz
Number of subcarriers N
TX power 36 dBm
RX antenna gain 2 dBi
Path loss -58 dB
Channel type NLOS office
Average RX power -20 dBm
Frequency spacing Bandwidth/N
• Complexity of this solution is high!
• No practically feasible waveform that can achieve the targetperformance in terms of efficiency of information/energytransfer and complexity is currently known.
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Waveform Design (III)
References1. J. A. Paradiso and T. Starner, ”Energy scavenging for mobile and wirelesselectronics,” in IEEE Pervasive Comput.,
vol. 4(1), pp. 18-27, Jan.-Mar. 2005
2. L. R. Varshney, “Transporting Information and Energy Simultaneously,” in IEEE Int. Symp. Inform. Theory (ISIT), 2008, pp. 1612–1616.
3. H. J. Visser and R. J. M. Vullers, “RF energy harvesting and transport for wireless sensor network applications: Principles and requirements,” Proc. IEEE, vol. 101, no. 6, pp. 1410–1423, 2013.
4. M. Maso, “Energy Harvesting Oriented Transceiver Design for 5G Networks”, in Energy Management in Wireless Cellular and Ad hoc Networks’, Edited by Shakir, M. Z., Imran, M. A., Alouini, M.-S., Vasilakos, T. and Qarage, K., Springer, 2016.
5. Z. Hasan, H. Boostanimehr, and V. K. Bhargava, “Green Cellular Networks: A Survey, Some Research Issues and Challenges,” in IEEE Communs. Surveys and Tutorial, vol. 13, no. 4, pp. 525-540, 2011.
6. R. Zhang and C. K. Ho, “MIMO Broadcasting for simultaneously wireless information and power transfer,” IEEE Trans. Wireless Communications, vol. 12, no. 5, pp. 1989-2001, May 2013.
7. M. Ismail, W. Zhuang, E. Serpedin, and K. Qaraqe, “A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users”, IEEE Communications Surveys & Tutorials, Early Access, Nov 2014.
8. Zhou, Xun; Zhang, Rui; Ho, Chin Keong, Wireless Information and Power Transfer: Architecture Design and Rate-Energy Tradeoff, IEEE Transactions on Communications, vol.61, no.11, pp.4754,4767, November 2013, doi: 10.1109/TCOMM.2013.13.120855
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References9. R. Sandhya Lakshmi, RF Energy Harvesting for Wireless Devices, International Journal of Engineering Research
and Development e-ISSN: 2278-067X, ISSN: 2278-800X, www.ijerd.com Volume 11, Issue 04 (April 2015), PP. 39-52.
10. X. Lu, P. Wang, D. Niyato, D. I. Kim and Z. Han, "Wireless Networks With RF Energy Harvesting: A Contemporary Survey," in IEEE Communications Surveys & Tutorials, vol. 17, no. 2, pp. 757-789, Secondquarter 2015.
11. V. Talla, B. Kellogg, B. Ransford, A. Naderiparizi, S. Gollakota, J. R. Smith, “Powering the Next Billion Devices with Wi-Fi”, Arxiv preprint: http://arxiv.org/abs/1505.06815
12. A. N. Parks, A. P. Sample, Y. Zhao and J. R. Smith, "A wireless sensing platform utilizing ambient RF energy," 2013 IEEE Radio and Wireless Symposium, Austin, TX, 2013, pp. 331-333.
13. B. Clerckx and E. Bayguzina, “Waveform design for wireless power transfer,” IEEE Transactions on Signal Processing, vol. PP, no. 99, pp. 1–1, 2016.
14. B. Clerckx, E. Bayguzina, D. Yates, and P. D. Mitcheson, “Waveform optimization for wireless power transfer with nonlinear energy harvester modeling,” in Proc. Intl. Symp. Wireless Commun. Syst. (ISWCS 2015), Brussels, Belgium, Aug 2015, pp. 276–280.
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