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Transcript of 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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
Real-Time DSP Course: Overview
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
Real-Time DSP Course: Overview
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
Lab 1. QAM Transmitter Diagram
LabVIEW Control
PanelQAM
PassbandSignal
Eye Diagram
LabVIEW demo by Zukang Shen (UT Austin)
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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
Lab 3. Digital Filters
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
Lab 3. Digital Filters
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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Prof. Brian L. EvansNI Academic DayJune 30, 2005Beirut, Lebanon
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