infopad and beyondbwrcs.eecs.berkeley.edu/faculty/jan/jansweb/ewexternalfiles... · outline the...

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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displayed.The picture can't be displayed.



DESIGN


HANDWRITINGThe picture can't be displayed.

Scheduling for Quality of Service and

CDMA PowerControl Algorithms

MAC Layer Protocols for Up and Down Links


Optimization of Modulation and SS Techniques

SERVERS

InfoNet

TOOL APPLICATIONS

Capacity Optimization

for Interference Limited, Picocellular Channels


Low PowerMonolithic CMOS Radio Implementations -Wideband Spread Spectrum &



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


Text/Graphics Decompression for Color Display



Migration of processing between Pad and Network

The picture can't be displayed.Network and InfoPad Aware Design Tools

User Interface based on Pen and Speech Input



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.



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

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!

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