http://signal.ece.utexas.edu

http://www.cps.utexas.edu

http://www.wncg.org

Embedded Signal Processing

Prof. Brian L. Evans

November 21, 2003

http://www.ece.utexas.edu

2

On My Way to Austin… Signals and Systems Pack

Symbolic analysis of signals and systems in Mathematica

By product of my PhD work On market since 1995

Ptolemy Classic Mixes models of

computation Untimed dataflow Process network Discrete-event

Untimed dataflow synthesis Source code powers Agilent

Advanced Design System

1987-1993

1993-1996

3

Embedded Signal Processing Lab Develop and Disseminate

Theoretical bounds on signal/image quality

Optimal and low-complexity algorithms using bounds

Algorithm suites and fixed-point, real-time prototypes

Analog/Digital IIR Filter Design for Implementation

Butterworth and Chebyshev filters are special cases of Elliptic filters

Minimum order does not always give most efficient implementation

Control quality factors

4

Image Analysis

Ph.D. graduates: Dong Wei (SBC Research) K. Clint Slatton (University of Florida) Wade C. Schwartzkopf (Integrity Applications)

Real-Time Imaging Ph.D. students: Gregory E. Allen (UT Applied Research Labs) Serene BanerjeeMS students: Vishal Monga

Ph.D. graduates: Thomas D. Kite (Audio Precision) Niranjan Damera-Venkata (HP Labs)MS graduates: Young Cho (UCLA)

Ph.D. students: Dogu Arifler Ming Ding

Ph.D. graduates: Güner Arslan (Cicada) Biao Lu (Schlumberger) Milos Milosevic (Schlumberger)

ADSL/VDSL Transceiver Design

Wireless Communications

Ph.D. students: Kyungtae Han Zukang Shen MS students: Ian Wong (NI Summer Intern)

Ph.D. graduate: Murat Torlak (UT Dallas)MS graduates: Srikanth K. Gummadi (TI) Amey A. Deosthali (TI)

Wireless Networking and Comm. Group: http://www.wncg.org

Center for Perceptual Systems: http://www.cps.utexas.edu

Students & Alumni

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Senior Real-time DSP Lab Elective

Lab #6: Quadrature Amplitude Modulation Transmitter

Serial/parallelconverter

Map to 2-D constellation

Impulse modulator

Impulse modulator

Pulse shaper gT(t)

Local Oscillator

+

90o

Pulse shaper gT(t)

d[n]an

bn

a*(t)

b*(t)

s(t)

1 J

Delay

Bit stream

FIR filter

FIR filter

FIR filter

Transmitted signal

6

Senior Real-time DSP Lab Elective

Deliverable: V.22bis Voiceband Modem Design of sinusoidal generators, filters, etc. Program in C on TI DSP processor using Code Composer Studio Test implementation with spectrum analyzers, etc.

Reference Design in LabVIEW Allows Students To Explore communication performance tradeoffs vs. parameters See relationships among modem subsystems in block diagram

LabVIEW DSP Integration Toolkit 2.0 for Spring 2004 Interacts with Code Composer Studio for real-time debugging info Enables all test and measurement to be performed on desktop PC

Course alumni Prethi Gopinath and Newton Petersen at NI

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LabVIEW Interface

Control Panel

Eyediagram

QAMPassband

Signal

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Multicarrier Modulation Divide broadband channel into narrowband subchannels

No inter-symbol interference if constantsubchannel gain and ideal sampling

Based on fast Fourier transform (FFT) Standardized in ADSL/VDSL (wired)

and IEEE 802.11a/g & 802.16a (wireless)

subchannel

frequency

magnitude

carrier

DTFT-1pulse sinc

kcc

k

kc

sin

channel

In ADSL/VDSL, each subchannel is 4.3 kHz wide andcarries a QAM encoded subsymbol

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P/S

QAM demod

decoder

invert channel

=frequency

domainequalizer

S/P

quadrature amplitude

modulation (QAM) encoder

mirrordataand

N-IFFT

add cyclic prefix

P/SD/A +

transmit filter

N-FFTand

removemirrored

data

S/Premove

cyclic prefix

TRANSMITTER

RECEIVER

N/2 subchannels N real samples

N real samplesN/2 subchannels

time domain

equalizer (FIR filter)

receive filter

+A/D

channel

ADSL Transceiver: Data Transmission

Bits

00110

conventional ADSL equalizer structure

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Contributions by Research Group

New Time-Domain Equalizer Design Methods Maximum Bit Rate gives an upper bound Minimum Inter-Symbol Interference method

(amenable to real-time, fixed-point implementation)

Minimum Inter-Symbol Interference Method Reduces number of TEQ taps by a factor of ten

over Minimum Mean Squared Error method for same bit rate

Implemented in real-time on Motorola 56300, TI TMS320C6200 and TI TMS320C5000 DSPshttp://www.ece.utexas.edu/~bevans/projects/adsl

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Wireless Multicarrier Modulation

P/S

QAM demod

decoder

freq. domain

equalizer

S/P

quadrature amplitude

modulation (QAM) encoder

N-pointinverse

FFT

add cyclic prefix

P/SD/A +

transmit filter

N-pointFFT

S/Premove cyclic prefix

TRANSMITTER

RECEIVER

receive filter

+A/D

multipath channel

Bits

00110

Orthogonal frequency division multiplexing (OFDM)

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OFDM Simulation in LabVIEW IEEE 802.16a Standard

Fixed broadband wireless system

High speed wireless access from home or office

IEEE 802.16a Simulation Physical layer

communication Realistic channel models Channel estimation Authored by Alden Doyle,

Kyungtae Han, Ian Wong

www.ece.utexas.edu/~iwong/Research.htm

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Possible LabVIEW Extensions Add communication system design/simulation support for

Drop down and “click to configure” communication building blocks Multicarrier systems and error control coding Performance visualization mechanisms for communication systems

performance analysis (BER curves, eye diagrams, etc.) Text-based algorithm design environment

For quick calculations and parameter calculations Implement a text-to-VI translation tool, e.g. convert math script

“x = [1:10]; y = fft(x)” to a VI implementation Improve optimization toolkit

Make it easier to use Add supports for more extensive set of algorithms

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Fixed-Point Wordlength Optimization

Problem: Manual floating-to-fixed pointconversion for digital hardware implementation

Design time grows exponentially with number of variables

Time consuming Error prone

Goal: Develop fast algorithm tooptimize fixed-point wordlengths

Minimize hardware complexity Maximize application performance

Solution: Simulation-based search Determine minimum wordlength Greedy search algorithm Complexity-and-distortion measure

Wordlength(w)

ComplexityError

[1/performance]

Optimumwordlength

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Wordlength Optimization In LabVIEW

Use broadband wireless access demodulator design Pick four variables and build fixed-point type Manually estimate maximum and minimum values of

these variables for integer wordlength determination Optimize these variables using Greedy search

algorithm with complexity-and-distortion measure

Design

EncoderOFDM

Modulator

WirelessChannelModel

OFDMDemodulator

ChannelEstimator

DecoderBit error

ratetester

DataSource

ChannelEqualizer

w0w1

w2w3

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Possible LabVIEW Extensions

Add fixed-point data type

Build fixed-point arithmetic operations, filtering operations, etc.

Estimate implementation complexity as function of input wordlengths in blocks

Automatically estimate or log max and min values on arcs

Implement wordlength search algorithms

Design

wopt

wb

w1

w2

dw1

dw2

5

5

Max Min IWL

w0 4.8 -4.5 3

W1 3.7 3.7 2

W2 0.8 -0.9 0