Embracing Randomness Embracing Randomness ––A Roadmap to Truly Disappearing ElectronicsA Roadmap to Truly Disappearing Electronics

I&C Research Days Lausanne I&C Research Days Lausanne –– July 8, 04July 8, 04

Jan M. RabaeyJan M. Rabaeyand the PicoRadio Groupand the PicoRadio GroupBerkeley Wireless Research Center

Department of EECS, University of California, Berkeley

http://bwrc.eecs.berkeley.edu

Year

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Meaning in the Device

Meaning in the Connection

Meaning in the Collection

Bell’s Law: A New Computer Class Every 10 YearsBell’s Law: A New Computer Class Every 10 Years

Source: R. Newton

1940’s 2000’s

““Ambient Intelligence” (The Concept)Ambient Intelligence” (The Concept)

• An environment where technology is embedded, hidden in the background

• An environment that is sensitive, adaptive, and responsive to the presence of people and object

• An environment that augments activities through smart non-explicit assistance

• An environment that preserves security, privacy and trustworthiness while utilizing information when needed and appropriate

Fred Boekhorst, Philips, ISSCC02

Tackling Societal Tackling Societal Scale ProblemsScale Problems

Infrastructure maintenance

Trafficmanagement

Medical

Energymanagement

Smart buildings

Disaster Mitigation

The Technology is Not Quite There YetThe Technology is Not Quite There YetFrom 10’s of cm3 and 10’s to 100’s of mW

To 10’s of mm3 and 10’s of µW

Meso-scale low-cost wireless transceivers for ubiquitous wireless data acquisition that• are fully integrated

– Size smaller than 1 cm3

• are dirt cheap (“the Dutch treat”) – At or below 1$

• minimize power/energy dissipation– Limiting power dissipation to 100 µW

enables energy scavenging

• and form self-configuring, robust, ad-hoc networks containing 100’s to 1000’s of nodes

The Road to Truly Disappearing ElectronicsThe Road to Truly Disappearing Electronics

Berkeley PicoRadio ProjectBerkeley PicoRadio Project

Energy/Power as the Limiting FactorEnergy/Power as the Limiting Factor

--200Vibrations

--17Pressure Variation

--380Air flow

--330Human Power

--40Temperature

--10Solar (inside)

--15000Solar (outside)

0.5216400.52Radioactive(63Ni)

1063346-Heat engine

1.6-3.250-100-Ultra-capacitor

1103500-Micro-Fuel Cell

341080-Secondary Battery

902880-Primary Battery

P/cm3/yr(µW/cm3/Yr)

E/cm3

(J/cm3)P/cm3

(µW/cm3)Power Source

Courtesy Shad Roundy (ANU and UCB)

Reasonable Target: 100 µW/cm3(/year)

Practical Means of Energy ScavengingPractical Means of Energy Scavenging

Capacitive converter usingMEMS micro-vibrator 30 µW/cm3 (on microwave oven)

Piezoelectric bi-morphs

Photovoltaic

PZT

PVDF

10-1500 µW/cm2

90 µW/cm3

[Shad Roundy (IML,UCB)]

Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node

Baseband(mixed-signal)

RF+ Antenna

ClockGeneration

DigitalProcessor(s)

PowerSupply

NetworkSensors

Some Overall GuidelinesSome Overall Guidelines• Keep it simple!• Minimize the supply voltage and the ambient currents as much as possible• Aggressive use of new technologies (RF-MEMS, integrated passives, …)• Manufacturability is key

Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node

Baseband(mixed-signal)

RF+ Antenna

ClockGeneration

DigitalProcessor(s)

PowerSupply

NetworkSensors

64Kmemory DW8051

µc

BaseBand

SerialInterface

GPIOInterface

LocationingEngine

Neighbor List

SystemSupervisor

DLL

NetworkQueues

VoltageConv

• Simplest possible processor• Dedicated accelerators when needed• Aggressive power management• 1V supply, 16 MHz clock• 300 mV standby voltage• < 1 mW in full operation; < 1 µW standby

Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node

Baseband(mixed-signal)

RF+ Antenna

ClockGeneration

DigitalProcessor(s)

PowerSupply

NetworkSensors

Energy generation and conversion network

Energy Source 1(solar)

Energy Source 2(vibration, …)

Conversion

Netw

ork 1

Conversion

Netw

ork 2

Reservoir 1(capacitor)

Reservoir 2(microbattery)

Microbattery

Anchor Spring flexure Comb fingers

Electrostatic MEMS vibration converters

Towards a subTowards a sub--100 100 µµW Integrated NodeW Integrated Node

Baseband(mixed-signal)

RF+ Antenna

ClockGeneration

DigitalProcessor(s)

PowerSupply

NetworkSensors

1 µW oscillatorWineglass MEMS resonator

MEMS resonator die flips directly onto CMOS for a compact, integrated clock

module.

LowLow--Power RF: Back to The FuturePower RF: Back to The Future(Courtesy of Brian Otis)(Courtesy of Brian Otis)

D. Yee, UCB

© 2000 - Direct Conversionfc= 2GHz>10000 active devicesno off-chip components

© 1949 - superregenerativefc= 500MHz2 active deviceshigh quality off-chip passives - hand tuning

Back to the FutureBack to the Future

MatchingNetwork

MOD1

MOD2

OSC1

OSC2 Preamp PA

• Minimizes use of active components – exploits new technologies• Uses simple modulation scheme (OOK)• Allows efficient non-linear PA• Down-conversion through non-linearity (Envelope Detector)• Tx and Rx in 1-2 mW range (when on)

FBARFBAR--basedbased

RF Filter A

fclockRF Filter

EnvDet

∫

fclockRF Filter

EnvDet

∫

Thin-Film Bulk Acoustic Resonator

The Incredibly Shrinking RadioThe Incredibly Shrinking Radio

RF Filter LNA

fclock

RF FilterEnvDet ∫

fclock

RF FilterEnvDet ∫

RF Filter LNA

fclock

RF FilterEnvDet ∫

fclock

RF FilterEnvDet ∫

RXOn: 3 mWOff: 0 mW

RXOn: 3 mWOff: 0 mW

MatchingNetwork

MOD1

MOD2

OSC1

OSC2 Preamp PAMatchingNetwork

MOD1

MOD2

OSC1

OSC2 Preamp PA

TXOn: 4 mW

Stby: 1 mWOff: 0 mW

TXOn: 4 mW

Stby: 1 mWOff: 0 mW

• 130 nm CMOS• Carrier frequency: 1.9 GHz• 0 dBm OOK• Channel Spacing ~ 50MHz• 10-160 kbps/channel• 10 µs start-up time• Total area < 5 mm2

FBAR

Light Level Duty Cycle

Low Indoor Light 0.36%

Fluorescent Indoor Light 0.53%

Partly Cloudy Outdoor Light 5.6%

Bright Indoor Lamp 11%

High Light Conditions 100%Vibration Level Duty Cycle

2.2m/s21.6%

5.7m/s22.6%

An exercise in miniaturization and energy scavenging

Antenna(ceramic)

Single solar cell

Regulator

RF Transmitter

Energy StorageCapacitor (10 µF)

PicoBeaconPicoBeacon: An Energy: An Energy--Scavenging RadioScavenging Radio

The Return of SuperThe Return of Super--regenerativeregenerative• Fully Integrated Receiver

Front-end

• 400µA when active(~200µW) with 50% quench duty cycle

1500µm

1200

µm

OOK modulated(80 dbm signal)

“1”

“0”

How to go even further?How to go even further?Trading off accuracy for power!Trading off accuracy for power!

Example: sub-threshold RF oscillatorusing integrated LCs

124mV

1.354 GHz

3-layer inductor

150mV

1.5GHz

Simulations

76mVDiff. Output Swing

1.452 GHzOscillation Frequency

2-layer inductor

Measurement bias conditions: Vdd=0.5V, Itail=400µA

2.4 ns start-up time

The Roadmap to UltraThe Roadmap to Ultra--dense Networksdense NetworksTrading off “accuracy” for powerTrading off “accuracy” for power

Super-regenerative:< 500 µW

Untuned Subthreshold< 50 µW

Resonant bodyFinfet (NEMS)

Untuned mostly passive< 5 µW

The Challenge: Simplicity Threatens ReliabilityThe Challenge: Simplicity Threatens Reliability

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PicoRadio Meeting NAMP Meeting

-36 -35 -34 -33 -32 -31 -3010

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effective path loss

BE

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20 kbps, +1.5dBm40 kbps, +3dBm80 kbps, +4.5dBm

6 db

Factor 105 inerror rate

Narrowband radios very sensitive to fast fading

effects

A Host of Reliability IssuesA Host of Reliability Issues

• Channels are unreliable– Rapidly changing multi-path environment

• Nodes are inherently unreliable– May appear at will– May move– May temporarily run out of energy– May break down

• Cost and power concerns explicitly decrease reliability– Narrow-band radios increase sensitivity to fast fading– Nodes are duty cycled to preserve energy– Further reductions in power affect tuning and calibration

• Other issues such as sensor calibration …

Providing RobustnessProviding Robustness• Traditional radio’s provide robustness

through diversity:– Frequency: e.g. wide-band solutions (hopping)– Time: e.g. spreading– Spatial: e.g. multiple antenna’s

• All these approaches either come with complexity, synchronization, or acquisition overhead, or might not even be applicable– Data traffic irregular, and in very short bursts

• A more attractive approach: – Exploit redundancy– Embrace randomness

Exploiting Redundancy and Exploiting Redundancy and Randomness at the Network Level Randomness at the Network Level

Multi-hop sensornetwork

• Multi-hop approach reduces transmission overhead• Shortest path algorithm seems to be the optimal choice• But …

- Tends to exhaust some paths faster

- Breaks down in presence of unreliable nodes

R. Shah et al, 2003.

The Impact of Spatial DiversityThe Impact of Spatial Diversity

Adding a single node already changes broadcast reliabilitydramatically – spatial diversity is the preferred way toprovide robustness in sensor networks

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distance [cm]

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Deepfade due tomultipath

2 nodes

3 nodes

Data gathered usingPicoNodeI testbed

RegionRegion--based Opportunistic Routingbased Opportunistic Routing

One-hop neighbors

Forwarding region

Opportunistic routing:• Network specifies forwarding region• MAC “randomly” chooses next-hop based on connectivity• Improves reliability and energy efficiency

Probability of packet successE

nerg

y pe

r no

de

Maximizing SleepMaximizing Sleep--TimeTime

Dominated bychannel monitoring power

Dominated by TX (+RX) power

Parameters:• 3 packets/sec• 200 bits/packet• 20 bit pre-amble• 5 neighbors• Range: 10 m• Synchronization using cycled receiver with Ton/T = 0.1

*based on analytical model including actual PicoRadio power numbers

Average power of node

En-Yi Lin et al, ICC 2004

Maximizing SleepMaximizing Sleep--TimeTimeA pseudoA pseudo--asynchronous approach: The Cycled Receiverasynchronous approach: The Cycled Receiver

Allows deep sleep mode of node at the expense ofrendez-vous overhead (power and time)

How to choose the wake-up periodicity?

Every node wakes up occasionally and asks for “work”

DATA (Tp)

ACK (Tb)

TwaitSrc

T

Dest

Wakeup beacon (Tb)

Randomizing the Sleep DisciplineRandomizing the Sleep DisciplineSLEEP IF YOU CAN• If the node is not necessary, goes to sleep and saves power• Maintain sufficient connectivity• Create a sense of “virtual density”• Allows nodes that run low in power to back off

Given:1. Loss rate2. Delay constraint3. Data generation

requirement

Choose wake-up time• Adaptive

• Traffic & node density• Random

• Exponentially distributed sleeping times.

• Avoid phase synchronization.

Incoming traffic

Incoming traffic

ControllerSensors

For how long should the node be allowed to sleep ?

Maximizing the SleepMaximizing the Sleep--TimeTime

JanaVan Greunen et al, ICC 2004

Duty-cycle as a function of density & channel quality

Changing densities

Deteriorating channel

• Nodes estimate traffic and density based on per-hop delay.• Adaptively change their mean wake-up time based on estimated wake-up rate and latency requirements• Sleep time an exponential random variable

Under all network conditions, only 1% ofthe packets fail to meet the latency constraints

Going One Step Further:Going One Step Further:NarrowNarrow--band band UntunedUntuned RadiosRadios

fLO

Dis

trib

utio

n ftol

freq

Carrier-frequency variance much larger than the bandwidthChallenge: How to make these unmatched radios communicate?

A Statistical Communication ParadigmA Statistical Communication Paradigm“Strength in Numbers”“Strength in Numbers”

1 2 3 … H

DestinationSource

“Random frequency multi-hopping”• Information packet traverses from source to destination in a multi-hop fashion.• Transmitter broadcasts signal to neighboring block on random channel (as determined by process variations).• Receivers randomly select channel to listen to.

Forwarding node

1 2 3 4 5 K…4 Rx’s 1 Rx 6 Rx’s2 Rx’s

No Tx Collisions Receptions

Legal transmission only when single TX, multiple RX

A Statistical Communication ParadigmA Statistical Communication ParadigmSome Amazing Properties• Reliable communication over this unreliable platform indeed possible.• Even more, reliability improves EXPONENTIALLYwith a linear increase in network density.

Too many Tx’s cause collisions

Few Tx’sclean channels

• And the process is self-regulating

D. Petrovic et al., 2004

Summary And PerspectivesSummary And Perspectives• Scaling of technology leads to ever smaller

communication and computation nodes• Severe energy (power) constraints can only

be met by compromising on complexity (or size).

• But simple nodes/algorithms tend to be unreliable …

• An appealing solution: exploit the power of the numbers, and avoid brittleness by embracing randomness

• An opportunity for bold innovation!

The support of CEC, NSF, DARPA, GSRC Marco, and the BWRC sponsoring companies is greatly appreciated.

"Research is what I'm doing when I don't know what I'm doing."– W. Von Braun