wireless beyond the third generation— facing the energy...
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Wireless Beyond the Third GenerationWireless Beyond the Third Generation——Facing The Energy ChallengeFacing The Energy Challenge
Jan M. RabaeyBWRCUniversity of California @ Berkeleyhttp://www.eecs.berkeley.edu/~jan
ISLPED 2001, Huntington Beach
It’s all about Laws …It’s all about Laws …
Mo o re ’ s
M o o re ’ s
L awLaw
Sha n n on ’ s
L aw
Sh a n n on ’ s
L aw
Me t c al f e
’ s L aw
Me t c al f e
’ s L aw
Ge n e ’ s L aw
Ge n e ’ s L aw
Maxwe l l ’ s
Ma xwe l l ’ s
L a w sL a w s
L aw s o f P h y s i c s
L aw s o f P h y s i c s
The The FibonacciFibonacci Law on Wireless GrowthLaw on Wireless Growth
Source: Goldman-Sachs
“The number of world-wide wireless subscribers (in tens of millions)grows as a Fibonacci series”
1999 2000 2001 2002 2003
46
57
67
?
The Shift to Wireless DataThe Shift to Wireless Data——The New InternetThe New Internet
Clusters
Massive Cluster
Gigabit Ethernet
Pre-1990:Client-Server Systems
The 2000s:Extending toward the SmallEnabled by integration(Moore’s Law at Work!)and wireless connectivity
The 1990s:Conquering the worldThe network revolution
Courtesy: R. Katz, UCB
(Projected) Growth in 802.11 WLAN(Projected) Growth in 802.11 WLAN
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
2001 2002 2003 2004 2005
1-2Mbps
10-11Mbps
20Mbps+
54 MbpsTotal
Units, k
Source: Cahners In-Stat 2001
The Evolving Wireless SceneThe Evolving Wireless Scene
Range
Dat
a R
ate
1m 10m 100m 1km 10km
1Kb
10Kb
100Kb
1Mb
10Mb
100Mb
Cellular (WAN)
3G Cellular
2.5 G Cellular
802.11 (LAN)
802.1a
Bluetooth (PAN)
Sensor networks
Metropolitan
More bit/secMore bit/secMore bit/($·More bit/($·nJnJ))
Range
Dat
a R
ate
1m 10m 100m 1km 10km
1Kb
10Kb
100Kb
1Mb
10Mb
100Mb
Cellular (WAN)
3G Cellular
2.5 G Cellular
802.11 (LAN)
802.1a
Bluetooth (PAN)
Sensor networks
Metropolitan
More bit/secMore bit/secMore bit/($·More bit/($·nJnJ))
How to Get More bits/sec in aHow to Get More bits/sec in aBandBand--Limited Environment? Limited Environment? The Shannon Bound:In an AWGN channel, the best bandwidth-efficiency (in bits/sec/Hz)that can be achieved with arbitrarily low bit-error rate is given by
bweff ≤≤ log2 (1 + bweff * Eb/N0)
0 5 10 15 20 25 30 35 40 45 500
1
2
3
4
5
6
7
8
9
Energy/bit over Noise Spectral Density Eb/N0
Ban
dwid
th e
ffici
ency
(bi
ts/s
ec/H
z)
Bandwidth EfficientBandwidth Efficient
Energy EfficientEnergy Efficient
1
10
100
1000
10000
100000
0 2 4 6 8 10 12
SNR (db)
Rel
ativ
e C
om
ple
xity
The Cost of Approaching Shannon’s BoundThe Cost of Approaching Shannon’s Bound
Courtesy Engling Yeo, UCB
The Bliss and Challenge of Error CodingThe Bliss and Challenge of Error Coding
8/9 Turbo, νν=4, N=4k
2/3 Turbo, νν=4, N=64k 1,2, and 3 iterations
1/2 Turbo, νν=4, N=64k 1,2, and 3 iterations
8/9 LDPC, N=4k 1,3, and 5 iterations
8/9 Conv. Code, νν=3, N=4k
1/2 Conv. Code, νν=4, N=64k
2/3 Conv. Code, νν=4, N=64k
8/9 Capacity Bound2/3 Capacity Bound
1/2 Capacity Bound
1/2 LDPC, N=107, 1100 iterationsfor BER of 10-5
Dealing with NonDealing with Non--ideal Channels (e.g., fading)ideal Channels (e.g., fading)
• Multi-antenna approach exploits multi-path fading by sending data along good channels
• Results in large theoretical improvements in bandwidth efficiency for fading channels
• But…computationally hungry
)(ty
ArrayProcessing
)(tx
ArrayProcessing
1st path, α1 = 1
2nd path, α2 = 0.6
SNR (dB)0 5 10 15 20 250
5
10
15
20
25
30
Cap
acity
(bi
ts/s
/Hz)
(4,4) With Feedback(4,4) No Feedback(4,1) Orthogonal Design(1,1) Baseline
The Cost of Dealing with NonThe Cost of Dealing with Non--ideal Channelsideal Channels
0
1000
2000
3000
4000
5000
6000
7000
Performance
MIPS
0.8 Mb/s0.9 b/s/Hz
1.6 Mb/s1.8 b/s/Hz
1.9 Mb/s2.1 b/s/Hz
3.8 Mb/s4.2 b/s/Hz
5.6 Mb/s6.3 b/s/Hz
Data rate per userSpectral efficiency
* Assume 25 MHz bandwidth and 28 users
MatchedFilter
Multi-UserDetector
OFDM +Coding
OFDM +Multi-Antenna
OFDM + Multi-Antenna + Coding
Source: Ning Zhang, UCB
Compelling Wireless Implementation IssuesCompelling Wireless Implementation Issues
•• A Ferocious Quest for PerformanceA Ferocious Quest for Performance–– Driven by the hunger for bits/secDriven by the hunger for bits/sec
–– Outstripping the technology evolutionOutstripping the technology evolution
•• With a Premium on Reduction in Energy With a Premium on Reduction in Energy ConsumptionConsumption–– The compelling argument behind wireless is its The compelling argument behind wireless is its
untethered untethered naturenature
–– Power consumption key impediment to penetration of Power consumption key impediment to penetration of new servicesnew services
–– Energy sources on slow evolutionary path (5%/year)Energy sources on slow evolutionary path (5%/year)
What Technology Offers UsWhat Technology Offers UsGene (Frantz)’s LawGene (Frantz)’s Law
Gene’s Law
DSP Power
1,000
100
10
1
0.1
0.01
0.001
0.0001
0.00001
mW
/MIP
S
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
YearSource: Gene Frantz (TI)
Energy Efficiency of DSPs Doubles Every
18 Months
Shannon beats Moore beats ChemistsShannon beats Moore beats Chemists
1
10
100
1000
10000
100000
1000000
10000000
1980
1984
1988
1992
1996
2000
2004
2008
2012
2016
2020
Algorithmic Complexity(Shannon’s Law)
Processor Performance (~Moore’s Law)
Battery Capacity1G
2G
3G
Courtesy: Ravi Subramanian (Morphics)
The Need for FlexibilityThe Need for Flexibility• Cost-of-design issues point towards component
reuse– Design complexity impacts time-to-market– Physical effects increase verification costs and design risk
– NRE of new designs is increasing significantly (mask making, fab cost)
• Multi-standard has become a must in the diverse wireless landscape
• Adaptive solutions lead to better spectral utilization• A wide variety of unpredictable services
An Attractive Option:An Attractive Option:MultiMulti--Processor SystemProcessor System--onon--aa--ChipChip
Courtesy: Chris Rowen, Tensilica
Copyright Tensilica, Inc 2001
“The New NAND gate”
Flexibility Comes at a Huge CostFlexibility Comes at a Huge Cost
µP
Prog Mem
MACUnit
AddrGenµP
Prog Mem
µP
Prog Mem
SatelliteProcessor
DedicatedLogic
Satellite
Processor
SatelliteProcessor
GeneralPurpose
µP
Software
DirectMapped
Hardware
HardwareReconfigurable
Processor
ProgrammableDSP
Fle
xibi
lity
Fle
xibi
lity
InefficiencyInefficiency
3 orders of magnitude!3 orders of magnitude!
500 pJ/op
0.5 pJ/op
The OpportunityThe Opportunityof Configurable Architecturesof Configurable Architectures
Power (mW)
0
50
100
150
200
250
DSP
(T
IC
54)
DSP
Ext
ensi
on
Con
figu
rabl
e
Ded
icat
edH
ardw
are
Execution
Memory
Control
Clocking
Area (mm^2)
DSP
(T
IC
54)
DSP
Ext
ensi
on
Con
figu
rabl
e
Ded
icat
edH
ardw
are
* Based on the implementations of a multi-user detector
Source: N. Zhang, UCB
The Opportunity of ReconfigurableThe Opportunity of Reconfigurable——When Does it Work? When Does it Work?
* All results are scaled to 0.18µm
101
102
103
103
104
105
106
107
108
FFT sizeT
rans
form
s/se
c/m
m2
2 ) Function-specific reconfigurable hardwareData-path reconfigurable processor FPGA Low-power DSP High-performance DSP
101
102
103
10-10
10-9
10-8
10-7
10-6
10-5
10-4
10-3
FFT size
J/T
rans
form
Lower limit Function-specific reconfigurable hardwareData-path reconfigurable processor FPGA Low-power DSP High-performance DSP
Source: N. Zhang, UCB
Energy and Area Efficiencyof Various FFT Implementations
ReconfigurableDataPath
ReconfigurableState Machines
Embedded uP+ DSPs
FPGA
DedicatedDSP
The Ideal “RadioThe Ideal “Radio--onon--aa--Chip” PlatformChip” Platform
• Heterogeneous• Matches the computational
model• Provides flexibility only where
needed and desirable and at the right granularity
• Supports massive concurrency
• Operates at minimum supply voltage and clock frequency
Combines performance, flexibility and energy-efficiency
An Orthogonal Approach to Bit/secAn Orthogonal Approach to Bit/sec——UltraUltra--Wide Band RadioWide Band Radio
Traditional Sinusoidal, Narrowband
Frequency
Time
Time
Frequency
Impulse, Ultra-Wideband
Splurge on Bandwidth (> 5 GHz) and Punt on Bit/sec/HzPossible advantages: easy co-existence, low-power, simple
Digital PulseDigital Pulse--Based RadioBased RadioSimple Digital Architecture:
• Transmit Only Narrow Pulses (No Carrier Frequency)• Spread Energy Over Existing Noise Floor
A/DV
-+ V
-+
The Architectural Challenge:Providing accurate timing resolution without high-frequency clocks!
Predicted performance: 100 kbits/sec @ < 10-4 bit/sec/Hz and ~ 10 nJ/bit
Range
Dat
a R
ate
1m 10m 100m 1km 10km
1Kb
10Kb
100Kb
1Mb
10Mb
100Mb
Cellular (WAN)
3G Cellular
2.5 G Cellular
802.11 (LAN)
802.1a
Bluetooth (PAN)
Sensor networks
Metropolitan
More bit/secMore bit/secMore bit/($·More bit/($·nJnJ))
More Bits/(More Bits/(nJnJ·$·mm·$·mm33):):Wireless Sensor NetworksWireless Sensor NetworksPushing the Bounds in Pushing the Bounds in Ultra [Small, Cheap, LowUltra [Small, Cheap, Low--Power]Power]
The Smart BuildingThe Smart BuildingIntegrated Sensor/Actuator/Control System• Improves quality-of-living• Saves energy• Provides security• Helps localizing items• Extends building-human interface
Berkeley Berkeley PicoRadio’sPicoRadio’sMeso-scale low-cost radio’s for ubiquitous wireless data acquisition in sensor/actuator networks that are fully integratedand consume less than 100 µµW enabling energy scavenging
The EnergyThe Energy--Scavenging OpportunityScavenging Opportunity
0
1
10
100
1000
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5Years
µµW
atts
Lithium
Zinc-Air
NiMH
Li (rechargeable)
Solar
Vibrations
Alkaline
Battery size: 0.5 cm3
Vibration: 1 cm2 piezo-electricSolar: 1 cm2 single-crystal
Courtesy: S. Roundy (UCB)
Opportunity: Metcalfe’s LawOpportunity: Metcalfe’s Law
“The true value of a network increases as the square of the number of users on the network”
A Variant: Jan’s LawA Variant: Jan’s Law“The power efficiency of a wireless sensor node increases as the square of the number of nodes in the network (or is proportional to the node density).”
Addressing the Communication CostAddressing the Communication Cost
-100
-80
-60
-40
-20
0
20
1 10 100
Distance (in m)
Tran
smit
Pow
er (i
n db
M) f c
= 2.4 GHz
f c= 0.43 MHz
Bluetooth
(assuming d4 path loss of and 10 kB/sec data rate)
• Minimum required transmit power increases as d4 due to ground wave and multi-path
• Increasing carrier frequency costs 20db/decade
16 pJ/bit
Adding a Single Relay Point in a Adding a Single Relay Point in a Wireless LANWireless LAN
Source: M. Kubisch and H. Karl, TU Berlin
Bit-rate: 6 Mb/secPacket Error Rate: 1%Fixed Receiver Power: 100 mWPath Loss Exp.: 3.8d1/d2 =1
Reduces energy/bitup to 4 times!
node range
TradingTrading--off Latency for Energy:off Latency for Energy:SelfSelf--configuring Multiconfiguring Multi--hop Networkshop Networks
sensoractuator
controller
• 1 hop over 50 m1.25 nJ/bit
• 5 hops of 10 m each5 × 2 pJ/bit = 10 pJ/bit
• Multi-hop reduces transmission energy by 125!
But …how to ensure fairness?But …how to ensure fairness?
EnergyEnergy--Conscious NetworkingConscious NetworkingSimulated Energy DissipationSimulated Energy Dissipationin Sensor Networks (BWRC)in Sensor Networks (BWRC)
Performance-oriented
Energy-Conscious
Po
wer
Co
nsu
mp
tio
n
Source: R. Shah (UCB)
The SensorThe Sensor--Node RF ChallengeNode RF Challenge
• Increasing carrier frequency increases power dissipation– Mostly due to higher speed
active components (synthesizers, mixers, A/Ds)
• But enables higher integration– Smaller sizes of passives
ands antennas0.1
1
100.1 1 10 100 1000
Receiver Power Consumption (mW)
Car
rier
Fre
quen
cy
Rx power consumption versus carrier frequencyfor a number of low-data rate, small-distance RF implementations(all operate in Shannon’s “energy-efficient zone”)
Eliminating most HighEliminating most High--Speed ComponentsSpeed ComponentsSubSub--sampling receiver with passive sampling receiver with passive frontendfrontend
RF Filter LNA RF Filter AD
fbase
Image Rejection
Provides diversityShapes LNA thermal noise
RF Filter
RF Filter
RF Filter
• Does not requireany high-frequencyactive components
• Receive energy reduced by 1-2 ordersof magnitude to ~ 5 nJ/bit
Enabled by HighEnabled by High--Q Integrated FiltersQ Integrated Filters
-
RF-MEMS: Poly Si-Ge Resonator
Thin-Film Bulk Acoustic Resonators Q > 1000 @ 2 GHz(FBAR – Agilent)
The Importance of Power Management The Importance of Power Management •• Activity in sensor (data) networks is low and random (< 1%)Activity in sensor (data) networks is low and random (< 1%)• Receiving a bit is computationally more expensive than
transmitting one • Most Media Access protocols assume that the receiver is
always on and listening!
Why not power transceiver up for real events only Why not power transceiver up for real events only (incoming data, sensor event, network maintenance)?(incoming data, sensor event, network maintenance)?
Reactive MediaReactive Media--Access ControlAccess Control
Truly Reactive Messaging at the Physical and Media-Access Levelv Power Down the Whole Data Radiov Reduces Monitoring Energy Consumption by 103 Timesv Wa keup Radi o Power’ s Up Dat a Radi o f or Dat a Recept i on
Sleeping nodes
Communicating nodes
The WakeThe Wake--up (Reactive) Radioup (Reactive) Radio
PAPulse
Generator
RF Filter
RF Filter
RF Filter
Transmit
RF Filter LNA RF Filter AD
RF Filter
RF Filter
RF Filter Receive
EnergyDetector
PulsePositionDetector
Wake-up
• Always running– Super low power:
10-4~ 10-3 active mode power
• Data radio shut down when idle, and powered up by wake-up radio
• Receiver response time: < 10ms
Receive SessionWakeup
Tone
What it Ultimately Boils Down ToWhat it Ultimately Boils Down To——PowerPower--Profile of PicoRadio Profile of PicoRadio (Projected)(Projected)
Clock distribution
14%
Reconfigurable protocol stack
25%
Reactive receiver 1%
Radio receiver12%
Radio transmitter
5%
Baseband13%
Embedded microprocessor
30%
Clock distribution
14%
Reconfigurable protocol stack
25%
Reactive receiver 1%
Radio receiver12%
Radio transmitter
5%
Baseband13%
Embedded microprocessor
30%
Summary/PerspectiveSummary/Perspective• Both the bits/sec/Hz and the bits/nJ quests create
formidable energy challenges• Keep your eyes open for innovative, orthogonal
approaches that re-stack the cards– There is a whole lot of unexplored land available > 10 GHz
• In the end, it are the laws of physics that provide the ultimate bounds
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