Download
jan m rabaey eecs dept univ of california berkeley n.
Skip this Video
Loading SlideShow in 5 Seconds..
Jan M. Rabaey EECS Dept. Univ. of California, Berkeley PowerPoint Presentation
Download Presentation
Jan M. Rabaey EECS Dept. Univ. of California, Berkeley

Jan M. Rabaey EECS Dept. Univ. of California, Berkeley

1 Views Download Presentation
Download Presentation

Jan M. Rabaey EECS Dept. Univ. of California, Berkeley

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Ultra-low power and ultra-low costwireless sensor nodes An integrated perspective Jan M. Rabaey EECS Dept. Univ. of California, Berkeley

  2. 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 enablesenergy scavenging • and form self-configuring ad-hoc networks containing 100’s to 1000’s of nodes Still valid, but pushing the limits ever further

  3. The Incredibly Shrinking Radio PA Test LNATest TX1 Passive Test Structures • 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 Diff Osc Receiver 4 mm Env Det Test TX2 RF Amp Test

  4. 64K memory Base Band Voltage Conv GPIO Interface Serial Interface DW8051 μc Network Queues Locationing Engine Neighbor List System Supervisor DLL Wireless Sensor Network Protocol Processor Integrates all digital protocol and applications functions ofwireless sensor node In fab (Jan 04) Runs reliable and energy-optimizedprotocol stack (from application level down)

  5. The Road towards a First Integrated PicoNode 16kB CODE 4kB XDATA 256 DATA DW8051 Chip Supervisor Serial sfrbus or membus? FlashIF MAC SIF Serial ADC GPIO SIF LocalHW PHY ADC Digital Network Processor Flash Storage 20MHz Clock Source Board Design In Process Powertrain Solar Cell Voltage Supply Voltage Supply Voltage Supply Sensor1 Sensor2 RF Transceiver PrgThresh0 PrgThresh1 Tx0 Tx2 User Interface OOK Receiver OOK Transmitter SIF = sensor interface

  6. 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/s2 1.6% 5.7m/s2 2.6% 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

  7. 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

  8. 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

  9. Service Layer Application Application Interface Query/Command Network Layer Naming Time/Synchronization SNSP Location 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

  10. 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, …)

  11. 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

  12. 1500mm • Fully Integrated • 400mA when active(~200mW with 50% quench duty cycle) 1200mm On the Road:Reducing RF power by another factor of 5 • Providing gain at minimal current: The Super-regenerative Receiver Back from fab any day

  13. Realizing sub-50 mW receivers Example: sub-threshold RF oscillatorusing integrated LCs (in fab) Simulated Performance Next step: mostly untuned radio’s and lots of them Combine with purely statistical routing (in collaboration with Kannan)

  14. Chip Supervisor synch. Tcl TM TM asynch. TM TM Tcl’ Time reference 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! Idea: Self-adapting approach to ULV Status: White paper