Prsentation PowerPoint

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INTEGRATION TECHNOLOGIES FOR AUTONOMOUS WIRELESS
SENSORS
Hughes.Metras_at_cea.fr
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Sommaire

• Functional blocks
• Applications
• Enabling technologies
• Energy scavenging, storage and management
• Sensors sensor interfaces
• Data transmissions (standards, RFID, RF, UWB)
• System design and IC design issues
• Conclusions

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Functional blocks of wireless sensors

• actuation/sensing
• wireless connectivity
• embedded intelligence
• energy management

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Silicon Technologies Trends
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Applications mobile terminals
MIMOSA

• MIMOSA vision the mobile terminal serves as a
  user interface to ambient intelligence and as a
  gateway between local (sensor) information and
  global mobile services
• The architecture is open for development of
  different vertical applications (well-being,
  health, home automation, etc.)
• 15 partners, 6 countries
• ST Microelectronics
• Nokia
• Legrand
• Suunto
• Sonion

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Context capturing
FP6 Call 4 Mobile systems beyond 3G

• Provide heterogeneous wireless sensor network
  solutions to enable Context Capturing to make
  Ambient networks Intelligent, in particular
  wireless and mobile systems beyond 3G thus
• To enable truly Multi-sensory and Personal mobile
  applications and services as well as assisting
  mobile communications through sensor information

25 partners Philips, IBM, EADS, Thales,
Telefonica, Fujitsu, Mitsubishi, Coordinator
LETI
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Applications health/fitness
Sensewear
Suunto
CEA-LETI

• Challenges and future needs
• motion capture, speed,
• integration within textiles, large area low cost
  electronics
• Physiological parameters monitoring (lactate,
  glucose,)

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Applications transports

• health monitoring (P,T, HUM, VIB)

• Accelerometers

Source EADS

• tire pressure sensors

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Applications environment security

• Industrial plants

• forest fire detection

• structural health monitoring

• Parasits in homes forests

• Homeland security

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Energy Scavenging Energy Storage
Energy storage
Micro Fuel cells
Energy scavenging 1,3 mV, 3V, 0,8 Hz
Thickness 10 µm Surfacic capacity 100
µAh/cm² Discharge peak current 500 µA/cm² to 1
mA/cm2
Li Ion batteries
Source MIT Medialab
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Energy Management
mC

• Monitoring

• Vdd1

• Adaptation

• Up
• Converter

• Command

• Down
• Converter

• Vdd2

DC/DC

• Logic (HW/SW)
• Adaptation to available energy
• Dynamic power supply management
• Wake up and idle mode

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Sensors

• Humidity

• Pressure sensor

• Accelerometer

• Temp
• Force
• Chemical
• Bio

• Magnetometer

• Gyroscope

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Sensor Interfaces
Temperature Sensor
Corrections Gain, Bias, T
Capteur
ADC
Signal Conditionning
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Wireless communications standards
Distance
Graphics
HiFi Audio
Digital Video
Multi-channel Video
Text
Internet
Video streaming
100 km
802.16 WI-Max
GSM/CDMA
GPRS/3G
LMDS
10 km
WAN
1 km
802.11.a/b/g Wi-Fi/HL
100 m
LAN
802.15.4 Zigbee, UWB
10 m
802.15.1 Bluetooth
802.15.3 UWB
PAN
1 m
BAN
10 kbits/s
100 kbits/s
1Mbits/s
10 Mbits/s
100 Mbits/s
Débit
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Contactless links (RFID)
POWER

• Inductive coupling
• Magnetic field (Near field) at 13,56 MHz
• Antenna Bobine

2 fonctions élémentaires 1- Power Transfer
2- Bi-directional data transfer
DATA
POWER

• Electrical coupling
• Electric field (Far field) at 868 MHz, 2,45 GHz
• Antenna planar or filaire ou planaire

DATA

• Fe 200Hz, SD 14 bits
• Capacitive Pressure Sensor from Tronics
• Miniaturized Antennae

• Challenges
• Performance antenna, reading distance
• complex functions (sensing tags)

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Wireless link
Figure of merit
c
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Wireless link narrow band zigbee like

• specifications 802.15.4 Zigbee
• 250kbit/s, 10 m
• ISM band 16 channels in 2400-2480MHz
• Various topologies, tens of nodes

• Challenges
• Power reduction
• RF Mems integration (BAW filters)
• RF functions integration
• Routing protocols

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Wireless link UWB
Principle very short pulses (lt 1ns)
Low data rate location

• Objectifs

• challenges
• New architectures
• direct sampling
• pulse genrators
• Synchronisation
• Energy detetction
• antenna

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Integrating system level design IC design
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Design tuning at system level (v.1)

• Breakthroughs in ULP radios complete
  system modeling

fine-tuning of specifications
through system modeling
Impact of receiver imperfections on BER
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Design tuning at system level (v.2)

• Breakthroughs in ULP radios complete
  system modeling

fine-tuning of specifications
through system modeling
Intensive use of high-level languages
(Matlab, System C)
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Matlab simulation chain
channel and some impairments
transmitter
receiver
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Matlab simulation chain

• Models for
• Receiver A/D bits
•  bit true  digital model
• Carrier frequency offsets
• Symbol clock frequency offset
• RF oscillator phase noise (1/f² and white
• Limiter amplifier

• Models for
• Receiver NF
• Receiver gain
• DC offset
• DC offset rejection filter
• IQ imbalance
• Adjacent and alternate channel
• Channel filter

example adjacent channel rejection

• Reference BER formula (non coherent)

• Reference simulation chain
• PER target 1e-2
• PSDU 22 bytes
• BER 5.7e-5

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Conclusions

• Microtechnologies/Mems may lead to breakthrough
  in wireless sensors
• Radio architectures
• Sensor interfaces
• Energy scavenging and management
• The convergence of mechanical/thermal/chemical
  functions and electrical world of ICs
• new design methodologies
• new design tools