Infopad and beyond
http://bwrc.eecs.berkeley.edu
Jan Rabaey & Robert BrodersenMay 18, 1999
Outline
● The precursor to BWRC: The Infopad project
● The sequel: BWRC● Research focus and drivers
Infopad (92-97)
Voice vs. Data?
● Previous telecommunication systems have been optimized for voice
however● More than 50% of telecomm traffic in
Bay Area is now data, not voice» Internet FIND/SVP Survey
– 25% of Internet users make fewer long distance calls
– 32% watch less television
Exponential growth of Internet traffic
(Source: GILDER Technology Report, Nov. 1996)
Tera
byt
esP
erM
onth
400
300
200
100
0
1992
1993
1994
1995
1996
• Growing at the rate off 20% per month• Earlier this year increased 2x in 100 days!
Wireless Internet Access
● Voice communications » Has been the only driver for personal
wireless access » Will evolve to be just one of many services.
● The ideal access device would allow multimedia internet access from any location (like a cellphone does for voice)
● The access device should have the mobility and battery life of a PDA, with the multimedia capability of a PC
The progression towards a Wireless Personal Internet Access Device
● Improving support for data● But so far
» Low bandwidth - optimized for audio and outdoor mobile links
» Low user capacity» Wrong form factor and poor multimedia
support
?
Portable Multimedia Access System
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Set-top box doubles as basestation and gateway from WAN
Allows family andpersonal use
of set-top box access
Infopad Model:Put the Brains in the Net
Internal Architecture
DataFlow
Low Power Bus
RadioModem
Embedded Processor
AudioCodec
VideoDecomp
VideoAudio
Decomp Fifo
Graphics
Pen
Sched ECC Pact Interface
SRAM
DSPBlocks
Infopad Terminal and Basestation
InfoPad Terminal Characteristics
● Supports video, audio and text/graphics● Total number of transistors ~5 million,
custom ~1.5 million
InfoPad Multimedia processing
ARM / RAM / EPROM SIO
RadioReceiver
RadioTransmitter244Kbaud
625Kbit/s
PenDigitizerKeyboard port
CODEC /
ProcessorInterface
Receiver Interface
TransmitterInterface
Pen/KeyboardInterface
Speech/AudioInterface
Text/GraphicsInterface
VideoInterface
FrameBufferRams
Color VideoDecompression Chip Set
LCD640x480
ColorAMLCD
5 volts1.5 volts
SynchronizationError CorrectionCRC
amplifiers
InfoPad circuitry
The Cost of Generality
● Energy Optimized and Dedicated» 100 Mops/mW
● Energy Optimized but General Purpose» Keep the generality, but reduce the energy
as much as possible - e.g. StrongArm
» .5 Watts, 130 Mips = 3 Mops/mW
● Performance Optimized » Clock rate is everything … somehow we�ll
get the power into it and back out..
» 10-100 Watts, 100-1000 Mips = .01 Mops/mW
InfoPad Software Support
BaseStation
Application
Application
Application
InfoNetSingleLogical
Pad
Network software support
BaseStation
RecognizersVirtual frame buffer
Pen and audio interfaces
Mobility supportName server
Video transcoding
SchedulingRadio protocols
Hardware support
InfoPads
Infonet ArchitectureBackbone Network - ATM
MULTIMEDIA
INFOPADS
CELL
SERVERS
GATEWAY
Ether
PADSERVERS
CELLPAD
ManagementManagement
SERVERS
X-WindowVideoAudioPen
+ Recognizers
Physical Link
0 20 40 60 80 100Time(ms)
0.0
200.0
400.0
600.0Samples
Latency MeasurementsVideo and Pen in separate streams
6 InfoPad Groups
● User Interface (Brewer, Rowe)» Middleware and multimodal input
● Medley (Messerschmitt)» Backbone network protocols supporting QOS
● Infonet (Rabaey, Brodersen, Katz)» Mobile network protocols and servers
● RF (Gray, Meyer)» CMOS RF for wide and narrowband transceivers
● Terminal (Brodersen) - Low power digital design● CAD (Rabaey) - Support for low power
The Success of InfoPad - the Research Projects
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ATM and Fast Ethernet Backbone
BASE STATION SPEECH AND
RECOGNITION
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DESIGN
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HANDWRITINGThe picture can't be displayed.
Scheduling for Quality of Service and
CDMA PowerControl Algorithms
MAC Layer Protocols for Up and Down Links
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Optimization of Modulation and SS Techniques
SERVERS
InfoNet
TOOL APPLICATIONS
Capacity Optimization
for Interference Limited, Picocellular Channels
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Low PowerMonolithic CMOS Radio Implementations -Wideband Spread Spectrum &
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Energy Optimized ARM Processor CoreThe picture can't be displayed.
Low Power Signal Processing AcceleratorsThe picture can't be displayed.
Concurrent Electrical/Mechanical Casing DesignThe picture can't be displayed.
System Level Power Analysis Tools
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Text/Graphics Decompression for Color Display
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Migration of processing between Pad and Network
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User Interface based on Pen and Speech Input
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Support for Distributed Processing for the Mobile Network
NAMESERVER,CELL and PAD
SERVERS
InfoNet
(the InfoNet)
AUDIO, PENAND VIDEOTYPE
and WIRED toWIRELESSBRIDGE
Indoor Picocellular Channel MeasurementsThe picture can't be displayed.
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DECT Radio (TDMA)
What didn�t work...
● Interaction with industry - great during retreats, but inconsistent in between
● Communication between groups» 45 students - 8 faculty» Large overhead in meetings» Collaborative tools didn�t work
● No common environment - Spread between multiple floors of Cory and Soda hall
● Large-scale deploymentThis revealed the need for a new model:
BWRC
Berkeley Wireless Research Center (BWRC)
Conventional cellular phone solution
• Research into technology and design methodologies for CMOS single chip radios
• Exploring future applications of wireless technology, 4th generation and beyond
BWRC - Statement of Purpose
Provide an environment for research into the design issues necessary to support future wireless communication systems.The focus will be on highly integrated CMOS implementations which have the lowest possible energy consumption while using the most-advanced communication algorithms.
Berkeley Wireless Research Center
● Intended life time of at least 6 years, with yearly reviews, and informal commitments of 3 years
● 45 graduate researchers, 10 faculty, industrial and academic visitors
● University affiliated, but infrastructure supported by industry through overhead-free gifts
● 7 member companies in first phase
● Officially opened on Jan. 29, 1999
Center Management and Faculty
● Technical Director: Gary Kelson● Scientific Co-directors: Robert Brodersen and Jan Rabaey● Faculty
» Randy Katz — Wireless network protocols» Anthony Joseph - Mobile applications» David Tse — Communications theory multi-users and multi-antenna» Jan Rabaey — Digital low power, design methodology» Alberto Sangiovanni-Vincentelli — Design methodology» Robert Brodersen — Circuit design, radio architecture and design
methodology» Paul Gray — Analog RF design, radio architecture» Bob Meyer — Analog RF design» Chenming Hu — Ultra-scaled CMOS technology and modeling» Paul Wright - Case design and manufacture
Center Industrial Members
● Cadence● Ericsson● HP● Intel● Lucent● ST-Microelectronics● TI
Combining wireless systems, semiconductor, and and design methodology industries.
The BWRC Set-up
● Floorplan optimized for interaction
● Off campus, but within walking distance from Cory» 11,000 square foot
office space● To be treated as the
6th floor of Cory Hall
GSRC
Goal: Develop methodology for next-generation IC designs
● Brings together multiple universities in distributed research activity
● Effort led by single university● Focus is break-through
research● Funded at 4 M$ in year 1 & 2,
going up to 9 M$ in year 3
Active cooperation between BWRC and GSRC
Research Focus Center on Design and Test
Center Drivers
● Universal Radio» Allows uncoordinated use of spectra without loss in capacity
» Extensible over time to exploit advances in technology and
support new applications
● Ultra Low-Power PicoRadio» System-on-a chip implementation supporting all functions up to
external world interface (sensors, transducers)
» Total power dissipation in the 100�s of microwatts
● Millimeter Radio» Investigates radio architectures for future CMOS processes ( <
0.05 µm) which allows use of bands of > 50GHz
Universal Radio Goals
● Provide a strategy for peaceful coexistence in unlicensed RF bands
● Supports evolution of technology and applications in a heterogeneous environment
● Change the way spectrum is allocated By using the following channel use strategy:● Maximum capacity by local optimization ● Higher transmit powers are allowed if a user
» localizes in time-frequency-spatial signal space» facilitates adaptation by other users
Measures of Success
● Demonstrate the coexistence of multiple services with incompatible characteristics in the presence of an alien interfering system
● Developed a design methodology which allows rapid implementation of the universal radios with varying characteristics
● Change the strategy, approach, paradigm that standards bodies use for frequency allocation
Increased Spectral Efficiency Through Aggressive Signal Processing
SBaseband Signal
Despreading
X
AdaptiveError
Signal
Convergence speed
Aver
age
SIR
(db)
Unquantized
8 bit
4 bit
● Tracks changes in channel, environment, and interfering users
● Uses common error metrics such as MSE, and common algorithms such as LMS and RMS
Example: Adaptive Multi-User Detection for CDMA
Increasing Algorithm ComplexityImproves Convergence
Block RLS using Gramm-Schmitt Decomposition
1.375 Gmults/secfor 25 Mchip/sec rate
Huge computational complexity
The Implementation Trade-off
Signal Update BlockAcquisition andTiming Recovery Signal Update Block
AdaptivePilot
Correlator
A d a p t iveD ata
C or re la tor
C0 CL-1
Digital Baseband
Sk
...
Data Out
Receiver
ChannelCoefficientEstimates
AdaptivePilot
Correlator
Dat
a In
300 million multiplications/sec357 million add-sub�s/sec
Adaptive multi-user detection
Adaptive Correlator — Direct Mapping
Power and area are dominated by MACs and multipliesOnly 36% of power of DSP-processor solution going into arithmetic
Adaptive Multi-User Detection Test Chip
Correlator
PicoRadio Goals
Develop meso-scale radio�s for ubiquitous wireless data acquisition that minimize power/energy dissipation » Minimize energy (<10 pJ/(correct) bit) for energy-
limited source» Minimize power (< 1 mW) for power-limited source
(e.g. based on energy scavenging)
By using the following strategies» self-configuring networks» fluid trade-off between communication and
computation» aggressive low-energy architectures and circuits
Possible applications
● The wireless home (system size: 50-100 m)● Atomic picocellular wireless systems
(system dimension < 5 m)» Self-composing systems
– virtual keyboard or notepad– smart environments (cabinet, fridge, store)– wireless backplanes (phone, computer, multimedia)– bodyLAN
» Human-environment interaction– identification, personalization
The Wireless Home
Monitoring and Control• Identification, location, and security• Climate • Environment set-upNetwork of sensors, actuators, and monitors
Multimedia data networking• Routing of periodic, high BW data between network of sourcesand destinations (voice, adio, video)
Data networking• Burst-mode access of high BW data sources (internet access)
The Wireless Home — Observations
● Requires diversity of communication, reliability, and bandwidth requirements (high bandwidth periodic, high rate bursty, low rate bursty)» migrating all these functions into single wireless service will most
probably lead to severe energy-inefficiency (worth checking if this is really true …)
» better solution seems to be co-existing wireless networks with appropriate bridging elements
● Single-cell implementation is inappropriate due to system-size, cannot assume wired backplane either. Most plausible scenario:
– single basestation (control center) with high-energy downlink– multi-hop uplink from sources to destinations. Hop distance
dynamically determined by network density
Atomic Picocellular Systems
● Single cell environment - no network issues as in the wireless home
● Self-configuring is crucial. » System could contain hundreds or thousands
of transceivers. Coordinated and managed configuration seems painful.
» Poses interesting protocol issues
Energy/Power is be the absolute central focus!
- foremost: low-energy wireless system design» adaptive wireless systems
Dynamic trade-off between computation and communication is the key to system-level energy optimization
» energy minimization through all the abstraction layersapplication, network, media access, physical
- implementation methodologies to enable the above- radio architectures - what needs to be adaptive or what is fixed?- circuit implementation - how the get the best buck for the pJ- approaches to energy-scavenging- design methodology
- self-configuring and adaptive protocols, communication channel design- automating the design generation process
Intercom Project
● Design driver for Design Methodologies project
● Goal: fully integrated radios to support digital intercom function within group of mobile users
● Properties: single cell, PCM voice only (initially)
Short-term Driver: Digital IntercomBasestation
Mobiles
Implementation Platform
Programmable Logic
EmbeddedStrongARM Processor
1.6 Mbit/secFH Radio (Proxim)
Up to 20 users per cell @ 64 kbit/sec per linkTDMA selected as MAC protocol Towards single chipExercises the complete design flow from high-level specification
Digital Intercom
● Intended as wireless testbed and prototyping environment for picoradio
● Initial implementation based on Infopad chassis and off-the-shelf hardware
● Designed to allow for interchangeable radio modules (DECT, Frequency hopping, CDMA)
● Software support includes RTOS and wireless protocol stack
�PicoNode� for Sensor Networks
● Single-chip node provides all communication, geolocation and computation functions, necessary for an adaptive distributed sensor network
● Proposal submitted to DARPA (1/99) and approved (2/99)
● Main Premises:» integration leads to lowest cost, size, and energy» integration of communication and computation
enables fluid optimization of communication versus compression, depending upon system requirements and environment
�PicoNode� for Sensor Networks
● Single-chip node provides all communication, geolocation and computation functions, necessary for an adaptive distributed sensor network
● Proposal submitted to DARPA (1/99) and approved (2/99)
● Main Premises:» integration leads to lowest cost, size, and energy» integration of communication and computation
enables fluid optimization of communication versus compression, depending upon system requirements and environment
Communication versus Computation
● Computation cost (2004): 60 pJ/operation (assuming continued scaling)
● Communication cost (thermal energy minimum):» 100 m distance: 20 nJ/bit @ 1.5 GHz
» 10 m distance: 2 pJ/bit @ 1.5 GHz
● Computation versus Communications» 100 m distance: 300 operations == 1bit
» 10 m distance: 0.03 operation == 1bit
Computation/Communication requirements vary with distance, data type, and environment
System-Level Energy Minimization
● Dominant factor in energy equation determined by BW and distance requirements» for cells smaller than 10 m transmitting 1 Kbits/sec communication
energy can be ignored. Energy-efficient computation is key.» This is not the case if the distance is increased to 100 m (size of a
home). Minimization of communication energy becomes a prime driver. Partitioning of the link and the use of repeaters is beneficial (similar to interconnect on chips - but much more outspoken)
● Finding the right optimum is even-harder in self-configuring systems» precise location and communication requirements of subscribers
not known in advance and vary over time» no (or little) background infrastructure or coordination
Explore Energy Efficiency of Existing Protocols
● Existing Protocols for Wireless Networks, or �ad hoc networks�» Destination-Sequenced Distance Vector» Dynamic Source Routing» Temporally-Ordered Routing Algorithm» Ad Hoc On-Demand Distance Vector» Wireless LAN
Low-Power Network Protocols
● Investigation of existing routing protocols
that minimize Energy Cost Function
» Which is better? More Hops or Longer Hops?
● Cost = F(cost per hop, # of hops, ???)
» Must determine what other parameters affect
the energy cost function.
System-Level Energy Minimization
● Trade�offs at the MAC-level:» synchronous access control probably most energy-
efficient, but hard to implement in environment with large number of transceivers + incurs protocol communication overhead
» non-coordinated asynchronous access incurs some inefficiency due to access conflicts, but has advantage of reduced coordination overhead and potentially can evolve to energy-efficient optimum + simpler and more robust
Architecture Level
● Energy-efficiency dictates custom implementation of often recurring functions
● Adaptivity and configurability requires some level of programmability for protocol and communication processing» protocol processing: study of energy-efficiency of
implementation platforms: custom, standard cell, network of PLA�s, FPGA, array of nanoRISCs, microprocessor will help us to delineate the trade-off space
» better insight in communication processing
PicoNode for Sensor Networks
EmbeddedMicroprocessor
Dedicated
Signal
Analog RF, GPS
Reconfigurable
ReconfigurableLogic
receiver and
Processor Digital
Processing
sensor interface
Heterogeneous Implementation Architecture allowsfor Trade-off between Flexibility and Efficiency
Ultra Low-energy Circuit Design
● Dropping voltage down to minimum possible levels (between 100 and 500 mV)
● Study potential of sub-threshold operation, and activity-based threshold control
● Study impact of burst-mode operation on circuit design; e.g. potential of dynamic voltage scaling, current-mode logic, and adiabatic design
● Study impact of performance variations on circuit architecture; self-timing or mesochronous designs
Means of energy-scavenging
● Motion (I.e. wrist watch, ID�s, pens)● Light (sensors)● Pressure● Recycle energy from cheap down-link to
expensive up-link
● Of course, batteries are always an option if one can keep the energy dissipation of the component ignorable!