ni academic day june 30, 2005 beirut, lebanon modem design, implementation, and testing using ni’s...

NI Academic DayJune 30, 2005Beirut, Lebanon

Modem Design, Implementation, and Testing Using NI’s LabVIEW

Prof. Brian L. EvansDept. of Electrical and Computer Engineering

The University of Texas at Austin, Austin, Texas [email protected]

Visiting Associate ProfessorAmerican University of Beirut, Beirut, Lebanon

Contributions by Vishal Monga, Zukang Shen, Ahmet Toker, and Ian Wong, UT Austin

http://www.wncg.org http://www.ece.utexas.edu

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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon

Outline

Real-Time Digital Signal Processing (DSP) Laboratory Course

Single Carrier Transceiver

Sinusoidal Generation

Digital Filters

Data Scramblers

Pulse Amplitude Modulation

Quadrature Amplitude Modulation

Conclusion

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Real-Time DSP Course: Overview

Objectives of undergraduate class Build intuition for signal processing concepts Translate signal processing concepts into

real-time digital communications software

Lecture: breadth (three hours/week) Digital signal processing algorithms Digital communication systems Digital signal processor architectures

Laboratory: depth (three hours/week) Deliver voiceband modem “Design is the science of tradeoffs” (Prof. Yale Patt, UT) Test/validate implementation

Over 600 served

since 1997

Web site: http://www.ece.utexas.edu/~bevans/courses/realtime/

Download site: http://www.ece.utexas.edu/~bevans/courses/realtime.zip

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Embedded system demand: volume, volume, … 400 Million units/year: automobiles, PCs, cell phones 30 Million units/year: ADSL modems and printers

Consumer electronics products

How much should an embedded processor cost?

Product Average Unit Price

Annual Revenue

Wireless phone $136 $11.5 Billion

Digital cameras $271 $ 4.2 Billion

Portable CD players $ 48 $ 0.9 Billion

MP3 players $137 $ 0.7 Billion

Compact audio systems $111 $ 0.5 Billion

Source: CEA Market Reseach. Data for 2004 calendar year.

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Digital signal processor market 1990-2000 40% annual growth #1 in growth within semiconductor market

Worldwide revenue (US dollars) $6.1B ‘00, $4.5B ‘01, $4.9B ‘02, $6.1B ‘03, $8.0B ‘04 Estimated annual growth of 23% for 2003-2008

Market share (based on 2002 revenue) 43% TI, 14% Freescale, 14% Agere, 9% Analog Dev.

Fixed-point vs. floating-point DSPs >90% of digital signal processors sold are fixed-point Floating–point DSPs used for initial real-time prototype

How many digital signal processors are in a PC?

Revenue figures from Forward Concepts (http://www.fwdconcepts.com)

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Real-Time DSP Course: Which DSP?

Students are next-to-final year (junior) and final-year (senior) undergraduate students

Fixed-point DSPs for high-volume products Battery-powered: cell phones, digital still cameras … Wall-powered: ADSL modems, cellular basestations …

Fixed-point issues Using non-standard C extensions for fractional data Converting floating-point programs to fixed-point Manual tracking of binary point prone to error

Floating-point DSPs Feasibility for fixed-point DSP realization Shorter prototyping time

Program TI TMS320C67x DSP in C TI Code Composer Studio 2.2

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Real-Time DSP Course: Textbooks

C. R. Johnson, Jr., and W. A.Sethares, TelecommunicationBreakdown, Prentice Hall, 2004. Intro to digital communications

and transceiver design Matlab examples

S. A. Tretter, Comm. System Design usingDSP Algorithms with Lab Experiments forthe TMS320C6701 & TMS320C6711, 2003. Assumes DSP theory and algorithms Assumes access to C6000 reference manuals Errata/code: http://www.ece.umd.edu/~tretter

Bill Sethares (Wisconsin)

Rick Johnson (Cornell)

Steven Tretter (Maryland)

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Lab 1. QAM Transmitter DiagramLab 4Rate

Control

Lab 6 QAM

Encoder

Lab 3Tx Filters

Lab 2 Passband

Signal

LabVIEW demo by Zukang Shen (UT Austin)

http://www.ece.utexas.edu/~bevans/courses/realtime/demonstration

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Lab 1. QAM Transmitter Diagram

LabVIEW Control

PanelQAM

PassbandSignal

Eye Diagram

LabVIEW demo by Zukang Shen (UT Austin)

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square root raise cosine, roll-off = 0.75, SNR =

raise cosine, roll-off = 1, SNR = 30 dB

passband signal for 1200 bps mode

passband signal for 2400 bps mode

Lab 1. QAM Transmitter Diagram

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Lab 2. Sine Wave Generation

Aim: Evaluate three waysto generate sine waves insignal quality vs. complexity Function call Lookup table Difference equation

Three output methods Polling data transmit register Software interrupts Direct memory access (DMA) transfers

Expected outcomes are to understand Signal quality vs. implementation complexity tradeoff C6701 EVM board’s stereo codec operation Interrupt mechanisms and DMA transfers

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Lab 2. Sine Wave Generation

Evaluation procedure Validate sine wave frequency on scope, and test for

various sampling rates (14 sampling rates on board) Method 1 with interrupt priorities Method 1 with different DMA initialization(s)

LabVIEW DSP Test Integration Toolkit 2.0

Code Composer Studio 2.2

C6701

Fall 2003

HP 60 MHz

Digital Storage

Oscilloscope

Spring 2004

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Lab 3. Digital Filters

Aim: Evaluate four ways to implementdiscrete-time linear time-invariant filters FIR filter: convolution in C and assembly IIR Filter: direct form and cascade of biquads, both in C

IIR filter design gotchas: oscillation & instability In classical designs, poles sensitive to perturbation Quality factor measures sensitivity of pole pair:

Q [ ½ , ) where Q = ½ dampens and Q = oscillates

Elliptic analog lowpass IIR filter p = 0.21 at p = 20 rad/s and s = 0.31 at s = 30 rad/s [Evans 1999]

Q poles zeros

1.7 -5.3533±j16.9547 0.0±j20.2479

61.0 -0.1636±j19.9899 0.0±j28.0184clas

sica

l

Q poles zeros

0.68 -11.4343±j10.5092 -3.4232±j28.6856

10.00 -1.0926±j21.8241 -1.2725±j35.5476 opti

miz

ed

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IIR filter design for implementation Butterworth/Chebyshev filters special

cases of elliptic filters Minimum order not always most efficient

Filter design gotcha: polynomial inflation Polynomial deflation (rooting) reliable in floating-point Polynomial inflation (expansion) may degrade roots Keep native form computed by filter design algorithm

Expected outcomes are to understand Speedups from convolution assembly routine vs. C Quantization effects on filter stability (IIR) FIR vs. IIR: how to decide which one to use

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Test Equipment Agilent Function Generator HP 60 MHz Digital Storage Oscilloscope Spectrum Analyzer

Evaluation Procedure Sweep filters with sinusoids to construct magnitude and

phase responses• Manually using test equipment, or• Automatically by LabVIEW DSP Test Integration Toolkit

Check filter output for cut-off frequency, roll-off factor… FIR: Compare execution times (in Code Composer) of

• C without compiler optimizations• C with compiler optimizations• C callable assembly language routine

IIR: Compute execution times (in Code Composer)

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Conclusion

ObjectivesBuild intuition for signal processing concepts

Translate signal processing concepts intoreal-time digital communications software

Deliverables and takeawaysDeliver voiceband transceiver

Tradeoffs in signal quality vs. implementation complexity

Test/validate implementation

Extend hands-on experience to broadband modems

Role of technologyTI DSPs and Code Composer Studio

NI LabVIEW and DSP Test Integration Toolkit

ni academic day june 30, 2005 beirut, lebanon modem design, implementation, and testing using ni’s...

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