communications and signals design for wireless … 2016 1 communications and signals design for...

1Globecom 2016

Communications and Signals Design for Wireless Power Transmission

Rui Zhang

ECE Department, National University of Singapore

Globecom Workshop on Wireless Energy HarvestingWashington, DC USA, 2016

Rui Zhang, National University of Singapore

Agenda

Overview of main WPT technologies

Microwave WPT: Historical development and contemporary design

WPT and energy receiver model

Single-user WPT

Multi-user WPT

Extensions and future work

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Agenda Rui Zhang, National University of Singapore

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Why Wireless Power?Rui Zhang, National University of Singapore

Wireless power transfer (WPT): deliver power without wires Advantages over traditional energy supply methods:

Convenient: without the hassle of connecting wires and replacing batteries Cost-effective: on-demand power supply with uninterrupted operations Environmental friendly: avoid battery disposal

Extensive applications: Consumer electronics wireless charging Biomedical implants wireless charging Wireless sensor/IoT devices charging Backscatter/RFID communications Simultaneous wireless information and power transfer (SWIPT) Wireless powered communications (WPC)


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Near-field technique based on magnetic induction Main advantage: Very high efficiency (e.g. >90%) Main limitations

Require precise tx/rx coil alignment, very short range, single receiver only Example Applications

Electric vehicle charging, smart phone charging, RFID, smart cards, … Industry standard: Qi (Chee) Representative companies: Powermat, Delphi, GetPowerPad,

WildCharge, Primove, …

Inductive Wireless Power Transfer


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Near-field technique based on magnetic resonant coupling Main advantages: high efficiency and mid-range, one-to-many (multicast) charging Main limitations: sensitive to tx/rx coil alignment, large tx/rx size Applications

Similar to inductive coupling, but target for longer range and multicasting Industry standard: Qi, AirFuel,… Representative companies: Intel, PowerbyProxi, WiTricity, WiPower,….

Magnetic Resonant Wireless Power Transfer


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Far-field WPT technique via EM/microwave radiation Main advantages:

long range, small tx/rx form factors, flexible deployment, support power multicasting with mobility, applicable for both LoS and Non-LoS environment, integration with wireless communication (backscatter, SWIPT, WPCN)

Main limitations: low efficiency, safety and health issues Extensive Applications

Wireless sensor/IoT devices charging, RFID, solar power satellite,… Representative companies: Intel, Energous, PowerCast, Ossia,…

Radiative Wireless Power Transmission

Energy flow


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WPT via highly concentrated laser emission Main advantages

long range, compact size, high energy concentration, no interference to existing communication systems or electronics

Main limitations laser radiation is hazardous, require LoS link and accurate rx focusing,

vulnerable to cloud, fog, and rain Applications

Laser-powered UAVs, laser-powered solar power satellite,… Representative company: LaserMotive, …

Laser Power BeamingOverview of main WPT technologies

Comparison of the Main WPT Technologies

Strength Efficiency Distance Multicast Mobility Safety

Inductive Coupling Very high Very high Very short No No Yes

Magnetic Resonant Coupling

High High Short Yes Difficult Yes

EM Radiation

Omni-directional

Low Low Long Yes Yes Yes

Beamforming (microwave)

High High Very long(LOS)

Yes Yes Safety constraints may apply

Laser beaming High High Long No Difficult Safety constraints may apply

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This talk will focus on EM radiation WPT technology and the main communication and signal design techniques for improving its performance


Agenda




Single-user WPT

Multi-user WPT


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Microwave WPT: Historical development and contemporary design Rui Zhang, National University of Singapore

Microwave Wireless Power Transmission: Historical MilestonesYear Main activity and achievement1888 Heinrich Hertz demonstrated electromagnetic wave propagation in free space

1899 Nicola Tesla conducted the first experiment on dedicated WPT

1901 Nicola Tesla started the Wardenclyffe Tower project

1964 William C. Brown invented rectenna

1964 William C. Brown successfully demonstrated the wireless-powered tethered helicopter

1968 William C. Brown demonstrated the beam-positioned Helicopter

1968 Peter Glaser proposed the SPS concept

1975 Over 30kW DC power was obtained over 1.54km in the JPL Goldstone demonstration

1983 Japan launched the MINIX project

1987 Canada demonstrated the free-flying wireless-powered aircraft 150m above the ground

1992 Japan conducted the MILAX experiment with the phased array transmitter

1993 Japan conducted the ISY-METS experiment

2008 Power was successfully transmitted over 148km in Hawaii

2015 Japan announced successful power beaming to a small device

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Rui Zhang, National University of SingaporeMicrowave WPT: Historical development and contemporary design

Microwave Wireless Power Transmission: Nikola Tesla and his Wardenclyffe Project in early 1900

150 KHz and 300 kW. Unsuccessful and never put into practical use.

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The Invention of ``Rectenna” for Microwave Power Transmission:the Microwave Powered Helicopter by William C. Brown in 1960s

2.45 GHz and less than 1kW. Overall 26% transfer efficiency at 7.6 meters high.

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Solar Satellite with Microwave Power Transmission (1970s-current)

NASA Sun Tower

Target at GW-level power transfer with more than 50% efficiency

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Microwave Wireless Power Transmission: A Fresh New Look

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Historical microwave WPT: Targeting for long distance and high power Mainly driven by the wireless-powered aircraft and SPS applications Requires high transmission power, huge tx/rx antennas, clear LoS link

Contemporary WPT systems: Low-power delivery over moderate distances Reliable and convenient WPT network for low-power devices (sensors, IoT

devices, RFID tags, smart phone, etc.) New design challenges and requirements:

Range: a few meters to hundreds of meters Efficiency: a fractional of percent Non-LoS: closed-loop WPT with channel state information Mobility support: device tracking Ubiquitous and authenticated accessibility Inter-operate with wireless communication systems Safety and health guarantees


Research in Wireless Power Transmission : A Shift of Paradigm


Wireless power transfer (WPT)

Wireless poweredcommunication network

(WPCN)

Simultaneous wireless information and power transfer

(SWIPT)Energy

Energy

Information

Energy

Information

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Extensive research efforts have been devoted to co-designing the wireless power and communication systems, e.g., WPCN & SWIPT

A trade-off between rate & power maximization needs to be made, e.g., time switching, power splitting, harvest-then-transmit, etc.

However, even designing efficient WPT system alone is challenging and new Focus of this talk: introduce the main communication & signal processing

techniques for achieving efficient WPT


Agenda




Single-user WPT

Multi-user WPT


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WPT and energy receiver model Rui Zhang, National University of Singapore

Wireless Power Transmission: A Generic Model

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End-to-end efficiency:

e1: DC-to-RF conversion efficiency at energy transmitter (ET) e2: RF-to-RF transmission efficiency, main bottleneck

Require highly directional transmission with multi-antenna and accurate channel knowledge at ET

e3: RF-to-DC conversion efficiency at energy receiver (ER) Require efficient rectenna design and power waveform optimization


Narrowband Wireless Power Transmission: Channel Model

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Rui Zhang, National University of SingaporeWPT and energy receiver model

Modulated vs. Unmodulated Energy Signal

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Use pseudo-random modulated energy signal to avoid the spike in the power spectral density (PSD) caused by constant unmodulated energy signal

Rui Zhang, National University of SingaporeWPT and energy receiver model

Wireless Power Transmission: Receiver Model (1)

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Only keep the second-order term since y(t) is typically small


Wireless Power Transmission: Receiver Model (2)

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The harvested DC power is proportional to the input RF power (linear model) Nonlinear model if higher-order terms are included (to be considered later)


Agenda




Single-user WPT

Multi-user WPT


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Single-user WPT Rui Zhang, National University of Singapore

Single-User Multi-Band MIMO WPT

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Single-user MIMO WPT with Mt antennas at ET and Mr antennas at ER N frequency sub-bands, with MIMO channel gains H1,…,HN The received power is (assuming linear model):

Power maximization problem:

: transmit covariance matrix at sub-band n nS

rf

rf

: sum-power limit: per-subband power limit

' , where 1 '

t

st

s

PP

P N P N N= ≤ ≤

Single-user WPT

Energy Beamforming for Multi-Band MIMO WPT

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Optimal solution:

: dominant eigenvector of Hn n nv H H

[ ] : permutation of sub-bands with theirdominant eigvenvalues in decreasing order•

Concentrate power to the N’strongest sub-bands

For each sub-band, concentrate power to the strongest eigen-direction

In contrast to multi-band MIMO communication systems

Optimal value:

Exploit both frequency-diversity gain and spatial energy-beamforming gain

max,[ ] : the dominant eigenvalue of the th strongest sub-bandn nλ

Single-user WPT

Channel Acquisition for MIMO WPT

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Energy beamforming requires channel state information (CSI) at the ET Unique considerations for CSI acquisition in WPT in contrast to conventional

wireless communication: CSI at (energy) receiver: not required for WPT Net energy maximization: to balance the energy overhead for CSI acquisition and

the energy harvested with CSI-based energy beamforming Hardware constraint: no/low signal processing capability for low-cost ERs

Candidate solutions depending on the antenna architecture at the ER Forward-link training with CSI feedback Reverse-link training via channel reciprocity Power probing with limited energy feedback

Single-user WPT

Antenna Architecture of ER

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For enabling CSI acquisition, each ER must have a communication module, in addition to the energy harvesting module

Shared-antenna architecture The same set of antennas used for both energy harvesting and communication Energy harvesting and communication take place in a time-division manner Compact receiver form factor, easy channel estimation But require communication and energy harvesting at the same frequency, and

new frontend design of ER Separate-antenna architecture

Different antennas for energy harvesting and communication, independent and concurrent operations, and commercial off-the-shelf hardware available

Single-user WPT

CSI Acquisition (1): Forward-Link Training with CSI Feedback

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Applicable for shared-antenna architecture only Similar to conventional wireless communications, pilot signals sent by the

ET to the ER for channel estimation ER then feeds back the estimated channel to ET Limitations:

Training overhead scales with the number of antennas at ET, not suitable for massive MIMO WPT

Requires channel estimation and/or feedback by ER, though it does not require CSI for energy harvesting

Single-user WPT

CSI Acquisition (2): Reverse-Link Training via Channel Reciprocity

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Applicable for shared-antenna architecture only Exploits channel reciprocity: ER sends pilot signals to ET for channel estimation Advantages:

No channel estimation or feedback required at ER Time/energy training overhead independent of number of ET antennas, suitable for

massive MIMO WPT Limitations: Critically depends on channel reciprocity (holds in practice?) New design trade-offs:

Too little training: coarsely estimated channel, reduced energy beamforming gain Too much training: consumes excessive energy at ER, less time for energy transfer

Maximize net energy at ER: harvested energy – energy consumed for training

Single-user WPT

Net Harvested Power versus Number of Trained ER Antennas

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rf

Number of ET antennas: =5Number of ER antennas: =10

1 Watt, =-60 dB

t

rt

MM

P β=

Single-user WPT

CSI Acquisition (3): Power-Probing with Energy Feedback

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Applicable for separate-antenna architecture ET sends energy signals with online designed transmit covariance matrices ER measures the amount of harvested energy during each interval ER sends a finite-bit feedback based on its present and past energy measurements ET obtains refined CSI estimation based on the feedback bits

Advantages: Low signal processing requirement at the ER, no need for hardware change Simultaneous energy harvesting not interrupted

Limitations: Training overhead increases with the number of ET antennas

Single-user WPT

Power-Probing with One-Bit Feedback: Case Study

ER k feeds back one-bit information indicating increase or decrease of harvested energy between time slots n and n-1

With one-bit feedbacks, ET Adjusts transmit beamforming for next slot Obtains improved estimation of channels

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Rui Zhang, National University of SingaporeSingle-user WPT

ACCPM Based Channel Learning

Objective: find any point in target set Analytic center cutting plane method (ACCPM): Iteratively shrink working set towards target set. In the nth iteration Find analytic center of working set Find cutting plane whose boundary passes (neutral cutting plane) Cut away half space according to cutting plane to obtain new working set

Q: How to cut half-space? A: Based on one-bit feedback (energy increase or decrease at ER)

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1n−P

X

Cutting planenH

1n n n−= P P H

X

G(n) G(n)~ ~


Convergence Analysis

ACCPM based single user channel learning algorithm obtains estimation for with in at most intervals

Convergence speed only depends on No. of transmit antennas , but not on No. of receive antennas

Reason: Dimension of :

Theoretical bound only, faster convergence is often observed in simulation

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Simulation Result: Baseline Schemes

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Partial CSIT: existing one-bit feedback based channel learning schemes Cyclic Jacobi technique (CJT)

One-bit feedback: increase or decrease in received power Usage of feedback: perform blind estimate of EVD of MIMO channel Application: MIMO, one receiver only

Gradient sign One-bit feedback: increase or decrease in received power Usage of feedback: adjust transmit beam with random perturbation Application: MIMO, one receiver only

Distributed beamforming One-bit feedback: larger or smaller than prior highest received power Usage of feedback: adjust phase of transmit beam Application: MISO, one receiver only


Simulation Result

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ACCPM: best accuracy & convergence performance

Absolute error of harvested power versus No. of feedback intervals


Agenda




Single-user WPT

Multi-user WPT


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Multi-user WPT Rui Zhang, National University of Singapore

Multi-User MIMO Energy Multicasting


Utilize the broadcast nature of microwave propagation for energy multicast Energy near-far problem: fairness is a key issue in the multi-user EB designMultiple beams are needed in general to balance the energy harvesting

performance among users

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Multi-user WPT

Multi-User WPT: Network Architecture

J distributed ETs simultaneously serve K ERs each having multiple antennas Three main networking architectures (with complexity from high to low):1. CoMP (Coordinated Multi-Point) WPT

All ETs jointly design energy signals to the K ERs based on global CSI Only requires exchange of CSI and waveform parameters among ETs, as opposed

to message exchange in CoMP communications2. Locally-coordinated WPT

Each ER is served by a subset of ETs ET-oriented association: group the ETs into clusters, with each cluster ETs

cooperatively serving a subset of ERs ER-oriented association: each ER is freely associated with a subset of ETs

3. Single-ET WPT: each ER served by exactly one ET

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Rui Zhang, National University of SingaporeMulti-user WPT

Multi-User WPT: Power Region Characterization

Considering CoMP-based WPT, the harvested power at the ERs are

Power region: the set of all achievable power tuples by the K ERs

Pareto-boundary: the power-tuples at which it is impossible to increase the power of one ER without reducing that of others

Pareto-boundary characterization (analogous to capacity region in multi-user communications) Weighted-sum-power maximization (WSPMax) Power-profile method

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: MIMO channel from all the ETs to ER : the covariance matrix of the signal transmitted by all ETsk J k

JHS

Multi-user WPT

Weighted-Sum-Power Maximization

The WSPMax problem for power region characterization can be formulated as

Semidefinite programming (SDP) problem, can be efficiently solved by standard convex optimization techniques or existing software toolbox

For single ET with J=1, equivalent to point-to-point MIMO WPT with an equivalent channel

For Pareto boundary with hyper-planes, WSPMax only obtains the vertex points

Time sharing is thus needed in general to attain inner points on the boundary

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1

0 : weight for ER

1

kK

kk

kµ

µ=

≥

=∑

Multi-user WPT

Power-Profile Method for Pareto Boundary Characterization

The power-profile approach for power region characterization solves the problem

SDP problem again, thus can be efficiently solved The optimal solution has rank greater than 1 in general, i.e., multi-beam WPT The same performance can be achieved with single-beam WPT together with

time sharing

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1

0 : weight for ER

1

kK

kk

kα

α=

≥

=∑

Multi-user WPT

Simulation Results

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A WPT system that serves a square area of 30m x 30m with co-located versus distributed antennas

Co-located antennas: a single ET with 9-element uniform linear array (ULA) at the center of the serving area

Distributed antennas: 9 ETs each with single antenna equally spaced in the area

Two single-antenna ERs at (15m, 5m) and (18.88m, 29.49m), which are 10m and 15m away from the area center, respectively

Total transmit power of the system is 2W Simulation 1: maximize the minimum (max-min) harvested power

by the two ERs Simulation 2: find the achievable power region of the two users

Multi-user WPT

Spatial Power Distribution with Max-Min Solution

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(a) Co-located antenna system (b) Distributed antenna system

Power beamed towards the ERs in co-located antenna system More even spatial power distribution for distributed antenna system

Multi-user WPT

Achievable Power Region with Co-located vs Distributed Antennas

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Distributed antenna system improves the performance of ER2 at the cost of degrading the performance of ER1, thus helps mitigating the near-far problem in co-located antenna system

Multi-user WPT

Agenda




Single-user WPT

Multi-user WPT


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Extensions and future work Rui Zhang, National University of Singapore

Nonlinear Energy Harvesting Model (1): Efficiency vs. Input Power

In practice, the RF-DC conversion efficiency varies with input power Energy beamforming needs to take into account this non-linear model


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Harvested Power vs. Input Power with Curve Fitting

The non-linear model can be obtained via curve fitting based on measured data


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Nonlinear Energy Harvesting Model (2): Efficiency vs. Waveform

Waveform with high peak-to-average power ratio (PAPR) tends to give better energy conversion efficiency, thus new waveform design is needed for WPT


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Harvested Power versus Signal PAPR

Waveform optimization by exploiting non-linear energy harvesting model


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Wireless Information and Power Transfer Coexisting


Wireless power transfer coexists with existing communication systems New spectrum sharing models and techniques needed to maximize

spectrum/energy efficiency “Cognitive” wireless information and power transfer

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Near-Field WPT: ``Rezence’’ Standard via Magnetic Resonance Coupling

Main advantages Multi-user charging Real-time charging control support (via built-in Bluetooth communication)

Main limitations Single TX charging unit Near-far fairness issue Lack of efficient magnetic channel estimation technique


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Near-Field WPT: Multi-Transmitter Charging Magnetic beamforming: make TXs’ generated magnetic fields constructively

added at one or more RXs by jointly optimizing the amplitude and phase ofvoltage/current at TXs

Node placement optimization: achieve uniform power over a target region

Different model and design from far-fieldbeamforming since RXs in near-field WPTare in general “coupled” with TXs

(Centralized WPT)(Distributed WPT)

Example: 5 TXs with different placed locations over a disc region


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Near-Far Issue in SIMO Near-Field WPT

Magnetic coupling (i.e., magnetic channel) between two coils decays withthe cubic of their separating distance (∝ 1/𝑑𝑑3)

Near-far problem in multi-user SIMO charging An efficient solution by exploiting the Tx-Rx coupling: jointly optimizing the

load resistance of different RXs

Increasing load resistance at RX 1 (closer to TX) helps increase the deliverable power to RXs 2 and 3 (far users)

But this also results in increased transmit power (i.e. lower efficiency)

Other Extensions & Future Work

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Channel acquisition for WPT in both near-field and far-field (frequency

selective and multi-user channels)

Energy outage minimization in delay-sensitive applications

Distributed channel training and energy beamforming

Massive MIMO and mmWave WPT

WPT with safety and health related constraints

Higher layer (MAC, Network, etc.) design issues in WPT

Hardware development and applications



For more details, please refer to

Y. Zeng, B. Clerckx, and R. Zhang, “Communications and signals design for wireless power transmission,” submitted to IEEE Trans. Commun. (Invited Paper), available online at arxiv/1611.06822 Nov., 2016.

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References

https://arxiv.org/abs/1611.06822

communications and signals design for wireless … 2016 1 communications and signals design for...

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