Ultra-low power and ultra-low cost wireless sensor nodes

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Transcript Ultra-low power and ultra-low cost wireless sensor nodes

Ultra-low power and ultra-low cost
wireless sensor nodes
An integrated perspective
Jan M. Rabaey
EECS Dept.
Univ. of California, Berkeley
PicoRadio’s ─ The Original Mission
Meso-scale low-cost radio’s for ubiquitous wireless
data acquisition that
• are fully integrated
–Size smaller than 1 cm3
• minimize power/energy dissipation
– Limiting power dissipation to 100 mW
enables energy scavenging
• and form self-configuring ad-hoc networks
containing 100’s to 1000’s of nodes
Still valid, but pushing the limits ever further
The Incredibly Shrinking Radio
OSC1
MOD1
OSC2
PA Test
MOD2
4 mm
LNA
Test
TX1
Passive
Test
Structures
Receiver
Env Det
Test
TX2
RF Amp Test
fclock
RF Filter
Diff
Osc
RF Filter
Env
Det
RF Filter
Env
Det

LNA
fclock

RX
RX
On:
On:33mW
mW
Off:
Off:00mW
mW
Preamp
PA
Matching
Network
TX
TX
On:
On:44mW
mW
Stby:
Stby:11mW
mW
Off:
Off:00mW
mW
• Technology: 0.13 mm CMOS
combined with off-chip FBARs
• Carrier frequency: 1.9 GHz
• 0 dBm OOK
• Two Channels
• Channel Spacing ~ 50MHz
• 40 kbps/channel
• Total area < 8 mm2
Wireless Sensor Network Protocol Processor
64K
memory
Neighbor
List
Locationing
Engine
Base
Band
Voltage
Conv
GPIO
Serial
Interface
Interface
DW8051
μc
System
Supervisor
Network
Queues
DLL
In fab (Jan 04)
Technology
0.13μ CMOS
Chip Size
3mm x 2.75mm =
8.2 mm2
Transistor Count
3.2M
Gate Count
62.5K gates
Clocks Freqs
16MHz(Main),
1MHz(BB)
On Chip memory
68Kbytes
Core Supply
Voltages
1V(High) –0.3V(Low)
On_Power
< 1 mW
Standby Power
mWs
Integrates all digital protocol
and applications functions of
wireless sensor node
Runs reliable and energy-optimized
protocol stack (from application level down)
The Road towards a First Integrated PicoNode
Digital
Network
Processor
16kB
CODE
Flash
Storage
4kB
XDATA
256
DATA
Chip
Supervisor
DW8051
20MHz
Clock Source
Serial
Powertrain
Solar Cell
sfrbus or membus?
FlashIF
SIF
ADC
MAC
Voltage
Voltage
Supply
Voltage
Supply
Supply
SIF
LocalHW
Serial
GPIO
ADC
PHY
Sensor1
Sensor2
User
Interface
PrgThresh0 PrgThresh1
OOK
Receiver
Tx0
Tx2
RF Transceiver
OOK
Transmitter
SIF = sensor interface
Energy-Scavenging becoming a Reality
• Demonstrate a self contained 1.9GHz transmitter - powered only by Solar &
Vibrational scavenged energy
• Push integration limits - limited by dimensions of solar cell
Front
Front
regulator
cap
Tx COB
Light Level
Low Indoor Light
Fluorescent Indoor Light
Partly Cloudy Outdoor Light
Bright Indoor Lamp
High Light Conditions
Vibration Level
2.2m/s2
5.7m/s2
Duty Cycle
0.36%
0.53%
5.6%
11%
100%
Duty Cycle
1.6%
2.6%
Perspectives: Where are we heading?
• Extrapolating towards the future: how far
can we push cost, size, and power?
– Ultra-dense sensor networks (“smart surfaces”)
enabled by sub 10 mW nodes.
– Cutting RF power by at least another factor of 5 (if
not more)
– Pushing the boundaries on voltage scaling
• Focus on the application perspective
– A Service-based Application Interface for Sensor
Networks
– Focus on issues such as portability, universality ,
scalability, and ad-hoc deployment
An Application Perspective to Sensor Networks
A plethora of implementation strategies emerging, some
of them being translated into standards
TinyOs/TinyDB
The juggernaut is rolling … but is it the right approach?
• Bottom-up definition without perspective on interoperability and portability
• Little reflection on how this translates into applications
A Quest: A Universal Application Interface
(AI) for Sensor Networks
•
•
•
•
Supports essential services such as queries, commands, time
synchronization, localization, and concepts repository
Similar in concept to the socket interface in the internet
Provides a single point for providing interoperability
Independent of implementation architecture and hardware platform
–
Allows for alternative PHY, MAC, and Network approaches and keeps the door open
for innovation
Application
Application Interface
Query/Command
Service Layer
Naming
SNSP
Time/Synchronization
Network Layer
Location
SNSP Status (joint project with
GSRC (ASV) and TU Berlin)
• White paper completed and in feedback gathering
mode (http://bwrc.eecs.berkeley.edu/research/picoradio/...)
• Very positive support so far (both from industry
and academia)
• Next targets:
– Further evolve document (start working group)
– Demonstrate feasibility by implementation on at least two
test beds
– Address number of issues left open for research (e.g.
implementation approaches for naming, synchronization,
localization, and concept repository services)
• Currently in process of acquiring funding (NSF,
European Commission, CEC, …)
Extrapolation of the low-power theme:
Ultra-dense sensor networks
• How to get nodes substantially smaller and
cheaper (“real” mm3 nodes): get them closer, use
lots of them, and make their energy consumption
absolutely minimal (this is < 10 mW).
• “Smart surfaces”: plane wings, smart
construction materials, intelligent walls
• How to get there? Go absolutely non-traditional!
– Use non-tuned mostly passive radio’s – center
carrier frequency randomly distributed
– Use statistical distribution to ensure reliable data
propagation
On the Road:
Reducing RF power by another factor of 5
• Providing gain at minimal current: The Super-regenerative
Receiver
1500mm
• 400mA when active
(~200mW with 50%
quench duty cycle)
1200mm
• Fully Integrated
Back from fab any day
Realizing sub-50 mW receivers
Example: sub-threshold RF oscillator
using integrated LCs (in fab)
Simulated Performance
Supply voltage
0.5 – 1.2V
Current
consumption
150μA
Oscillation
frequency
1.5GHz
Differential
output swing
150mV
(Vdd=500mV)
Phase noise
-100dBc/Hz
@1MHz offset
Next step: mostly untuned radio’s and lots of them
Combine with purely statistical routing (in collaboration with Kannan)
Ultra-Low Voltage (ULV) Digital Design
• Aggressive voltage scaling the premier way of reducing
power consumption; Performance not an issue
• Our goals: design at 250 mV or below
• Challenges:
– Wide variation in gate performance due to variability of thresholds
and device dimensions
– Sensitivity to dynamic errors due to noise and particle-caused
upsets (soft errors)
 Explore circuit and architecture techniques that deal with
performance variations and are (somewhat) resilient to
errors!
TM
TM
Tcl
TM
Tcl’
asynch.
TM
Time reference
Chip Supervisor
synch.
Idea: Self-adapting
approach to ULV
Status: White paper